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You searched for subject:(neural networks). Showing records 1 – 30 of 4388 total matches.

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University of Waterloo

1. Khan, Ahmed Faraz. Bidirectional Learning in Recurrent Neural Networks Using Equilibrium Propagation.

Degree: 2018, University of Waterloo

 Neurobiologically-plausible learning algorithms for recurrent neural networks that can perform supervised learning are a neglected area of study. Equilibrium propagation is a recent synthesis of… (more)

Subjects/Keywords: neural networks

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

APA (6th Edition):

Khan, A. F. (2018). Bidirectional Learning in Recurrent Neural Networks Using Equilibrium Propagation. (Thesis). University of Waterloo. Retrieved from http://hdl.handle.net/10012/13957

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):

Khan, Ahmed Faraz. “Bidirectional Learning in Recurrent Neural Networks Using Equilibrium Propagation.” 2018. Thesis, University of Waterloo. Accessed September 16, 2019. http://hdl.handle.net/10012/13957.

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

MLA Handbook (7th Edition):

Khan, Ahmed Faraz. “Bidirectional Learning in Recurrent Neural Networks Using Equilibrium Propagation.” 2018. Web. 16 Sep 2019.

Vancouver:

Khan AF. Bidirectional Learning in Recurrent Neural Networks Using Equilibrium Propagation. [Internet] [Thesis]. University of Waterloo; 2018. [cited 2019 Sep 16]. Available from: http://hdl.handle.net/10012/13957.

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

Council of Science Editors:

Khan AF. Bidirectional Learning in Recurrent Neural Networks Using Equilibrium Propagation. [Thesis]. University of Waterloo; 2018. Available from: http://hdl.handle.net/10012/13957

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


California State Polytechnic University – Pomona

2. Priya, Renita. A Deep Dive Into Automatic Code Generation Using Character Based Recurrent Neural Networks.

Degree: MS, Department of Computer Science, 2018, California State Polytechnic University – Pomona

 Deep Learning is an emerging field in Artificial Intelligence that uses biologically inspired neural networks to recognize patterns in the natural world. These neural networks(more)

Subjects/Keywords: neural networks

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APA (6th Edition):

Priya, R. (2018). A Deep Dive Into Automatic Code Generation Using Character Based Recurrent Neural Networks. (Masters Thesis). California State Polytechnic University – Pomona. Retrieved from http://hdl.handle.net/10211.3/206684

Chicago Manual of Style (16th Edition):

Priya, Renita. “A Deep Dive Into Automatic Code Generation Using Character Based Recurrent Neural Networks.” 2018. Masters Thesis, California State Polytechnic University – Pomona. Accessed September 16, 2019. http://hdl.handle.net/10211.3/206684.

MLA Handbook (7th Edition):

Priya, Renita. “A Deep Dive Into Automatic Code Generation Using Character Based Recurrent Neural Networks.” 2018. Web. 16 Sep 2019.

Vancouver:

Priya R. A Deep Dive Into Automatic Code Generation Using Character Based Recurrent Neural Networks. [Internet] [Masters thesis]. California State Polytechnic University – Pomona; 2018. [cited 2019 Sep 16]. Available from: http://hdl.handle.net/10211.3/206684.

Council of Science Editors:

Priya R. A Deep Dive Into Automatic Code Generation Using Character Based Recurrent Neural Networks. [Masters Thesis]. California State Polytechnic University – Pomona; 2018. Available from: http://hdl.handle.net/10211.3/206684


University of Waterloo

3. Bekolay, Trevor. Learning in large-scale spiking neural networks.

Degree: 2011, University of Waterloo

 Learning is central to the exploration of intelligence. Psychology and machine learning provide high-level explanations of how rational agents learn. Neuroscience provides low-level descriptions of… (more)

Subjects/Keywords: neuroplasticity; learning; neural networks; spiking neural networks

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APA (6th Edition):

Bekolay, T. (2011). Learning in large-scale spiking neural networks. (Thesis). University of Waterloo. Retrieved from http://hdl.handle.net/10012/6195

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):

Bekolay, Trevor. “Learning in large-scale spiking neural networks.” 2011. Thesis, University of Waterloo. Accessed September 16, 2019. http://hdl.handle.net/10012/6195.

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

MLA Handbook (7th Edition):

Bekolay, Trevor. “Learning in large-scale spiking neural networks.” 2011. Web. 16 Sep 2019.

Vancouver:

Bekolay T. Learning in large-scale spiking neural networks. [Internet] [Thesis]. University of Waterloo; 2011. [cited 2019 Sep 16]. Available from: http://hdl.handle.net/10012/6195.

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

Council of Science Editors:

Bekolay T. Learning in large-scale spiking neural networks. [Thesis]. University of Waterloo; 2011. Available from: http://hdl.handle.net/10012/6195

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


University of Johannesburg

4. De Wet, Anton Petrus Christiaan. An incremental learning system for artificial neural networks.

Degree: 2014, University of Johannesburg

M.Ing. (Electrical And Electronic Engineering)

This dissertation describes the development of a system of Artificial Neural Networks that enables the incremental training of feed forward… (more)

Subjects/Keywords: Neural networks (Computer science); Artificial Neural Networks

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APA (6th Edition):

De Wet, A. P. C. (2014). An incremental learning system for artificial neural networks. (Thesis). University of Johannesburg. Retrieved from http://hdl.handle.net/10210/12024

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):

De Wet, Anton Petrus Christiaan. “An incremental learning system for artificial neural networks.” 2014. Thesis, University of Johannesburg. Accessed September 16, 2019. http://hdl.handle.net/10210/12024.

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

MLA Handbook (7th Edition):

De Wet, Anton Petrus Christiaan. “An incremental learning system for artificial neural networks.” 2014. Web. 16 Sep 2019.

Vancouver:

De Wet APC. An incremental learning system for artificial neural networks. [Internet] [Thesis]. University of Johannesburg; 2014. [cited 2019 Sep 16]. Available from: http://hdl.handle.net/10210/12024.

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

Council of Science Editors:

De Wet APC. An incremental learning system for artificial neural networks. [Thesis]. University of Johannesburg; 2014. Available from: http://hdl.handle.net/10210/12024

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


University of Georgia

5. Crowell, Kevin Lee. Precipitation prediction using artificial neural networks.

Degree: MS, Artificial Intelligence, 2008, University of Georgia

 Precipitation, in meteorology, is defined as any product, liquid or solid, of atmospheric water vapor that is accumulated onto the earth’s surface. Water, and thus… (more)

Subjects/Keywords: Artificial Neural Networks

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APA (6th Edition):

Crowell, K. L. (2008). Precipitation prediction using artificial neural networks. (Masters Thesis). University of Georgia. Retrieved from http://purl.galileo.usg.edu/uga_etd/crowell_kevin_l_200812_ms

Chicago Manual of Style (16th Edition):

Crowell, Kevin Lee. “Precipitation prediction using artificial neural networks.” 2008. Masters Thesis, University of Georgia. Accessed September 16, 2019. http://purl.galileo.usg.edu/uga_etd/crowell_kevin_l_200812_ms.

MLA Handbook (7th Edition):

Crowell, Kevin Lee. “Precipitation prediction using artificial neural networks.” 2008. Web. 16 Sep 2019.

Vancouver:

Crowell KL. Precipitation prediction using artificial neural networks. [Internet] [Masters thesis]. University of Georgia; 2008. [cited 2019 Sep 16]. Available from: http://purl.galileo.usg.edu/uga_etd/crowell_kevin_l_200812_ms.

Council of Science Editors:

Crowell KL. Precipitation prediction using artificial neural networks. [Masters Thesis]. University of Georgia; 2008. Available from: http://purl.galileo.usg.edu/uga_etd/crowell_kevin_l_200812_ms


University of Georgia

6. Martin, Charles Maxwell. Crop yield prediction using artificial neural networks and genetic algorithms.

Degree: MS, Artificial Intelligence, 2009, University of Georgia

 Previous research has established that large-scale climatological phenomena influence local weather conditions in various parts of the world. These weather conditions have a direct effect… (more)

Subjects/Keywords: Artificial Neural Networks

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APA (6th Edition):

Martin, C. M. (2009). Crop yield prediction using artificial neural networks and genetic algorithms. (Masters Thesis). University of Georgia. Retrieved from http://purl.galileo.usg.edu/uga_etd/martin_charles_m_200912_ms

Chicago Manual of Style (16th Edition):

Martin, Charles Maxwell. “Crop yield prediction using artificial neural networks and genetic algorithms.” 2009. Masters Thesis, University of Georgia. Accessed September 16, 2019. http://purl.galileo.usg.edu/uga_etd/martin_charles_m_200912_ms.

MLA Handbook (7th Edition):

Martin, Charles Maxwell. “Crop yield prediction using artificial neural networks and genetic algorithms.” 2009. Web. 16 Sep 2019.

Vancouver:

Martin CM. Crop yield prediction using artificial neural networks and genetic algorithms. [Internet] [Masters thesis]. University of Georgia; 2009. [cited 2019 Sep 16]. Available from: http://purl.galileo.usg.edu/uga_etd/martin_charles_m_200912_ms.

Council of Science Editors:

Martin CM. Crop yield prediction using artificial neural networks and genetic algorithms. [Masters Thesis]. University of Georgia; 2009. Available from: http://purl.galileo.usg.edu/uga_etd/martin_charles_m_200912_ms


University of Waterloo

7. Caterini, Anthony. A Novel Mathematical Framework for the Analysis of Neural Networks.

Degree: 2017, University of Waterloo

 Over the past decade, Deep Neural Networks (DNNs) have become very popular models for processing large amounts of data because of their successful application in… (more)

Subjects/Keywords: Neural Networks; Convolutional Neural Networks; Deep Neural Networks; Machine Learning; Recurrent Neural Networks

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APA (6th Edition):

Caterini, A. (2017). A Novel Mathematical Framework for the Analysis of Neural Networks. (Thesis). University of Waterloo. Retrieved from http://hdl.handle.net/10012/12173

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):

Caterini, Anthony. “A Novel Mathematical Framework for the Analysis of Neural Networks.” 2017. Thesis, University of Waterloo. Accessed September 16, 2019. http://hdl.handle.net/10012/12173.

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

MLA Handbook (7th Edition):

Caterini, Anthony. “A Novel Mathematical Framework for the Analysis of Neural Networks.” 2017. Web. 16 Sep 2019.

Vancouver:

Caterini A. A Novel Mathematical Framework for the Analysis of Neural Networks. [Internet] [Thesis]. University of Waterloo; 2017. [cited 2019 Sep 16]. Available from: http://hdl.handle.net/10012/12173.

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

Council of Science Editors:

Caterini A. A Novel Mathematical Framework for the Analysis of Neural Networks. [Thesis]. University of Waterloo; 2017. Available from: http://hdl.handle.net/10012/12173

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


ETH Zürich

8. Neil, Daniel. Deep Neural Networks and Hardware Systems for Event-driven Data.

Degree: 2017, ETH Zürich

 Event-based sensors, built with biological inspiration, differ greatly from traditional sensor types. A standard vision sensor uses a pixel array to produce a frame containing… (more)

Subjects/Keywords: Deep Neural Networks; Event-driven sensors; Deep neural networks (DNNs); Spiking deep neural networks; Recurrent Neural Networks; Convolutional neural networks

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APA (6th Edition):

Neil, D. (2017). Deep Neural Networks and Hardware Systems for Event-driven Data. (Doctoral Dissertation). ETH Zürich. Retrieved from http://hdl.handle.net/20.500.11850/168865

Chicago Manual of Style (16th Edition):

Neil, Daniel. “Deep Neural Networks and Hardware Systems for Event-driven Data.” 2017. Doctoral Dissertation, ETH Zürich. Accessed September 16, 2019. http://hdl.handle.net/20.500.11850/168865.

MLA Handbook (7th Edition):

Neil, Daniel. “Deep Neural Networks and Hardware Systems for Event-driven Data.” 2017. Web. 16 Sep 2019.

Vancouver:

Neil D. Deep Neural Networks and Hardware Systems for Event-driven Data. [Internet] [Doctoral dissertation]. ETH Zürich; 2017. [cited 2019 Sep 16]. Available from: http://hdl.handle.net/20.500.11850/168865.

Council of Science Editors:

Neil D. Deep Neural Networks and Hardware Systems for Event-driven Data. [Doctoral Dissertation]. ETH Zürich; 2017. Available from: http://hdl.handle.net/20.500.11850/168865


California State University – Sacramento

9. Deo, Sudarshan. Deep learning with convolutional neural networks for image recognition: step-by-step process from preparation to generalization.

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

 This project collects several experiments in Deep Learning Convolutional Neural Network for Image predictions. It makes use of Google TensorFlow and TFlearn Deep Learning libraries… (more)

Subjects/Keywords: Neural Networks; Classification; Neural networks; Convolutional neural network

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APA (6th Edition):

Deo, S. (2019). Deep learning with convolutional neural networks for image recognition: step-by-step process from preparation to generalization. (Masters Thesis). California State University – Sacramento. Retrieved from http://hdl.handle.net/10211.3/207763

Chicago Manual of Style (16th Edition):

Deo, Sudarshan. “Deep learning with convolutional neural networks for image recognition: step-by-step process from preparation to generalization.” 2019. Masters Thesis, California State University – Sacramento. Accessed September 16, 2019. http://hdl.handle.net/10211.3/207763.

MLA Handbook (7th Edition):

Deo, Sudarshan. “Deep learning with convolutional neural networks for image recognition: step-by-step process from preparation to generalization.” 2019. Web. 16 Sep 2019.

Vancouver:

Deo S. Deep learning with convolutional neural networks for image recognition: step-by-step process from preparation to generalization. [Internet] [Masters thesis]. California State University – Sacramento; 2019. [cited 2019 Sep 16]. Available from: http://hdl.handle.net/10211.3/207763.

Council of Science Editors:

Deo S. Deep learning with convolutional neural networks for image recognition: step-by-step process from preparation to generalization. [Masters Thesis]. California State University – Sacramento; 2019. Available from: http://hdl.handle.net/10211.3/207763


University of Victoria

10. Edwards, Roderick. Neural networks and neural fields: discrete and continuous space neural models.

Degree: Department of Mathematics and Statistics, 2018, University of Victoria

 'Attractor' neural network models have useful properties, but biology suggests that more varied dynamics may be significant. Even the equations of the Hopfield network, without… (more)

Subjects/Keywords: Neural circuitry; Neural networks (Computer science)

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APA (6th Edition):

Edwards, R. (2018). Neural networks and neural fields: discrete and continuous space neural models. (Thesis). University of Victoria. Retrieved from https://dspace.library.uvic.ca//handle/1828/9682

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):

Edwards, Roderick. “Neural networks and neural fields: discrete and continuous space neural models.” 2018. Thesis, University of Victoria. Accessed September 16, 2019. https://dspace.library.uvic.ca//handle/1828/9682.

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

MLA Handbook (7th Edition):

Edwards, Roderick. “Neural networks and neural fields: discrete and continuous space neural models.” 2018. Web. 16 Sep 2019.

Vancouver:

Edwards R. Neural networks and neural fields: discrete and continuous space neural models. [Internet] [Thesis]. University of Victoria; 2018. [cited 2019 Sep 16]. Available from: https://dspace.library.uvic.ca//handle/1828/9682.

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

Council of Science Editors:

Edwards R. Neural networks and neural fields: discrete and continuous space neural models. [Thesis]. University of Victoria; 2018. Available from: https://dspace.library.uvic.ca//handle/1828/9682

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


Bucknell University

11. Mukhopadhyay, Himadri. The Resonate-and-fire Neuron: Time Dependent and Frequency Selective Neurons in Neural Networks.

Degree: 2010, Bucknell University

 The means through which the nervous system perceives its environment is one of the most fascinating questions in contemporary science. Our endeavors to comprehend the… (more)

Subjects/Keywords: Neural Signals; Neural Networks; Temporal Backpropagation

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APA (6th Edition):

Mukhopadhyay, H. (2010). The Resonate-and-fire Neuron: Time Dependent and Frequency Selective Neurons in Neural Networks. (Thesis). Bucknell University. Retrieved from https://digitalcommons.bucknell.edu/masters_theses/23

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):

Mukhopadhyay, Himadri. “The Resonate-and-fire Neuron: Time Dependent and Frequency Selective Neurons in Neural Networks.” 2010. Thesis, Bucknell University. Accessed September 16, 2019. https://digitalcommons.bucknell.edu/masters_theses/23.

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

MLA Handbook (7th Edition):

Mukhopadhyay, Himadri. “The Resonate-and-fire Neuron: Time Dependent and Frequency Selective Neurons in Neural Networks.” 2010. Web. 16 Sep 2019.

Vancouver:

Mukhopadhyay H. The Resonate-and-fire Neuron: Time Dependent and Frequency Selective Neurons in Neural Networks. [Internet] [Thesis]. Bucknell University; 2010. [cited 2019 Sep 16]. Available from: https://digitalcommons.bucknell.edu/masters_theses/23.

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

Council of Science Editors:

Mukhopadhyay H. The Resonate-and-fire Neuron: Time Dependent and Frequency Selective Neurons in Neural Networks. [Thesis]. Bucknell University; 2010. Available from: https://digitalcommons.bucknell.edu/masters_theses/23

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


NSYSU

12. Wang, Hao-Yi. The Impacts of Image Contexts on Dialogue Systems.

Degree: Master, Information Management, 2018, NSYSU

 Chatting with machines is not only possible but also more and more common in our lives these days. With the approach, we can execute commands… (more)

Subjects/Keywords: , Dialogue; Convolutional neural networks; Recurrent neural networks; Image recognition; Natural language; Neural networks; Machine learning

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APA (6th Edition):

Wang, H. (2018). The Impacts of Image Contexts on Dialogue Systems. (Thesis). NSYSU. Retrieved from http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0616118-181354

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):

Wang, Hao-Yi. “The Impacts of Image Contexts on Dialogue Systems.” 2018. Thesis, NSYSU. Accessed September 16, 2019. http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0616118-181354.

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

MLA Handbook (7th Edition):

Wang, Hao-Yi. “The Impacts of Image Contexts on Dialogue Systems.” 2018. Web. 16 Sep 2019.

Vancouver:

Wang H. The Impacts of Image Contexts on Dialogue Systems. [Internet] [Thesis]. NSYSU; 2018. [cited 2019 Sep 16]. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0616118-181354.

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

Council of Science Editors:

Wang H. The Impacts of Image Contexts on Dialogue Systems. [Thesis]. NSYSU; 2018. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0616118-181354

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


University of Ottawa

13. Ayoub, Issa. Multimodal Affective Computing Using Temporal Convolutional Neural Network and Deep Convolutional Neural Networks .

Degree: 2019, University of Ottawa

 Affective computing has gained significant attention from researchers in the last decade due to the wide variety of applications that can benefit from this technology.… (more)

Subjects/Keywords: Temporal Convolutional Neural Networks; Recurrent Neural Networks; Gaussian Processes; Hyperparameter Optimization; Convolutional Neural Networks

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APA (6th Edition):

Ayoub, I. (2019). Multimodal Affective Computing Using Temporal Convolutional Neural Network and Deep Convolutional Neural Networks . (Thesis). University of Ottawa. Retrieved from http://hdl.handle.net/10393/39337

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):

Ayoub, Issa. “Multimodal Affective Computing Using Temporal Convolutional Neural Network and Deep Convolutional Neural Networks .” 2019. Thesis, University of Ottawa. Accessed September 16, 2019. http://hdl.handle.net/10393/39337.

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

MLA Handbook (7th Edition):

Ayoub, Issa. “Multimodal Affective Computing Using Temporal Convolutional Neural Network and Deep Convolutional Neural Networks .” 2019. Web. 16 Sep 2019.

Vancouver:

Ayoub I. Multimodal Affective Computing Using Temporal Convolutional Neural Network and Deep Convolutional Neural Networks . [Internet] [Thesis]. University of Ottawa; 2019. [cited 2019 Sep 16]. Available from: http://hdl.handle.net/10393/39337.

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

Council of Science Editors:

Ayoub I. Multimodal Affective Computing Using Temporal Convolutional Neural Network and Deep Convolutional Neural Networks . [Thesis]. University of Ottawa; 2019. Available from: http://hdl.handle.net/10393/39337

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

14. Joseph, Tony. Joint spatial and layer attention for convolutional networks.

Degree: 2019, University of Ontario Institute of Technology

 In this work, we propose a novel approach that learns to sequentially attend to different Convolutional Neural Networks (CNN) layers (i.e., ???what??? feature abstraction to… (more)

Subjects/Keywords: Computational Attention; Convolutional Neural Networks; Reccurent Neural Networks; Neural Networks; Image-Based Camera Localization

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APA (6th Edition):

Joseph, T. (2019). Joint spatial and layer attention for convolutional networks. (Thesis). University of Ontario Institute of Technology. Retrieved from http://hdl.handle.net/10155/1061

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):

Joseph, Tony. “Joint spatial and layer attention for convolutional networks.” 2019. Thesis, University of Ontario Institute of Technology. Accessed September 16, 2019. http://hdl.handle.net/10155/1061.

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

MLA Handbook (7th Edition):

Joseph, Tony. “Joint spatial and layer attention for convolutional networks.” 2019. Web. 16 Sep 2019.

Vancouver:

Joseph T. Joint spatial and layer attention for convolutional networks. [Internet] [Thesis]. University of Ontario Institute of Technology; 2019. [cited 2019 Sep 16]. Available from: http://hdl.handle.net/10155/1061.

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

Council of Science Editors:

Joseph T. Joint spatial and layer attention for convolutional networks. [Thesis]. University of Ontario Institute of Technology; 2019. Available from: http://hdl.handle.net/10155/1061

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


University of Georgia

15. Ramyaa, Ramyaa. Frost prediction using Artificial Neural Networks: a classification approach.

Degree: MS, Artificial Intelligence, 2004, University of Georgia

 Air temperatures below freezing can damage plants. Irrigation is the most widely practiced frost protection measure. However, growers need information about when to start irrigating,… (more)

Subjects/Keywords: Neural Networks

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APA (6th Edition):

Ramyaa, R. (2004). Frost prediction using Artificial Neural Networks: a classification approach. (Masters Thesis). University of Georgia. Retrieved from http://purl.galileo.usg.edu/uga_etd/ramyaa_ramyaa_200408_ms2

Chicago Manual of Style (16th Edition):

Ramyaa, Ramyaa. “Frost prediction using Artificial Neural Networks: a classification approach.” 2004. Masters Thesis, University of Georgia. Accessed September 16, 2019. http://purl.galileo.usg.edu/uga_etd/ramyaa_ramyaa_200408_ms2.

MLA Handbook (7th Edition):

Ramyaa, Ramyaa. “Frost prediction using Artificial Neural Networks: a classification approach.” 2004. Web. 16 Sep 2019.

Vancouver:

Ramyaa R. Frost prediction using Artificial Neural Networks: a classification approach. [Internet] [Masters thesis]. University of Georgia; 2004. [cited 2019 Sep 16]. Available from: http://purl.galileo.usg.edu/uga_etd/ramyaa_ramyaa_200408_ms2.

Council of Science Editors:

Ramyaa R. Frost prediction using Artificial Neural Networks: a classification approach. [Masters Thesis]. University of Georgia; 2004. Available from: http://purl.galileo.usg.edu/uga_etd/ramyaa_ramyaa_200408_ms2


Anna University

16. Ashok V. Certain investigations on noninvasive optical blood glucose concentration prediction system using modified haar wavelet transform and neural networks;.

Degree: noninvasive optical blood glucose concentration prediction system using modified haar wavelet transform and neural networks, 2014, Anna University

Diabetes Mellitus is the most well known Constitutional disorder of newlineCarbohydrates Metabolism characterized by inadequate Secretion or newlineutilization of insulin This disorder condition reduces the… (more)

Subjects/Keywords: neural networks; noninvasive; optical blood

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APA (6th Edition):

V, A. (2014). Certain investigations on noninvasive optical blood glucose concentration prediction system using modified haar wavelet transform and neural networks;. (Thesis). Anna University. Retrieved from http://shodhganga.inflibnet.ac.in/handle/10603/22940

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):

V, Ashok. “Certain investigations on noninvasive optical blood glucose concentration prediction system using modified haar wavelet transform and neural networks;.” 2014. Thesis, Anna University. Accessed September 16, 2019. http://shodhganga.inflibnet.ac.in/handle/10603/22940.

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

MLA Handbook (7th Edition):

V, Ashok. “Certain investigations on noninvasive optical blood glucose concentration prediction system using modified haar wavelet transform and neural networks;.” 2014. Web. 16 Sep 2019.

Vancouver:

V A. Certain investigations on noninvasive optical blood glucose concentration prediction system using modified haar wavelet transform and neural networks;. [Internet] [Thesis]. Anna University; 2014. [cited 2019 Sep 16]. Available from: http://shodhganga.inflibnet.ac.in/handle/10603/22940.

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

Council of Science Editors:

V A. Certain investigations on noninvasive optical blood glucose concentration prediction system using modified haar wavelet transform and neural networks;. [Thesis]. Anna University; 2014. Available from: http://shodhganga.inflibnet.ac.in/handle/10603/22940

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

17. Vieira, Lucimar Sasso. Conversão de voz baseada na transformada wavelet.

Degree: Mestrado, Física Aplicada, 2007, University of São Paulo

Dentre as inúmeras técnicas de conversão de voz utilizadas atualmente, aquelas baseadas em bancos de filtros wavelet, associadas com redes neurais artificiais,têm se destacado. Este… (more)

Subjects/Keywords: Neural networks; Voice conversion; Wavelets

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APA (6th Edition):

Vieira, L. S. (2007). Conversão de voz baseada na transformada wavelet. (Masters Thesis). University of São Paulo. Retrieved from http://www.teses.usp.br/teses/disponiveis/76/76132/tde-05092007-192622/ ;

Chicago Manual of Style (16th Edition):

Vieira, Lucimar Sasso. “Conversão de voz baseada na transformada wavelet.” 2007. Masters Thesis, University of São Paulo. Accessed September 16, 2019. http://www.teses.usp.br/teses/disponiveis/76/76132/tde-05092007-192622/ ;.

MLA Handbook (7th Edition):

Vieira, Lucimar Sasso. “Conversão de voz baseada na transformada wavelet.” 2007. Web. 16 Sep 2019.

Vancouver:

Vieira LS. Conversão de voz baseada na transformada wavelet. [Internet] [Masters thesis]. University of São Paulo; 2007. [cited 2019 Sep 16]. Available from: http://www.teses.usp.br/teses/disponiveis/76/76132/tde-05092007-192622/ ;.

Council of Science Editors:

Vieira LS. Conversão de voz baseada na transformada wavelet. [Masters Thesis]. University of São Paulo; 2007. Available from: http://www.teses.usp.br/teses/disponiveis/76/76132/tde-05092007-192622/ ;


Texas A&M University

18. Story, Brett. Structural Impairment Detection Using Arrays of Competitive Artificial Neural Networks.

Degree: 2012, Texas A&M University

 Aging railroad bridge infrastructure is subject to increasingly higher demands such as heavier loads, increased speed, and increased frequency of traffic. The challenges facing railroad… (more)

Subjects/Keywords: Neural Networks; Bridge Engineering

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APA (6th Edition):

Story, B. (2012). Structural Impairment Detection Using Arrays of Competitive Artificial Neural Networks. (Thesis). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/ETD-TAMU-2012-05-11088

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):

Story, Brett. “Structural Impairment Detection Using Arrays of Competitive Artificial Neural Networks.” 2012. Thesis, Texas A&M University. Accessed September 16, 2019. http://hdl.handle.net/1969.1/ETD-TAMU-2012-05-11088.

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

MLA Handbook (7th Edition):

Story, Brett. “Structural Impairment Detection Using Arrays of Competitive Artificial Neural Networks.” 2012. Web. 16 Sep 2019.

Vancouver:

Story B. Structural Impairment Detection Using Arrays of Competitive Artificial Neural Networks. [Internet] [Thesis]. Texas A&M University; 2012. [cited 2019 Sep 16]. Available from: http://hdl.handle.net/1969.1/ETD-TAMU-2012-05-11088.

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

Council of Science Editors:

Story B. Structural Impairment Detection Using Arrays of Competitive Artificial Neural Networks. [Thesis]. Texas A&M University; 2012. Available from: http://hdl.handle.net/1969.1/ETD-TAMU-2012-05-11088

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


Texas A&M University

19. Annan, Carl Ashie. Neural Network-Based Noise Suppressor and Predictor for Quantifying Valve Stiction in Oscillatory Control Loops.

Degree: 2014, Texas A&M University

 Valve stiction-induced oscillations in chemical processing systems adversely affects control loop performance and can degrade the quality of products. Estimating the degree of stiction in… (more)

Subjects/Keywords: Neural Networks; Stiction; NLPCA

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APA (6th Edition):

Annan, C. A. (2014). Neural Network-Based Noise Suppressor and Predictor for Quantifying Valve Stiction in Oscillatory Control Loops. (Thesis). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/154110

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):

Annan, Carl Ashie. “Neural Network-Based Noise Suppressor and Predictor for Quantifying Valve Stiction in Oscillatory Control Loops.” 2014. Thesis, Texas A&M University. Accessed September 16, 2019. http://hdl.handle.net/1969.1/154110.

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

MLA Handbook (7th Edition):

Annan, Carl Ashie. “Neural Network-Based Noise Suppressor and Predictor for Quantifying Valve Stiction in Oscillatory Control Loops.” 2014. Web. 16 Sep 2019.

Vancouver:

Annan CA. Neural Network-Based Noise Suppressor and Predictor for Quantifying Valve Stiction in Oscillatory Control Loops. [Internet] [Thesis]. Texas A&M University; 2014. [cited 2019 Sep 16]. Available from: http://hdl.handle.net/1969.1/154110.

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

Council of Science Editors:

Annan CA. Neural Network-Based Noise Suppressor and Predictor for Quantifying Valve Stiction in Oscillatory Control Loops. [Thesis]. Texas A&M University; 2014. Available from: http://hdl.handle.net/1969.1/154110

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

20. Samidurai, R. Studies and stability of non linear impulsive neural networks; -.

Degree: Mathematics, 2010, Periyar University

Abstract available in image PDF

References p.116-130

Advisors/Committee Members: Marshal, Anthoni S.

Subjects/Keywords: Neural Networks

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APA (6th Edition):

Samidurai, R. (2010). Studies and stability of non linear impulsive neural networks; -. (Thesis). Periyar University. Retrieved from http://shodhganga.inflibnet.ac.in/handle/10603/5208

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):

Samidurai, R. “Studies and stability of non linear impulsive neural networks; -.” 2010. Thesis, Periyar University. Accessed September 16, 2019. http://shodhganga.inflibnet.ac.in/handle/10603/5208.

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

MLA Handbook (7th Edition):

Samidurai, R. “Studies and stability of non linear impulsive neural networks; -.” 2010. Web. 16 Sep 2019.

Vancouver:

Samidurai R. Studies and stability of non linear impulsive neural networks; -. [Internet] [Thesis]. Periyar University; 2010. [cited 2019 Sep 16]. Available from: http://shodhganga.inflibnet.ac.in/handle/10603/5208.

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

Council of Science Editors:

Samidurai R. Studies and stability of non linear impulsive neural networks; -. [Thesis]. Periyar University; 2010. Available from: http://shodhganga.inflibnet.ac.in/handle/10603/5208

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

21. Sujatha P. Image steganalysis using artificial neural networks.

Degree: Computing Sciences, 2013, Vels University

This research work presents the steganalysis of steganographic images under predefined way of hiding information. Hiding information in the cover image is done by different… (more)

Subjects/Keywords: Computing Sciences; Artificial Neural Networks

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APA (6th Edition):

P, S. (2013). Image steganalysis using artificial neural networks. (Thesis). Vels University. Retrieved from http://shodhganga.inflibnet.ac.in/handle/10603/8912

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):

P, Sujatha. “Image steganalysis using artificial neural networks.” 2013. Thesis, Vels University. Accessed September 16, 2019. http://shodhganga.inflibnet.ac.in/handle/10603/8912.

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

MLA Handbook (7th Edition):

P, Sujatha. “Image steganalysis using artificial neural networks.” 2013. Web. 16 Sep 2019.

Vancouver:

P S. Image steganalysis using artificial neural networks. [Internet] [Thesis]. Vels University; 2013. [cited 2019 Sep 16]. Available from: http://shodhganga.inflibnet.ac.in/handle/10603/8912.

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

Council of Science Editors:

P S. Image steganalysis using artificial neural networks. [Thesis]. Vels University; 2013. Available from: http://shodhganga.inflibnet.ac.in/handle/10603/8912

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


Nelson Mandela Metropolitan University

22. Pretorius, Christiaan Johannes. Artificial neural networks as simulators for behavioural evolution in evolutionary robotics.

Degree: MSc, Faculty of Science, 2010, Nelson Mandela Metropolitan University

 Robotic simulators for use in Evolutionary Robotics (ER) have certain challenges associated with the complexity of their construction and the accuracy of predictions made by… (more)

Subjects/Keywords: Neural networks (Computer science); Robotics

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APA (6th Edition):

Pretorius, C. J. (2010). Artificial neural networks as simulators for behavioural evolution in evolutionary robotics. (Masters Thesis). Nelson Mandela Metropolitan University. Retrieved from http://hdl.handle.net/10948/1476

Chicago Manual of Style (16th Edition):

Pretorius, Christiaan Johannes. “Artificial neural networks as simulators for behavioural evolution in evolutionary robotics.” 2010. Masters Thesis, Nelson Mandela Metropolitan University. Accessed September 16, 2019. http://hdl.handle.net/10948/1476.

MLA Handbook (7th Edition):

Pretorius, Christiaan Johannes. “Artificial neural networks as simulators for behavioural evolution in evolutionary robotics.” 2010. Web. 16 Sep 2019.

Vancouver:

Pretorius CJ. Artificial neural networks as simulators for behavioural evolution in evolutionary robotics. [Internet] [Masters thesis]. Nelson Mandela Metropolitan University; 2010. [cited 2019 Sep 16]. Available from: http://hdl.handle.net/10948/1476.

Council of Science Editors:

Pretorius CJ. Artificial neural networks as simulators for behavioural evolution in evolutionary robotics. [Masters Thesis]. Nelson Mandela Metropolitan University; 2010. Available from: http://hdl.handle.net/10948/1476


University of Aberdeen

23. Goetz, Thomas. From synapse to behaviour : selective modulation of neuronal networks.

Degree: 2008, University of Aberdeen

In this thesis, I describe the development of a novel method to selectively modulate neural activity cell-type selectively. Binding of Zolpidem, an allosteric modulator that enhances GABAa receptor function and the inverse agonist β-carboline, require a phenylalanine residue (F77) in the γ subunit.

Subjects/Keywords: 612.81; Neural networks (Neurobiology); GABA

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APA (6th Edition):

Goetz, T. (2008). From synapse to behaviour : selective modulation of neuronal networks. (Doctoral Dissertation). University of Aberdeen. Retrieved from http://digitool.abdn.ac.uk:80/webclient/DeliveryManager?pid=24802 ; http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.493492

Chicago Manual of Style (16th Edition):

Goetz, Thomas. “From synapse to behaviour : selective modulation of neuronal networks.” 2008. Doctoral Dissertation, University of Aberdeen. Accessed September 16, 2019. http://digitool.abdn.ac.uk:80/webclient/DeliveryManager?pid=24802 ; http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.493492.

MLA Handbook (7th Edition):

Goetz, Thomas. “From synapse to behaviour : selective modulation of neuronal networks.” 2008. Web. 16 Sep 2019.

Vancouver:

Goetz T. From synapse to behaviour : selective modulation of neuronal networks. [Internet] [Doctoral dissertation]. University of Aberdeen; 2008. [cited 2019 Sep 16]. Available from: http://digitool.abdn.ac.uk:80/webclient/DeliveryManager?pid=24802 ; http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.493492.

Council of Science Editors:

Goetz T. From synapse to behaviour : selective modulation of neuronal networks. [Doctoral Dissertation]. University of Aberdeen; 2008. Available from: http://digitool.abdn.ac.uk:80/webclient/DeliveryManager?pid=24802 ; http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.493492


Vilnius University

24. Vasiliauskaitė, Vilma. Spiečiaus intelekto taikymo finansų rinkose analizė ir optimizavimas.

Degree: Master, 2014, Vilnius University

Prekiaujant vertybiniais popieriais, svarbiausia yra priimti teisingą sprendimą: pirkti arba parduoti. Daugelis investuotojų prieš priimdami sprendimą atkreipia dėmesį į pasirinktos akcijos kainos kitimo grafiką ir… (more)

Subjects/Keywords: Swarm Intelligent; Neural networks

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APA (6th Edition):

Vasiliauskaitė, V. (2014). Spiečiaus intelekto taikymo finansų rinkose analizė ir optimizavimas. (Masters Thesis). Vilnius University. Retrieved from http://vddb.laba.lt/obj/LT-eLABa-0001:E.02~2008~D_20140623_183138-57850 ;

Chicago Manual of Style (16th Edition):

Vasiliauskaitė, Vilma. “Spiečiaus intelekto taikymo finansų rinkose analizė ir optimizavimas.” 2014. Masters Thesis, Vilnius University. Accessed September 16, 2019. http://vddb.laba.lt/obj/LT-eLABa-0001:E.02~2008~D_20140623_183138-57850 ;.

MLA Handbook (7th Edition):

Vasiliauskaitė, Vilma. “Spiečiaus intelekto taikymo finansų rinkose analizė ir optimizavimas.” 2014. Web. 16 Sep 2019.

Vancouver:

Vasiliauskaitė V. Spiečiaus intelekto taikymo finansų rinkose analizė ir optimizavimas. [Internet] [Masters thesis]. Vilnius University; 2014. [cited 2019 Sep 16]. Available from: http://vddb.laba.lt/obj/LT-eLABa-0001:E.02~2008~D_20140623_183138-57850 ;.

Council of Science Editors:

Vasiliauskaitė V. Spiečiaus intelekto taikymo finansų rinkose analizė ir optimizavimas. [Masters Thesis]. Vilnius University; 2014. Available from: http://vddb.laba.lt/obj/LT-eLABa-0001:E.02~2008~D_20140623_183138-57850 ;


California State University – Sacramento

25. Sirinonrang, Sukanya. On-line measurements using neural networks and soft computing for the control of glass production furnace.

Degree: MS, Mechanical Engineering, 2010, California State University – Sacramento

 Liquefied petroleum (LP) gas is used as a backup energy system for glass production furnace. LP gas is mixed with air at a desired ratio… (more)

Subjects/Keywords: ANFIS; Glass production; Neural networks

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APA (6th Edition):

Sirinonrang, S. (2010). On-line measurements using neural networks and soft computing for the control of glass production furnace. (Masters Thesis). California State University – Sacramento. Retrieved from http://hdl.handle.net/10211.9/834

Chicago Manual of Style (16th Edition):

Sirinonrang, Sukanya. “On-line measurements using neural networks and soft computing for the control of glass production furnace.” 2010. Masters Thesis, California State University – Sacramento. Accessed September 16, 2019. http://hdl.handle.net/10211.9/834.

MLA Handbook (7th Edition):

Sirinonrang, Sukanya. “On-line measurements using neural networks and soft computing for the control of glass production furnace.” 2010. Web. 16 Sep 2019.

Vancouver:

Sirinonrang S. On-line measurements using neural networks and soft computing for the control of glass production furnace. [Internet] [Masters thesis]. California State University – Sacramento; 2010. [cited 2019 Sep 16]. Available from: http://hdl.handle.net/10211.9/834.

Council of Science Editors:

Sirinonrang S. On-line measurements using neural networks and soft computing for the control of glass production furnace. [Masters Thesis]. California State University – Sacramento; 2010. Available from: http://hdl.handle.net/10211.9/834


Oregon State University

26. Moore, Christopher (Chistopher Emory). A recurrent neural network implementation using the graphics processing unit.

Degree: MS, Computer Science, 2009, Oregon State University

 We took the back-propagation algorithms of Werbos for recurrent and feed-forward neural networks and implemented them on machines with graphics processing units (GPU). The parallelism… (more)

Subjects/Keywords: rnn; Neural networks (Computer science)

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APA (6th Edition):

Moore, C. (. E. (2009). A recurrent neural network implementation using the graphics processing unit. (Masters Thesis). Oregon State University. Retrieved from http://hdl.handle.net/1957/13658

Chicago Manual of Style (16th Edition):

Moore, Christopher (Chistopher Emory). “A recurrent neural network implementation using the graphics processing unit.” 2009. Masters Thesis, Oregon State University. Accessed September 16, 2019. http://hdl.handle.net/1957/13658.

MLA Handbook (7th Edition):

Moore, Christopher (Chistopher Emory). “A recurrent neural network implementation using the graphics processing unit.” 2009. Web. 16 Sep 2019.

Vancouver:

Moore C(E. A recurrent neural network implementation using the graphics processing unit. [Internet] [Masters thesis]. Oregon State University; 2009. [cited 2019 Sep 16]. Available from: http://hdl.handle.net/1957/13658.

Council of Science Editors:

Moore C(E. A recurrent neural network implementation using the graphics processing unit. [Masters Thesis]. Oregon State University; 2009. Available from: http://hdl.handle.net/1957/13658

27. Triastuti Sugiyarto, Endang. Analysing rounding data using radial basis function neural networks model.

Degree: PhD, 2007, University of Northampton

 Unspecified counting practices used in a data collection may create rounding to certain ‘based’ number that can have serious consequences on data quality. Statistical methods… (more)

Subjects/Keywords: 600; QA76.87 Neural networks

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APA (6th Edition):

Triastuti Sugiyarto, E. (2007). Analysing rounding data using radial basis function neural networks model. (Doctoral Dissertation). University of Northampton. Retrieved from http://nectar.northampton.ac.uk/2809/ ; http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.545825

Chicago Manual of Style (16th Edition):

Triastuti Sugiyarto, Endang. “Analysing rounding data using radial basis function neural networks model.” 2007. Doctoral Dissertation, University of Northampton. Accessed September 16, 2019. http://nectar.northampton.ac.uk/2809/ ; http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.545825.

MLA Handbook (7th Edition):

Triastuti Sugiyarto, Endang. “Analysing rounding data using radial basis function neural networks model.” 2007. Web. 16 Sep 2019.

Vancouver:

Triastuti Sugiyarto E. Analysing rounding data using radial basis function neural networks model. [Internet] [Doctoral dissertation]. University of Northampton; 2007. [cited 2019 Sep 16]. Available from: http://nectar.northampton.ac.uk/2809/ ; http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.545825.

Council of Science Editors:

Triastuti Sugiyarto E. Analysing rounding data using radial basis function neural networks model. [Doctoral Dissertation]. University of Northampton; 2007. Available from: http://nectar.northampton.ac.uk/2809/ ; http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.545825

28. Σταθοπούλου, Δήμητρα. Σύγκριση μεθόδων εκπαίδευσης τεχνητών νευρωνικών δικτύων.

Degree: 2010, University of Patras

Η παρούσα διπλωματική εργασία αποσκοπεί στη μελέτη και την εκπαίδευση των Τεχνητών Νευρωνικών Δικτύων με τη βοήθεια γνωστών μεθόδων, όπως τη μέθοδο όπισθεν διάδοσης σφάλματος… (more)

Subjects/Keywords: Νευρωνικά δίκτυα; 006.32; Neural networks

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APA (6th Edition):

Σταθοπούλου, . (2010). Σύγκριση μεθόδων εκπαίδευσης τεχνητών νευρωνικών δικτύων. (Masters Thesis). University of Patras. Retrieved from http://nemertes.lis.upatras.gr/jspui/handle/10889/4419

Chicago Manual of Style (16th Edition):

Σταθοπούλου, Δήμητρα. “Σύγκριση μεθόδων εκπαίδευσης τεχνητών νευρωνικών δικτύων.” 2010. Masters Thesis, University of Patras. Accessed September 16, 2019. http://nemertes.lis.upatras.gr/jspui/handle/10889/4419.

MLA Handbook (7th Edition):

Σταθοπούλου, Δήμητρα. “Σύγκριση μεθόδων εκπαίδευσης τεχνητών νευρωνικών δικτύων.” 2010. Web. 16 Sep 2019.

Vancouver:

Σταθοπούλου . Σύγκριση μεθόδων εκπαίδευσης τεχνητών νευρωνικών δικτύων. [Internet] [Masters thesis]. University of Patras; 2010. [cited 2019 Sep 16]. Available from: http://nemertes.lis.upatras.gr/jspui/handle/10889/4419.

Council of Science Editors:

Σταθοπούλου . Σύγκριση μεθόδων εκπαίδευσης τεχνητών νευρωνικών δικτύων. [Masters Thesis]. University of Patras; 2010. Available from: http://nemertes.lis.upatras.gr/jspui/handle/10889/4419


Indiana University of Pennsylvania

29. Gresavage, Thomas. A Neural Networks Approach to Determining Angle and Scale of Partially Occluded Objects.

Degree: MS, Mathematics, 2016, Indiana University of Pennsylvania

  A team of biological researchers wishes to investigate the eating behaviors of local insects to determine whether they prefer indigenous or invasive plant species.… (more)

Subjects/Keywords: computer vision; neural networks; python

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APA (6th Edition):

Gresavage, T. (2016). A Neural Networks Approach to Determining Angle and Scale of Partially Occluded Objects. (Thesis). Indiana University of Pennsylvania. Retrieved from https://knowledge.library.iup.edu/etd/1408

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):

Gresavage, Thomas. “A Neural Networks Approach to Determining Angle and Scale of Partially Occluded Objects.” 2016. Thesis, Indiana University of Pennsylvania. Accessed September 16, 2019. https://knowledge.library.iup.edu/etd/1408.

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

MLA Handbook (7th Edition):

Gresavage, Thomas. “A Neural Networks Approach to Determining Angle and Scale of Partially Occluded Objects.” 2016. Web. 16 Sep 2019.

Vancouver:

Gresavage T. A Neural Networks Approach to Determining Angle and Scale of Partially Occluded Objects. [Internet] [Thesis]. Indiana University of Pennsylvania; 2016. [cited 2019 Sep 16]. Available from: https://knowledge.library.iup.edu/etd/1408.

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

Council of Science Editors:

Gresavage T. A Neural Networks Approach to Determining Angle and Scale of Partially Occluded Objects. [Thesis]. Indiana University of Pennsylvania; 2016. Available from: https://knowledge.library.iup.edu/etd/1408

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


Penn State University

30. Shihab, Rizvi. DEVELOPMENT AND TESTING OF AN EXPERT SYSTEM.

Degree: MS, Petroleum and Natural Gas Engineering, 2010, Penn State University

 The main topic of the research is the enhanced oil recovery (EOR) method of forward dry in-situ combustion (ISC). ISC is an EOR method used… (more)

Subjects/Keywords: in-situ combustion neural networks

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

APA (6th Edition):

Shihab, R. (2010). DEVELOPMENT AND TESTING OF AN EXPERT SYSTEM. (Masters Thesis). Penn State University. Retrieved from https://etda.libraries.psu.edu/catalog/12040

Chicago Manual of Style (16th Edition):

Shihab, Rizvi. “DEVELOPMENT AND TESTING OF AN EXPERT SYSTEM.” 2010. Masters Thesis, Penn State University. Accessed September 16, 2019. https://etda.libraries.psu.edu/catalog/12040.

MLA Handbook (7th Edition):

Shihab, Rizvi. “DEVELOPMENT AND TESTING OF AN EXPERT SYSTEM.” 2010. Web. 16 Sep 2019.

Vancouver:

Shihab R. DEVELOPMENT AND TESTING OF AN EXPERT SYSTEM. [Internet] [Masters thesis]. Penn State University; 2010. [cited 2019 Sep 16]. Available from: https://etda.libraries.psu.edu/catalog/12040.

Council of Science Editors:

Shihab R. DEVELOPMENT AND TESTING OF AN EXPERT SYSTEM. [Masters Thesis]. Penn State University; 2010. Available from: https://etda.libraries.psu.edu/catalog/12040

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