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You searched for subject:(DNN). Showing records 1 – 30 of 42 total matches.

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University of Limerick

1. Zeng, Jing. Using DotNetNuke in development and implementation of marine robotics research at University of Limerick.

Degree: 2013, University of Limerick

non-peer-reviewed

This thesis explores using the open source content management system DotNetNuke (DNN) for the design and implementation of a portal website for the Mobile… (more)

Subjects/Keywords: DotNetNuke; DNN

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Zeng, J. (2013). Using DotNetNuke in development and implementation of marine robotics research at University of Limerick. (Thesis). University of Limerick. Retrieved from http://hdl.handle.net/10344/5169

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Zeng, Jing. “Using DotNetNuke in development and implementation of marine robotics research at University of Limerick.” 2013. Thesis, University of Limerick. Accessed March 04, 2021. http://hdl.handle.net/10344/5169.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Zeng, Jing. “Using DotNetNuke in development and implementation of marine robotics research at University of Limerick.” 2013. Web. 04 Mar 2021.

Vancouver:

Zeng J. Using DotNetNuke in development and implementation of marine robotics research at University of Limerick. [Internet] [Thesis]. University of Limerick; 2013. [cited 2021 Mar 04]. Available from: http://hdl.handle.net/10344/5169.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Zeng J. Using DotNetNuke in development and implementation of marine robotics research at University of Limerick. [Thesis]. University of Limerick; 2013. Available from: http://hdl.handle.net/10344/5169

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


Texas A&M University

2. Yeh, Rachel Hsingtze. DNN Weight Compression Method with ADMM Framework.

Degree: MS, Electrical Engineering, 2019, Texas A&M University

 Deep neural networks (DNNs) is a powerful technique evolved to the state-of-the-art technique for computer vision tasks. The "deep compression" is introduced to overcome the… (more)

Subjects/Keywords: DNN Compression; ADMM

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APA (6th Edition):

Yeh, R. H. (2019). DNN Weight Compression Method with ADMM Framework. (Masters Thesis). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/188818

Chicago Manual of Style (16th Edition):

Yeh, Rachel Hsingtze. “DNN Weight Compression Method with ADMM Framework.” 2019. Masters Thesis, Texas A&M University. Accessed March 04, 2021. http://hdl.handle.net/1969.1/188818.

MLA Handbook (7th Edition):

Yeh, Rachel Hsingtze. “DNN Weight Compression Method with ADMM Framework.” 2019. Web. 04 Mar 2021.

Vancouver:

Yeh RH. DNN Weight Compression Method with ADMM Framework. [Internet] [Masters thesis]. Texas A&M University; 2019. [cited 2021 Mar 04]. Available from: http://hdl.handle.net/1969.1/188818.

Council of Science Editors:

Yeh RH. DNN Weight Compression Method with ADMM Framework. [Masters Thesis]. Texas A&M University; 2019. Available from: http://hdl.handle.net/1969.1/188818


Georgia Tech

3. Immanuel, Yehowshua U. PLUG-AND-PLAY FOSS ML ACCELERATOR : FROM CONCEPT TO CONCEPTION.

Degree: MS, Electrical and Computer Engineering, 2020, Georgia Tech

 ML accelerators are a fairly new research area and it is important that the archi- tecture community is able to iterate quickly on architectural exploration.… (more)

Subjects/Keywords: DNN Accelerator; AI

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APA (6th Edition):

Immanuel, Y. U. (2020). PLUG-AND-PLAY FOSS ML ACCELERATOR : FROM CONCEPT TO CONCEPTION. (Masters Thesis). Georgia Tech. Retrieved from http://hdl.handle.net/1853/64210

Chicago Manual of Style (16th Edition):

Immanuel, Yehowshua U. “PLUG-AND-PLAY FOSS ML ACCELERATOR : FROM CONCEPT TO CONCEPTION.” 2020. Masters Thesis, Georgia Tech. Accessed March 04, 2021. http://hdl.handle.net/1853/64210.

MLA Handbook (7th Edition):

Immanuel, Yehowshua U. “PLUG-AND-PLAY FOSS ML ACCELERATOR : FROM CONCEPT TO CONCEPTION.” 2020. Web. 04 Mar 2021.

Vancouver:

Immanuel YU. PLUG-AND-PLAY FOSS ML ACCELERATOR : FROM CONCEPT TO CONCEPTION. [Internet] [Masters thesis]. Georgia Tech; 2020. [cited 2021 Mar 04]. Available from: http://hdl.handle.net/1853/64210.

Council of Science Editors:

Immanuel YU. PLUG-AND-PLAY FOSS ML ACCELERATOR : FROM CONCEPT TO CONCEPTION. [Masters Thesis]. Georgia Tech; 2020. Available from: http://hdl.handle.net/1853/64210


Georgia Tech

4. Kwon, Hyouk Jun. Data- and communication-centric approaches to model and design flexible deep neural network accelerators.

Degree: PhD, Computer Science, 2020, Georgia Tech

 Deep neural network (DNN) accelerators, which are specialized hardware for DNN inferences, enabled energy-efficient and low-latency DNN inferences. To maximize the efficiency (energy efficiency, latency,… (more)

Subjects/Keywords: DNN accelerator; DNN dataflow; DNN mapping; Flexible mapping accelerator

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APA (6th Edition):

Kwon, H. J. (2020). Data- and communication-centric approaches to model and design flexible deep neural network accelerators. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/63663

Chicago Manual of Style (16th Edition):

Kwon, Hyouk Jun. “Data- and communication-centric approaches to model and design flexible deep neural network accelerators.” 2020. Doctoral Dissertation, Georgia Tech. Accessed March 04, 2021. http://hdl.handle.net/1853/63663.

MLA Handbook (7th Edition):

Kwon, Hyouk Jun. “Data- and communication-centric approaches to model and design flexible deep neural network accelerators.” 2020. Web. 04 Mar 2021.

Vancouver:

Kwon HJ. Data- and communication-centric approaches to model and design flexible deep neural network accelerators. [Internet] [Doctoral dissertation]. Georgia Tech; 2020. [cited 2021 Mar 04]. Available from: http://hdl.handle.net/1853/63663.

Council of Science Editors:

Kwon HJ. Data- and communication-centric approaches to model and design flexible deep neural network accelerators. [Doctoral Dissertation]. Georgia Tech; 2020. Available from: http://hdl.handle.net/1853/63663


University of Ottawa

5. Li, Dongfu. Deep Neural Network Approach for Single Channel Speech Enhancement Processing .

Degree: 2016, University of Ottawa

 Speech intelligibility represents how comprehensible a speech is. It is more important than speech quality in some applications. Single channel speech intelligibility enhancement is much… (more)

Subjects/Keywords: DNN; GMM; MRCG; Single-channel speech processing

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APA (6th Edition):

Li, D. (2016). Deep Neural Network Approach for Single Channel Speech Enhancement Processing . (Thesis). University of Ottawa. Retrieved from http://hdl.handle.net/10393/34472

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Li, Dongfu. “Deep Neural Network Approach for Single Channel Speech Enhancement Processing .” 2016. Thesis, University of Ottawa. Accessed March 04, 2021. http://hdl.handle.net/10393/34472.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Li, Dongfu. “Deep Neural Network Approach for Single Channel Speech Enhancement Processing .” 2016. Web. 04 Mar 2021.

Vancouver:

Li D. Deep Neural Network Approach for Single Channel Speech Enhancement Processing . [Internet] [Thesis]. University of Ottawa; 2016. [cited 2021 Mar 04]. Available from: http://hdl.handle.net/10393/34472.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Li D. Deep Neural Network Approach for Single Channel Speech Enhancement Processing . [Thesis]. University of Ottawa; 2016. Available from: http://hdl.handle.net/10393/34472

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


Delft University of Technology

6. Koning, Tim (author). Low level quadcopter control using Reinforcement Learning: Developing a self-learning drone.

Degree: 2020, Delft University of Technology

 Reinforcement Learning (RL) is a learning paradigm where an agent learns a task by trial and error. The agent needs to explore its environment and… (more)

Subjects/Keywords: Reinforcement Learning; AI; DNN; quadcopter; TD3; DDPG

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APA (6th Edition):

Koning, T. (. (2020). Low level quadcopter control using Reinforcement Learning: Developing a self-learning drone. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:0b9e0796-13b5-42ba-b231-fbb6aadd5233

Chicago Manual of Style (16th Edition):

Koning, Tim (author). “Low level quadcopter control using Reinforcement Learning: Developing a self-learning drone.” 2020. Masters Thesis, Delft University of Technology. Accessed March 04, 2021. http://resolver.tudelft.nl/uuid:0b9e0796-13b5-42ba-b231-fbb6aadd5233.

MLA Handbook (7th Edition):

Koning, Tim (author). “Low level quadcopter control using Reinforcement Learning: Developing a self-learning drone.” 2020. Web. 04 Mar 2021.

Vancouver:

Koning T(. Low level quadcopter control using Reinforcement Learning: Developing a self-learning drone. [Internet] [Masters thesis]. Delft University of Technology; 2020. [cited 2021 Mar 04]. Available from: http://resolver.tudelft.nl/uuid:0b9e0796-13b5-42ba-b231-fbb6aadd5233.

Council of Science Editors:

Koning T(. Low level quadcopter control using Reinforcement Learning: Developing a self-learning drone. [Masters Thesis]. Delft University of Technology; 2020. Available from: http://resolver.tudelft.nl/uuid:0b9e0796-13b5-42ba-b231-fbb6aadd5233


University of Texas – Austin

7. -5451-7038. Bit error tolerance of Deep Neural Network accelerators.

Degree: MSin Engineering, Electrical and Computer Engineering, 2020, University of Texas – Austin

 The resurgence of machine learning in various applications and it's inherent compute-intensive nature require hardware accelerators in the edge devices. The underlying process technology is… (more)

Subjects/Keywords: DNN; Fault tolerance; Neural network accelerators

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APA (6th Edition):

-5451-7038. (2020). Bit error tolerance of Deep Neural Network accelerators. (Masters Thesis). University of Texas – Austin. Retrieved from http://dx.doi.org/10.26153/tsw/11332

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

Chicago Manual of Style (16th Edition):

-5451-7038. “Bit error tolerance of Deep Neural Network accelerators.” 2020. Masters Thesis, University of Texas – Austin. Accessed March 04, 2021. http://dx.doi.org/10.26153/tsw/11332.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

MLA Handbook (7th Edition):

-5451-7038. “Bit error tolerance of Deep Neural Network accelerators.” 2020. Web. 04 Mar 2021.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

Vancouver:

-5451-7038. Bit error tolerance of Deep Neural Network accelerators. [Internet] [Masters thesis]. University of Texas – Austin; 2020. [cited 2021 Mar 04]. Available from: http://dx.doi.org/10.26153/tsw/11332.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

Council of Science Editors:

-5451-7038. Bit error tolerance of Deep Neural Network accelerators. [Masters Thesis]. University of Texas – Austin; 2020. Available from: http://dx.doi.org/10.26153/tsw/11332

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

8. Houidhek, Amal. Synthèse paramétrique de la parole Arabe : Parametric synthesis of Arabic speech.

Degree: Docteur es, Informatique, 2020, Université de Lorraine; Université de Tunis El Manar

Cette thèse porte sur l’adaptation de la synthèse paramétrique de la parole à partir d’un texte écrit à la langue arabe. Pour ce faire, différentes… (more)

Subjects/Keywords: Langue arabe; HMM; DNN; Gémination; Voyelles; Arabic language; HMM; DNN; Geminated consonants; Long vowels; 492.702 85; 006.54; 410.285

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APA (6th Edition):

Houidhek, A. (2020). Synthèse paramétrique de la parole Arabe : Parametric synthesis of Arabic speech. (Doctoral Dissertation). Université de Lorraine; Université de Tunis El Manar. Retrieved from http://www.theses.fr/2020LORR0116

Chicago Manual of Style (16th Edition):

Houidhek, Amal. “Synthèse paramétrique de la parole Arabe : Parametric synthesis of Arabic speech.” 2020. Doctoral Dissertation, Université de Lorraine; Université de Tunis El Manar. Accessed March 04, 2021. http://www.theses.fr/2020LORR0116.

MLA Handbook (7th Edition):

Houidhek, Amal. “Synthèse paramétrique de la parole Arabe : Parametric synthesis of Arabic speech.” 2020. Web. 04 Mar 2021.

Vancouver:

Houidhek A. Synthèse paramétrique de la parole Arabe : Parametric synthesis of Arabic speech. [Internet] [Doctoral dissertation]. Université de Lorraine; Université de Tunis El Manar; 2020. [cited 2021 Mar 04]. Available from: http://www.theses.fr/2020LORR0116.

Council of Science Editors:

Houidhek A. Synthèse paramétrique de la parole Arabe : Parametric synthesis of Arabic speech. [Doctoral Dissertation]. Université de Lorraine; Université de Tunis El Manar; 2020. Available from: http://www.theses.fr/2020LORR0116


University of California – Riverside

9. Rakesh Kumar, Ankith Jain. Statistical Analysis of WCET on DNN.

Degree: Electrical Engineering, 2018, University of California – Riverside

 The current research work on determining the worst-case execution time (WCET)focuses mainly on real-time systems since this is a key parameter in evaluating the reliabilityof… (more)

Subjects/Keywords: Electrical engineering; Computer engineering; DNN; EVT; GEV; GPD; MBPTA-CV; pWCET

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APA (6th Edition):

Rakesh Kumar, A. J. (2018). Statistical Analysis of WCET on DNN. (Thesis). University of California – Riverside. Retrieved from http://www.escholarship.org/uc/item/3vz734j8

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Rakesh Kumar, Ankith Jain. “Statistical Analysis of WCET on DNN.” 2018. Thesis, University of California – Riverside. Accessed March 04, 2021. http://www.escholarship.org/uc/item/3vz734j8.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Rakesh Kumar, Ankith Jain. “Statistical Analysis of WCET on DNN.” 2018. Web. 04 Mar 2021.

Vancouver:

Rakesh Kumar AJ. Statistical Analysis of WCET on DNN. [Internet] [Thesis]. University of California – Riverside; 2018. [cited 2021 Mar 04]. Available from: http://www.escholarship.org/uc/item/3vz734j8.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Rakesh Kumar AJ. Statistical Analysis of WCET on DNN. [Thesis]. University of California – Riverside; 2018. Available from: http://www.escholarship.org/uc/item/3vz734j8

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


IUPUI

10. Sinha, Debjyoti. Design Space Exploration of MobileNet for Suitable Hardware Deployment.

Degree: 2020, IUPUI

Indiana University-Purdue University Indianapolis (IUPUI)

Designing self-regulating machines that can see and comprehend various real world objects around it are the main purpose of the… (more)

Subjects/Keywords: Design Space Exploration; DNN; iMX RT1060; Data augmentation

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APA (6th Edition):

Sinha, D. (2020). Design Space Exploration of MobileNet for Suitable Hardware Deployment. (Thesis). IUPUI. Retrieved from http://hdl.handle.net/1805/22661

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Sinha, Debjyoti. “Design Space Exploration of MobileNet for Suitable Hardware Deployment.” 2020. Thesis, IUPUI. Accessed March 04, 2021. http://hdl.handle.net/1805/22661.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Sinha, Debjyoti. “Design Space Exploration of MobileNet for Suitable Hardware Deployment.” 2020. Web. 04 Mar 2021.

Vancouver:

Sinha D. Design Space Exploration of MobileNet for Suitable Hardware Deployment. [Internet] [Thesis]. IUPUI; 2020. [cited 2021 Mar 04]. Available from: http://hdl.handle.net/1805/22661.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Sinha D. Design Space Exploration of MobileNet for Suitable Hardware Deployment. [Thesis]. IUPUI; 2020. Available from: http://hdl.handle.net/1805/22661

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


University of Ontario Institute of Technology

11. Ren, Rui. Deep learning methods applied to anomaly detection in vehicle manufacturing and operations.

Degree: 2019, University of Ontario Institute of Technology

 As one of the most common modes of transportation, vehicles are very closely related to our lives. As a result, safety is an important issue… (more)

Subjects/Keywords: Artificial intelligence; Deep learning; Defect detection; Deep neural networks (DNN); Autoencoder

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APA (6th Edition):

Ren, R. (2019). Deep learning methods applied to anomaly detection in vehicle manufacturing and operations. (Thesis). University of Ontario Institute of Technology. Retrieved from http://hdl.handle.net/10155/1071

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Ren, Rui. “Deep learning methods applied to anomaly detection in vehicle manufacturing and operations.” 2019. Thesis, University of Ontario Institute of Technology. Accessed March 04, 2021. http://hdl.handle.net/10155/1071.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Ren, Rui. “Deep learning methods applied to anomaly detection in vehicle manufacturing and operations.” 2019. Web. 04 Mar 2021.

Vancouver:

Ren R. Deep learning methods applied to anomaly detection in vehicle manufacturing and operations. [Internet] [Thesis]. University of Ontario Institute of Technology; 2019. [cited 2021 Mar 04]. Available from: http://hdl.handle.net/10155/1071.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Ren R. Deep learning methods applied to anomaly detection in vehicle manufacturing and operations. [Thesis]. University of Ontario Institute of Technology; 2019. Available from: http://hdl.handle.net/10155/1071

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


IUPUI

12. Chappa, Naga Venkata Sai Raviteja. Squeeze-and-Excitation SqueezeNext: An Efficient DNN for Hardware Deployment.

Degree: 2020, IUPUI

Indiana University-Purdue University Indianapolis (IUPUI)

Convolution neural network is being used in field of autonomous driving vehicles or driver assistance systems (ADAS), and has achieved… (more)

Subjects/Keywords: BlueBox 2.0; CNN; DNN; i.Mx-RT1060; Machine Learning

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Chappa, N. V. S. R. (2020). Squeeze-and-Excitation SqueezeNext: An Efficient DNN for Hardware Deployment. (Thesis). IUPUI. Retrieved from http://hdl.handle.net/1805/22611

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Chappa, Naga Venkata Sai Raviteja. “Squeeze-and-Excitation SqueezeNext: An Efficient DNN for Hardware Deployment.” 2020. Thesis, IUPUI. Accessed March 04, 2021. http://hdl.handle.net/1805/22611.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Chappa, Naga Venkata Sai Raviteja. “Squeeze-and-Excitation SqueezeNext: An Efficient DNN for Hardware Deployment.” 2020. Web. 04 Mar 2021.

Vancouver:

Chappa NVSR. Squeeze-and-Excitation SqueezeNext: An Efficient DNN for Hardware Deployment. [Internet] [Thesis]. IUPUI; 2020. [cited 2021 Mar 04]. Available from: http://hdl.handle.net/1805/22611.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Chappa NVSR. Squeeze-and-Excitation SqueezeNext: An Efficient DNN for Hardware Deployment. [Thesis]. IUPUI; 2020. Available from: http://hdl.handle.net/1805/22611

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


Iowa State University

13. Qasaimeh, Murad. Efficient processing of vision kernels and deep neural networks on reconfigurable computing architectures.

Degree: 2020, Iowa State University

 Computer vision algorithms empowered with the recent advances in deep learning play a fundamental role in solving many problems that seemed impossible just a decade… (more)

Subjects/Keywords: Computer Vision; Convolution Operation; DNN; FPGA; GPU; Hardware Acceleration

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Qasaimeh, M. (2020). Efficient processing of vision kernels and deep neural networks on reconfigurable computing architectures. (Thesis). Iowa State University. Retrieved from https://lib.dr.iastate.edu/etd/18381

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Qasaimeh, Murad. “Efficient processing of vision kernels and deep neural networks on reconfigurable computing architectures.” 2020. Thesis, Iowa State University. Accessed March 04, 2021. https://lib.dr.iastate.edu/etd/18381.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Qasaimeh, Murad. “Efficient processing of vision kernels and deep neural networks on reconfigurable computing architectures.” 2020. Web. 04 Mar 2021.

Vancouver:

Qasaimeh M. Efficient processing of vision kernels and deep neural networks on reconfigurable computing architectures. [Internet] [Thesis]. Iowa State University; 2020. [cited 2021 Mar 04]. Available from: https://lib.dr.iastate.edu/etd/18381.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Qasaimeh M. Efficient processing of vision kernels and deep neural networks on reconfigurable computing architectures. [Thesis]. Iowa State University; 2020. Available from: https://lib.dr.iastate.edu/etd/18381

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


NSYSU

14. Wu, Pei-Hsuan. Architecture Design and Implementation of Deep Neural Network Hardware Accelerators.

Degree: Master, Computer Science and Engineering, 2018, NSYSU

 Deep Neural Networks (DNN) widely used in computer vision applications have superior performance in image classification and object detection. However, the huge amount of data… (more)

Subjects/Keywords: CNN hardware accelerator; deep neural network (DNN); convolutional neural network (CNN); machine learning

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Wu, P. (2018). Architecture Design and Implementation of Deep Neural Network Hardware Accelerators. (Thesis). NSYSU. Retrieved from http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0729118-154714

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Wu, Pei-Hsuan. “Architecture Design and Implementation of Deep Neural Network Hardware Accelerators.” 2018. Thesis, NSYSU. Accessed March 04, 2021. http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0729118-154714.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Wu, Pei-Hsuan. “Architecture Design and Implementation of Deep Neural Network Hardware Accelerators.” 2018. Web. 04 Mar 2021.

Vancouver:

Wu P. Architecture Design and Implementation of Deep Neural Network Hardware Accelerators. [Internet] [Thesis]. NSYSU; 2018. [cited 2021 Mar 04]. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0729118-154714.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Wu P. Architecture Design and Implementation of Deep Neural Network Hardware Accelerators. [Thesis]. NSYSU; 2018. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0729118-154714

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


University of Edinburgh

15. Hu, Qiong. Statistical parametric speech synthesis based on sinusoidal models.

Degree: PhD, 2017, University of Edinburgh

 This study focuses on improving the quality of statistical speech synthesis based on sinusoidal models. Vocoders play a crucial role during the parametrisation and reconstruction… (more)

Subjects/Keywords: 006.5; speech synthesis; sinusoidal models; vocoder; DNN; complex-valued neural network; phase

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Hu, Q. (2017). Statistical parametric speech synthesis based on sinusoidal models. (Doctoral Dissertation). University of Edinburgh. Retrieved from http://hdl.handle.net/1842/28719

Chicago Manual of Style (16th Edition):

Hu, Qiong. “Statistical parametric speech synthesis based on sinusoidal models.” 2017. Doctoral Dissertation, University of Edinburgh. Accessed March 04, 2021. http://hdl.handle.net/1842/28719.

MLA Handbook (7th Edition):

Hu, Qiong. “Statistical parametric speech synthesis based on sinusoidal models.” 2017. Web. 04 Mar 2021.

Vancouver:

Hu Q. Statistical parametric speech synthesis based on sinusoidal models. [Internet] [Doctoral dissertation]. University of Edinburgh; 2017. [cited 2021 Mar 04]. Available from: http://hdl.handle.net/1842/28719.

Council of Science Editors:

Hu Q. Statistical parametric speech synthesis based on sinusoidal models. [Doctoral Dissertation]. University of Edinburgh; 2017. Available from: http://hdl.handle.net/1842/28719


Mid Sweden University

16. Michailoff, John. Email Classification : An evaluation of Deep Neural Networks with Naive Bayes.

Degree: Information Systems and Technology, 2019, Mid Sweden University

  Machine learning (ML) is an area of computer science that gives computers the ability to learn data patterns without prior programming for those patterns.… (more)

Subjects/Keywords: Machine learning; neural network; DNN; Naive Bayes; network complexity; Software Engineering; Programvaruteknik

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APA (6th Edition):

Michailoff, J. (2019). Email Classification : An evaluation of Deep Neural Networks with Naive Bayes. (Thesis). Mid Sweden University. Retrieved from http://urn.kb.se/resolve?urn=urn:nbn:se:miun:diva-37590

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Michailoff, John. “Email Classification : An evaluation of Deep Neural Networks with Naive Bayes.” 2019. Thesis, Mid Sweden University. Accessed March 04, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:miun:diva-37590.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Michailoff, John. “Email Classification : An evaluation of Deep Neural Networks with Naive Bayes.” 2019. Web. 04 Mar 2021.

Vancouver:

Michailoff J. Email Classification : An evaluation of Deep Neural Networks with Naive Bayes. [Internet] [Thesis]. Mid Sweden University; 2019. [cited 2021 Mar 04]. Available from: http://urn.kb.se/resolve?urn=urn:nbn:se:miun:diva-37590.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Michailoff J. Email Classification : An evaluation of Deep Neural Networks with Naive Bayes. [Thesis]. Mid Sweden University; 2019. Available from: http://urn.kb.se/resolve?urn=urn:nbn:se:miun:diva-37590

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


University of Illinois – Urbana-Champaign

17. Lim, Teck Yian. Audio super-resolution with deep neural networks.

Degree: MS, Electrical & Computer Engr, 2018, University of Illinois – Urbana-Champaign

 This thesis reports various attempts at applying generative deep neural networks to audio for the task of recovering a high quality audio signal when given… (more)

Subjects/Keywords: Deep Neural Networks; Audio; Signal Processing; Generative Adversarial Networks; GAN; DNN; Super resolution

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Lim, T. Y. (2018). Audio super-resolution with deep neural networks. (Thesis). University of Illinois – Urbana-Champaign. Retrieved from http://hdl.handle.net/2142/100932

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Lim, Teck Yian. “Audio super-resolution with deep neural networks.” 2018. Thesis, University of Illinois – Urbana-Champaign. Accessed March 04, 2021. http://hdl.handle.net/2142/100932.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Lim, Teck Yian. “Audio super-resolution with deep neural networks.” 2018. Web. 04 Mar 2021.

Vancouver:

Lim TY. Audio super-resolution with deep neural networks. [Internet] [Thesis]. University of Illinois – Urbana-Champaign; 2018. [cited 2021 Mar 04]. Available from: http://hdl.handle.net/2142/100932.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Lim TY. Audio super-resolution with deep neural networks. [Thesis]. University of Illinois – Urbana-Champaign; 2018. Available from: http://hdl.handle.net/2142/100932

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

18. Gandhi, Mardavkumar. Compression of deep neural network to run on resource limited devices.

Degree: MS, Computer Science, 2019, California State University – Sacramento

 Neural Network comprises of fully connected layers and they have 1 or 2 hidden layers. Deep Neural Network has huge number of hidden layers and… (more)

Subjects/Keywords: Pruning; Quantization; DNN; LeNet-5

DNN) over Uncompressed Neural Networks are that the compressed DNN are memory efficient… …energy efficient and that’s why we can deploy the compressed DNN on resource limited devices… …original DNN. It is obvious that fewer the parameters in terms of weights, we need to perform… …In pruning we focus on to eliminate the connections or weights of the DNN and in… …fewer number of weights compared to original DNN, major number of weights will fit into SRAM… 

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Gandhi, M. (2019). Compression of deep neural network to run on resource limited devices. (Masters Thesis). California State University – Sacramento. Retrieved from http://hdl.handle.net/10211.3/213413

Chicago Manual of Style (16th Edition):

Gandhi, Mardavkumar. “Compression of deep neural network to run on resource limited devices.” 2019. Masters Thesis, California State University – Sacramento. Accessed March 04, 2021. http://hdl.handle.net/10211.3/213413.

MLA Handbook (7th Edition):

Gandhi, Mardavkumar. “Compression of deep neural network to run on resource limited devices.” 2019. Web. 04 Mar 2021.

Vancouver:

Gandhi M. Compression of deep neural network to run on resource limited devices. [Internet] [Masters thesis]. California State University – Sacramento; 2019. [cited 2021 Mar 04]. Available from: http://hdl.handle.net/10211.3/213413.

Council of Science Editors:

Gandhi M. Compression of deep neural network to run on resource limited devices. [Masters Thesis]. California State University – Sacramento; 2019. Available from: http://hdl.handle.net/10211.3/213413


Universidad de Chile

19. Novoa Ilic, José Eduardo. Robust speech recognition in noisy and reverberant environments using deep neural network-based systems.

Degree: 2018, Universidad de Chile

 In this thesis an uncertainty weighting scheme for deep neural network-hidden Markov model (DNN-HMM) based automatic speech recognition (ASR) is proposed to increase discriminability in… (more)

Subjects/Keywords: Reconocimiento automático de la voz; Redes neuronales (Ciencia de la computación); DNN-HMM

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APA (6th Edition):

Novoa Ilic, J. E. (2018). Robust speech recognition in noisy and reverberant environments using deep neural network-based systems. (Thesis). Universidad de Chile. Retrieved from http://repositorio.uchile.cl/handle/2250/168062

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Novoa Ilic, José Eduardo. “Robust speech recognition in noisy and reverberant environments using deep neural network-based systems.” 2018. Thesis, Universidad de Chile. Accessed March 04, 2021. http://repositorio.uchile.cl/handle/2250/168062.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Novoa Ilic, José Eduardo. “Robust speech recognition in noisy and reverberant environments using deep neural network-based systems.” 2018. Web. 04 Mar 2021.

Vancouver:

Novoa Ilic JE. Robust speech recognition in noisy and reverberant environments using deep neural network-based systems. [Internet] [Thesis]. Universidad de Chile; 2018. [cited 2021 Mar 04]. Available from: http://repositorio.uchile.cl/handle/2250/168062.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Novoa Ilic JE. Robust speech recognition in noisy and reverberant environments using deep neural network-based systems. [Thesis]. Universidad de Chile; 2018. Available from: http://repositorio.uchile.cl/handle/2250/168062

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


Delft University of Technology

20. Cox, Bart (author). Multi-model inference on the edge: Scheduling for multi-model execution on resource constrained devices.

Degree: 2020, Delft University of Technology

Deep neural networks (DNNs) are becoming the core components of many applications running on edge devices,especially for image-based analysis, e.g., identifying objects, faces, and genders.… (more)

Subjects/Keywords: DNN inference; Mean response time; Edge Devices; Memory Aware Scheduling; Mutli-model

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APA (6th Edition):

Cox, B. (. (2020). Multi-model inference on the edge: Scheduling for multi-model execution on resource constrained devices. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:a87ad458-7f9e-48f7-aed1-9ec258381347

Chicago Manual of Style (16th Edition):

Cox, Bart (author). “Multi-model inference on the edge: Scheduling for multi-model execution on resource constrained devices.” 2020. Masters Thesis, Delft University of Technology. Accessed March 04, 2021. http://resolver.tudelft.nl/uuid:a87ad458-7f9e-48f7-aed1-9ec258381347.

MLA Handbook (7th Edition):

Cox, Bart (author). “Multi-model inference on the edge: Scheduling for multi-model execution on resource constrained devices.” 2020. Web. 04 Mar 2021.

Vancouver:

Cox B(. Multi-model inference on the edge: Scheduling for multi-model execution on resource constrained devices. [Internet] [Masters thesis]. Delft University of Technology; 2020. [cited 2021 Mar 04]. Available from: http://resolver.tudelft.nl/uuid:a87ad458-7f9e-48f7-aed1-9ec258381347.

Council of Science Editors:

Cox B(. Multi-model inference on the edge: Scheduling for multi-model execution on resource constrained devices. [Masters Thesis]. Delft University of Technology; 2020. Available from: http://resolver.tudelft.nl/uuid:a87ad458-7f9e-48f7-aed1-9ec258381347

21. MURPHY, ANDREW. Controlling the voice quality dimension of prosody in synthetic speech using an acoustic glottal model.

Degree: School of Linguistic Speech & Comm Sci. C.L.C.S., 2021, Trinity College Dublin

 Statistical parametric speech synthesis (SPSS) offers a means of generating synthetic speech without the need for complex and extensive rules. One way in which this… (more)

Subjects/Keywords: Speech synthesis; Voice quality; Prosody; Irish; TTS; DNN; Voice source; Acoustic glottal model

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APA (6th Edition):

MURPHY, A. (2021). Controlling the voice quality dimension of prosody in synthetic speech using an acoustic glottal model. (Thesis). Trinity College Dublin. Retrieved from http://hdl.handle.net/2262/94214

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

MURPHY, ANDREW. “Controlling the voice quality dimension of prosody in synthetic speech using an acoustic glottal model.” 2021. Thesis, Trinity College Dublin. Accessed March 04, 2021. http://hdl.handle.net/2262/94214.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

MURPHY, ANDREW. “Controlling the voice quality dimension of prosody in synthetic speech using an acoustic glottal model.” 2021. Web. 04 Mar 2021.

Vancouver:

MURPHY A. Controlling the voice quality dimension of prosody in synthetic speech using an acoustic glottal model. [Internet] [Thesis]. Trinity College Dublin; 2021. [cited 2021 Mar 04]. Available from: http://hdl.handle.net/2262/94214.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

MURPHY A. Controlling the voice quality dimension of prosody in synthetic speech using an acoustic glottal model. [Thesis]. Trinity College Dublin; 2021. Available from: http://hdl.handle.net/2262/94214

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


Rochester Institute of Technology

22. Carmichael, Zachariah JL. Towards Lightweight AI: Leveraging Stochasticity, Quantization, and Tensorization for Forecasting.

Degree: MS, Computer Engineering, 2019, Rochester Institute of Technology

  The deep neural network is an intriguing prognostic model capable of learning meaningful patterns that generalize to new data. The deep learning paradigm has… (more)

Subjects/Keywords: DNN accelerators; Echo state networks; Edge computing; Low-precision arithmetic; Tensor decomposition; Time series forecasting

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APA (6th Edition):

Carmichael, Z. J. (2019). Towards Lightweight AI: Leveraging Stochasticity, Quantization, and Tensorization for Forecasting. (Masters Thesis). Rochester Institute of Technology. Retrieved from https://scholarworks.rit.edu/theses/10144

Chicago Manual of Style (16th Edition):

Carmichael, Zachariah JL. “Towards Lightweight AI: Leveraging Stochasticity, Quantization, and Tensorization for Forecasting.” 2019. Masters Thesis, Rochester Institute of Technology. Accessed March 04, 2021. https://scholarworks.rit.edu/theses/10144.

MLA Handbook (7th Edition):

Carmichael, Zachariah JL. “Towards Lightweight AI: Leveraging Stochasticity, Quantization, and Tensorization for Forecasting.” 2019. Web. 04 Mar 2021.

Vancouver:

Carmichael ZJ. Towards Lightweight AI: Leveraging Stochasticity, Quantization, and Tensorization for Forecasting. [Internet] [Masters thesis]. Rochester Institute of Technology; 2019. [cited 2021 Mar 04]. Available from: https://scholarworks.rit.edu/theses/10144.

Council of Science Editors:

Carmichael ZJ. Towards Lightweight AI: Leveraging Stochasticity, Quantization, and Tensorization for Forecasting. [Masters Thesis]. Rochester Institute of Technology; 2019. Available from: https://scholarworks.rit.edu/theses/10144


Arizona State University

23. Srivastava, Gaurav. Joint Optimization of Quantization and Structured Sparsity for Compressed Deep Neural Networks.

Degree: Computer Engineering, 2018, Arizona State University

Subjects/Keywords: Artificial intelligence; Computer engineering; Computer science; Deep learning; Deep Neural Networks; DNN quantization; DNN structured sparsity; DNN weight memory; Pareto-optimal

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APA (6th Edition):

Srivastava, G. (2018). Joint Optimization of Quantization and Structured Sparsity for Compressed Deep Neural Networks. (Masters Thesis). Arizona State University. Retrieved from http://repository.asu.edu/items/50451

Chicago Manual of Style (16th Edition):

Srivastava, Gaurav. “Joint Optimization of Quantization and Structured Sparsity for Compressed Deep Neural Networks.” 2018. Masters Thesis, Arizona State University. Accessed March 04, 2021. http://repository.asu.edu/items/50451.

MLA Handbook (7th Edition):

Srivastava, Gaurav. “Joint Optimization of Quantization and Structured Sparsity for Compressed Deep Neural Networks.” 2018. Web. 04 Mar 2021.

Vancouver:

Srivastava G. Joint Optimization of Quantization and Structured Sparsity for Compressed Deep Neural Networks. [Internet] [Masters thesis]. Arizona State University; 2018. [cited 2021 Mar 04]. Available from: http://repository.asu.edu/items/50451.

Council of Science Editors:

Srivastava G. Joint Optimization of Quantization and Structured Sparsity for Compressed Deep Neural Networks. [Masters Thesis]. Arizona State University; 2018. Available from: http://repository.asu.edu/items/50451

24. Johansson, Alexander. A COMPARATIVE STUDY OF DEEP-LEARNING APPROACHES FOR ACTIVITY RECOGNITION USING SENSOR DATA IN SMART OFFICE ENVIRONMENTS.

Degree: Faculty of Technology and Society (TS), 2018, Malmö University

Syftet med studien är att jämföra tre deep learning nätverk med varandra för att ta reda på vilket nätverk som kan producera den högsta… (more)

Subjects/Keywords: Deep learning; Human activity recognition; IoT technology; CNN; RNN; LSTM; DNN; Decision tree; Tensorflow; Engineering and Technology; Teknik och teknologier

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APA (6th Edition):

Johansson, A. (2018). A COMPARATIVE STUDY OF DEEP-LEARNING APPROACHES FOR ACTIVITY RECOGNITION USING SENSOR DATA IN SMART OFFICE ENVIRONMENTS. (Thesis). Malmö University. Retrieved from http://urn.kb.se/resolve?urn=urn:nbn:se:mau:diva-20928

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Johansson, Alexander. “A COMPARATIVE STUDY OF DEEP-LEARNING APPROACHES FOR ACTIVITY RECOGNITION USING SENSOR DATA IN SMART OFFICE ENVIRONMENTS.” 2018. Thesis, Malmö University. Accessed March 04, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:mau:diva-20928.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Johansson, Alexander. “A COMPARATIVE STUDY OF DEEP-LEARNING APPROACHES FOR ACTIVITY RECOGNITION USING SENSOR DATA IN SMART OFFICE ENVIRONMENTS.” 2018. Web. 04 Mar 2021.

Vancouver:

Johansson A. A COMPARATIVE STUDY OF DEEP-LEARNING APPROACHES FOR ACTIVITY RECOGNITION USING SENSOR DATA IN SMART OFFICE ENVIRONMENTS. [Internet] [Thesis]. Malmö University; 2018. [cited 2021 Mar 04]. Available from: http://urn.kb.se/resolve?urn=urn:nbn:se:mau:diva-20928.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Johansson A. A COMPARATIVE STUDY OF DEEP-LEARNING APPROACHES FOR ACTIVITY RECOGNITION USING SENSOR DATA IN SMART OFFICE ENVIRONMENTS. [Thesis]. Malmö University; 2018. Available from: http://urn.kb.se/resolve?urn=urn:nbn:se:mau:diva-20928

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


Univerzitet u Beogradu

25. Kocić, Jelena, 1982-, 57181961. Autonomno održanje vozila u kolovoznoj traci analizom informacija sa vizuelnih senzora korišćenjem neuralne mreže.

Degree: Elektrotehnički fakultet, 2020, Univerzitet u Beogradu

Elektrotehnika i računarstvo Uža naučna oblast: Elektronika / Electrical Engineering and Computer Science- Electronics

Cilj disertacije je ostvarivanje autonomnog održanja vozila u kolovoznoj traci analizom… (more)

Subjects/Keywords: autonomous driving; deep neural network (DNN); deep learning; camera; machine learning; robo-vehicle; simulator; autonomous driving system; end-to-end learning

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APA (6th Edition):

Kocić, Jelena, 1982-, 5. (2020). Autonomno održanje vozila u kolovoznoj traci analizom informacija sa vizuelnih senzora korišćenjem neuralne mreže. (Thesis). Univerzitet u Beogradu. Retrieved from https://fedorabg.bg.ac.rs/fedora/get/o:22504/bdef:Content/get

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Kocić, Jelena, 1982-, 57181961. “Autonomno održanje vozila u kolovoznoj traci analizom informacija sa vizuelnih senzora korišćenjem neuralne mreže.” 2020. Thesis, Univerzitet u Beogradu. Accessed March 04, 2021. https://fedorabg.bg.ac.rs/fedora/get/o:22504/bdef:Content/get.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Kocić, Jelena, 1982-, 57181961. “Autonomno održanje vozila u kolovoznoj traci analizom informacija sa vizuelnih senzora korišćenjem neuralne mreže.” 2020. Web. 04 Mar 2021.

Vancouver:

Kocić, Jelena, 1982- 5. Autonomno održanje vozila u kolovoznoj traci analizom informacija sa vizuelnih senzora korišćenjem neuralne mreže. [Internet] [Thesis]. Univerzitet u Beogradu; 2020. [cited 2021 Mar 04]. Available from: https://fedorabg.bg.ac.rs/fedora/get/o:22504/bdef:Content/get.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Kocić, Jelena, 1982- 5. Autonomno održanje vozila u kolovoznoj traci analizom informacija sa vizuelnih senzora korišćenjem neuralne mreže. [Thesis]. Univerzitet u Beogradu; 2020. Available from: https://fedorabg.bg.ac.rs/fedora/get/o:22504/bdef:Content/get

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


Virginia Commonwealth University

26. Azam, Md Ali. Energy Efficient Spintronic Device for Neuromorphic Computation.

Degree: MS, Mechanical and Nuclear Engineering, 2019, Virginia Commonwealth University

  Future computing will require significant development in new computing device paradigms. This is motivated by CMOS devices reaching their technological limits, the need for… (more)

Subjects/Keywords: Neuromorphic Spintronics Nano-magnet Neuron Device DNN; Computer and Systems Architecture; Electrical and Electronics; Electronic Devices and Semiconductor Manufacturing; Nanotechnology Fabrication

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APA (6th Edition):

Azam, M. A. (2019). Energy Efficient Spintronic Device for Neuromorphic Computation. (Thesis). Virginia Commonwealth University. Retrieved from https://doi.org/10.25772/JPZS-K169 ; https://scholarscompass.vcu.edu/etd/6036

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Azam, Md Ali. “Energy Efficient Spintronic Device for Neuromorphic Computation.” 2019. Thesis, Virginia Commonwealth University. Accessed March 04, 2021. https://doi.org/10.25772/JPZS-K169 ; https://scholarscompass.vcu.edu/etd/6036.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Azam, Md Ali. “Energy Efficient Spintronic Device for Neuromorphic Computation.” 2019. Web. 04 Mar 2021.

Vancouver:

Azam MA. Energy Efficient Spintronic Device for Neuromorphic Computation. [Internet] [Thesis]. Virginia Commonwealth University; 2019. [cited 2021 Mar 04]. Available from: https://doi.org/10.25772/JPZS-K169 ; https://scholarscompass.vcu.edu/etd/6036.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Azam MA. Energy Efficient Spintronic Device for Neuromorphic Computation. [Thesis]. Virginia Commonwealth University; 2019. Available from: https://doi.org/10.25772/JPZS-K169 ; https://scholarscompass.vcu.edu/etd/6036

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


University of Kentucky

27. Khanal, Subash. MISPRONUNCIATION DETECTION AND DIAGNOSIS IN MANDARIN ACCENTED ENGLISH SPEECH.

Degree: 2020, University of Kentucky

 This work presents the development, implementation, and evaluation of a Mispronunciation Detection and Diagnosis (MDD) system, with application to pronunciation evaluation of Mandarin-accented English speech.… (more)

Subjects/Keywords: Mispronunciation detection and diagnosis (MDD); Articulatory features; Automatic Speech Recognition; Deep Neural Network (DNN); Signal Processing

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APA (6th Edition):

Khanal, S. (2020). MISPRONUNCIATION DETECTION AND DIAGNOSIS IN MANDARIN ACCENTED ENGLISH SPEECH. (Masters Thesis). University of Kentucky. Retrieved from https://uknowledge.uky.edu/ece_etds/156

Chicago Manual of Style (16th Edition):

Khanal, Subash. “MISPRONUNCIATION DETECTION AND DIAGNOSIS IN MANDARIN ACCENTED ENGLISH SPEECH.” 2020. Masters Thesis, University of Kentucky. Accessed March 04, 2021. https://uknowledge.uky.edu/ece_etds/156.

MLA Handbook (7th Edition):

Khanal, Subash. “MISPRONUNCIATION DETECTION AND DIAGNOSIS IN MANDARIN ACCENTED ENGLISH SPEECH.” 2020. Web. 04 Mar 2021.

Vancouver:

Khanal S. MISPRONUNCIATION DETECTION AND DIAGNOSIS IN MANDARIN ACCENTED ENGLISH SPEECH. [Internet] [Masters thesis]. University of Kentucky; 2020. [cited 2021 Mar 04]. Available from: https://uknowledge.uky.edu/ece_etds/156.

Council of Science Editors:

Khanal S. MISPRONUNCIATION DETECTION AND DIAGNOSIS IN MANDARIN ACCENTED ENGLISH SPEECH. [Masters Thesis]. University of Kentucky; 2020. Available from: https://uknowledge.uky.edu/ece_etds/156

28. Erikson, Pernilla. Variabeltryck med inkjet i dagspress : Möjligheten att införa anpassade upplagor.

Degree: Graphic Arts Technology, 2012, Dalarna University

På uppdrag av Tidningsutgivarna har en studie utförts angående olika möjligheter att införa tryck av variabeldata med tryckmetoden inkjet i svensk dagspress. Målet var… (more)

Subjects/Keywords: variable print; inkjet; newsprint; customized editions; digital newspaper production; Kodak; Prosper; Versamark; Canon Océ; DNN; hybrid printing; printhead; nanography; NIIU; Synapse; variabeltryck; inkjet; dagspress; anpassade upplagor; digital tidningsproduktion; Kodak; Prosper; Versamark; Canon Océ; DNN; hybridtryck; skrivarhuvud; nanography; NIIU; Synapse

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Erikson, P. (2012). Variabeltryck med inkjet i dagspress : Möjligheten att införa anpassade upplagor. (Thesis). Dalarna University. Retrieved from http://urn.kb.se/resolve?urn=urn:nbn:se:du-11153

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Erikson, Pernilla. “Variabeltryck med inkjet i dagspress : Möjligheten att införa anpassade upplagor.” 2012. Thesis, Dalarna University. Accessed March 04, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:du-11153.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Erikson, Pernilla. “Variabeltryck med inkjet i dagspress : Möjligheten att införa anpassade upplagor.” 2012. Web. 04 Mar 2021.

Vancouver:

Erikson P. Variabeltryck med inkjet i dagspress : Möjligheten att införa anpassade upplagor. [Internet] [Thesis]. Dalarna University; 2012. [cited 2021 Mar 04]. Available from: http://urn.kb.se/resolve?urn=urn:nbn:se:du-11153.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Erikson P. Variabeltryck med inkjet i dagspress : Möjligheten att införa anpassade upplagor. [Thesis]. Dalarna University; 2012. Available from: http://urn.kb.se/resolve?urn=urn:nbn:se:du-11153

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

29. DENG XIN. Modeling the chemotaxis behaviors of C. Elegans using neural network: from artificial to biological approach.

Degree: 2013, National University of Singapore

Subjects/Keywords: C. elegans; undulatory locomotion; DNN; chemotaxis; speed regulation; wire diagram

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

XIN, D. (2013). Modeling the chemotaxis behaviors of C. Elegans using neural network: from artificial to biological approach. (Thesis). National University of Singapore. Retrieved from http://scholarbank.nus.edu.sg/handle/10635/43729

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

XIN, DENG. “Modeling the chemotaxis behaviors of C. Elegans using neural network: from artificial to biological approach.” 2013. Thesis, National University of Singapore. Accessed March 04, 2021. http://scholarbank.nus.edu.sg/handle/10635/43729.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

XIN, DENG. “Modeling the chemotaxis behaviors of C. Elegans using neural network: from artificial to biological approach.” 2013. Web. 04 Mar 2021.

Vancouver:

XIN D. Modeling the chemotaxis behaviors of C. Elegans using neural network: from artificial to biological approach. [Internet] [Thesis]. National University of Singapore; 2013. [cited 2021 Mar 04]. Available from: http://scholarbank.nus.edu.sg/handle/10635/43729.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

XIN D. Modeling the chemotaxis behaviors of C. Elegans using neural network: from artificial to biological approach. [Thesis]. National University of Singapore; 2013. Available from: http://scholarbank.nus.edu.sg/handle/10635/43729

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


Universitat Politècnica de Catalunya

30. Riera Villanueva, Marc. Low-power accelerators for cognitive computing.

Degree: Departament d'Arquitectura de Computadors, 2020, Universitat Politècnica de Catalunya

 Les xarxes neuronals profundes (DNN) han aconseguit un èxit enorme en aplicacions cognitives, i són especialment eficients en problemes de classificació i presa de decisions… (more)

Subjects/Keywords: Machine learning; Deep neural network (DNN); Hardware accelerator; Low-power architecture; Computation reuse; Input similarity; Weight repetition; Quantization; Pruning; Àrees temàtiques de la UPC::Informàtica; 004

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Riera Villanueva, M. (2020). Low-power accelerators for cognitive computing. (Thesis). Universitat Politècnica de Catalunya. Retrieved from http://hdl.handle.net/10803/669828

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Riera Villanueva, Marc. “Low-power accelerators for cognitive computing.” 2020. Thesis, Universitat Politècnica de Catalunya. Accessed March 04, 2021. http://hdl.handle.net/10803/669828.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Riera Villanueva, Marc. “Low-power accelerators for cognitive computing.” 2020. Web. 04 Mar 2021.

Vancouver:

Riera Villanueva M. Low-power accelerators for cognitive computing. [Internet] [Thesis]. Universitat Politècnica de Catalunya; 2020. [cited 2021 Mar 04]. Available from: http://hdl.handle.net/10803/669828.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Riera Villanueva M. Low-power accelerators for cognitive computing. [Thesis]. Universitat Politècnica de Catalunya; 2020. Available from: http://hdl.handle.net/10803/669828

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

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