Advanced search options

Advanced Search Options 🞨

Browse by author name (“Author name starts with…”).

Find ETDs with:

in
/  
in
/  
in
/  
in

Written in Published in Earliest date Latest date

Sorted by

Results per page:

Sorted by: relevance · author · university · dateNew search

You searched for +publisher:"Delft University of Technology" +contributor:("Reinders, Marcel"). Showing records 1 – 27 of 27 total matches.

Search Limiters

Last 2 Years | English Only

No search limiters apply to these results.

▼ Search Limiters


Delft University of Technology

1. Pourquié, Valérie (author). Dynamics of the transcriptome and proteome in regions of the brain differ considerably.

Degree: 2019, Delft University of Technology

Human brain research is advancing, facilitated by improved high-throughput techniques and systematically preservation of brain tissue in brain banks. Due to the complex organization and… (more)

Subjects/Keywords: Brain; Proteomics; Transcriptomics

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

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

APA (6th Edition):

Pourquié, V. (. (2019). Dynamics of the transcriptome and proteome in regions of the brain differ considerably. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:38d4d9e6-f6a2-448a-9a31-c0fc3258a301

Chicago Manual of Style (16th Edition):

Pourquié, Valérie (author). “Dynamics of the transcriptome and proteome in regions of the brain differ considerably.” 2019. Masters Thesis, Delft University of Technology. Accessed February 27, 2021. http://resolver.tudelft.nl/uuid:38d4d9e6-f6a2-448a-9a31-c0fc3258a301.

MLA Handbook (7th Edition):

Pourquié, Valérie (author). “Dynamics of the transcriptome and proteome in regions of the brain differ considerably.” 2019. Web. 27 Feb 2021.

Vancouver:

Pourquié V(. Dynamics of the transcriptome and proteome in regions of the brain differ considerably. [Internet] [Masters thesis]. Delft University of Technology; 2019. [cited 2021 Feb 27]. Available from: http://resolver.tudelft.nl/uuid:38d4d9e6-f6a2-448a-9a31-c0fc3258a301.

Council of Science Editors:

Pourquié V(. Dynamics of the transcriptome and proteome in regions of the brain differ considerably. [Masters Thesis]. Delft University of Technology; 2019. Available from: http://resolver.tudelft.nl/uuid:38d4d9e6-f6a2-448a-9a31-c0fc3258a301


Delft University of Technology

2. Thomaidou, Eftychia (author). Inferring features from 5'UTR sequences to Translation Initiation Rates in S.cerevisiae.

Degree: 2017, Delft University of Technology

 In this research, we studied the impact of the 5'UTR sequences on translation. This is done by generating various features describing the 5'UTR. Those features… (more)

Subjects/Keywords: bioinformatics; Machine Learning; translation initiation rates; S.cerevisiae

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

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

APA (6th Edition):

Thomaidou, E. (. (2017). Inferring features from 5'UTR sequences to Translation Initiation Rates in S.cerevisiae. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:dbc6962c-d4d5-4dcb-b6d6-e832bfa05ad6

Chicago Manual of Style (16th Edition):

Thomaidou, Eftychia (author). “Inferring features from 5'UTR sequences to Translation Initiation Rates in S.cerevisiae.” 2017. Masters Thesis, Delft University of Technology. Accessed February 27, 2021. http://resolver.tudelft.nl/uuid:dbc6962c-d4d5-4dcb-b6d6-e832bfa05ad6.

MLA Handbook (7th Edition):

Thomaidou, Eftychia (author). “Inferring features from 5'UTR sequences to Translation Initiation Rates in S.cerevisiae.” 2017. Web. 27 Feb 2021.

Vancouver:

Thomaidou E(. Inferring features from 5'UTR sequences to Translation Initiation Rates in S.cerevisiae. [Internet] [Masters thesis]. Delft University of Technology; 2017. [cited 2021 Feb 27]. Available from: http://resolver.tudelft.nl/uuid:dbc6962c-d4d5-4dcb-b6d6-e832bfa05ad6.

Council of Science Editors:

Thomaidou E(. Inferring features from 5'UTR sequences to Translation Initiation Rates in S.cerevisiae. [Masters Thesis]. Delft University of Technology; 2017. Available from: http://resolver.tudelft.nl/uuid:dbc6962c-d4d5-4dcb-b6d6-e832bfa05ad6


Delft University of Technology

3. Michielsen, Lieke (author). Automatic cell identification in single-cell RNA-sequencing data.

Degree: 2020, Delft University of Technology

Since the revolution of single-cell RNA-sequencing, the number of available datasets has increased enormously. In these datasets, cell identification is mainly done manually, which is… (more)

Subjects/Keywords: Cell types; Transcriptomics; Machine learning

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

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

APA (6th Edition):

Michielsen, L. (. (2020). Automatic cell identification in single-cell RNA-sequencing data. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:a7a2a1f7-486e-47bb-afb8-7cdc891db795

Chicago Manual of Style (16th Edition):

Michielsen, Lieke (author). “Automatic cell identification in single-cell RNA-sequencing data.” 2020. Masters Thesis, Delft University of Technology. Accessed February 27, 2021. http://resolver.tudelft.nl/uuid:a7a2a1f7-486e-47bb-afb8-7cdc891db795.

MLA Handbook (7th Edition):

Michielsen, Lieke (author). “Automatic cell identification in single-cell RNA-sequencing data.” 2020. Web. 27 Feb 2021.

Vancouver:

Michielsen L(. Automatic cell identification in single-cell RNA-sequencing data. [Internet] [Masters thesis]. Delft University of Technology; 2020. [cited 2021 Feb 27]. Available from: http://resolver.tudelft.nl/uuid:a7a2a1f7-486e-47bb-afb8-7cdc891db795.

Council of Science Editors:

Michielsen L(. Automatic cell identification in single-cell RNA-sequencing data. [Masters Thesis]. Delft University of Technology; 2020. Available from: http://resolver.tudelft.nl/uuid:a7a2a1f7-486e-47bb-afb8-7cdc891db795


Delft University of Technology

4. Klip, Roy (author). Fuzzy Face Clustering For Forensic Investigations.

Degree: 2019, Delft University of Technology

 The amount of personal imagery kept on (mobile) devices is increasing by the day. Analysis and organization of these large collections of data are becoming… (more)

Subjects/Keywords: Face Clustering; Deep Learning; Fuzzy Clustering

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

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

APA (6th Edition):

Klip, R. (. (2019). Fuzzy Face Clustering For Forensic Investigations. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:a9f82787-ac3d-4ff1-8239-4f3c1c6414b9

Chicago Manual of Style (16th Edition):

Klip, Roy (author). “Fuzzy Face Clustering For Forensic Investigations.” 2019. Masters Thesis, Delft University of Technology. Accessed February 27, 2021. http://resolver.tudelft.nl/uuid:a9f82787-ac3d-4ff1-8239-4f3c1c6414b9.

MLA Handbook (7th Edition):

Klip, Roy (author). “Fuzzy Face Clustering For Forensic Investigations.” 2019. Web. 27 Feb 2021.

Vancouver:

Klip R(. Fuzzy Face Clustering For Forensic Investigations. [Internet] [Masters thesis]. Delft University of Technology; 2019. [cited 2021 Feb 27]. Available from: http://resolver.tudelft.nl/uuid:a9f82787-ac3d-4ff1-8239-4f3c1c6414b9.

Council of Science Editors:

Klip R(. Fuzzy Face Clustering For Forensic Investigations. [Masters Thesis]. Delft University of Technology; 2019. Available from: http://resolver.tudelft.nl/uuid:a9f82787-ac3d-4ff1-8239-4f3c1c6414b9


Delft University of Technology

5. Lengyel, Attila (author). Addressing Illumination-Based Domain Shifts in Deep Learning: A Physics-Based Approach.

Degree: 2019, Delft University of Technology

 This work investigates how prior knowledge from physics-based reflection models can be used to improve the performance of semantic segmentation models under an illumination-based domain… (more)

Subjects/Keywords: Semantic segmentation; color invariants; deep learning; computer vision; domain adaptation

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

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

APA (6th Edition):

Lengyel, A. (. (2019). Addressing Illumination-Based Domain Shifts in Deep Learning: A Physics-Based Approach. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:f8619273-0e7e-42e3-990b-67e2f6edc78a

Chicago Manual of Style (16th Edition):

Lengyel, Attila (author). “Addressing Illumination-Based Domain Shifts in Deep Learning: A Physics-Based Approach.” 2019. Masters Thesis, Delft University of Technology. Accessed February 27, 2021. http://resolver.tudelft.nl/uuid:f8619273-0e7e-42e3-990b-67e2f6edc78a.

MLA Handbook (7th Edition):

Lengyel, Attila (author). “Addressing Illumination-Based Domain Shifts in Deep Learning: A Physics-Based Approach.” 2019. Web. 27 Feb 2021.

Vancouver:

Lengyel A(. Addressing Illumination-Based Domain Shifts in Deep Learning: A Physics-Based Approach. [Internet] [Masters thesis]. Delft University of Technology; 2019. [cited 2021 Feb 27]. Available from: http://resolver.tudelft.nl/uuid:f8619273-0e7e-42e3-990b-67e2f6edc78a.

Council of Science Editors:

Lengyel A(. Addressing Illumination-Based Domain Shifts in Deep Learning: A Physics-Based Approach. [Masters Thesis]. Delft University of Technology; 2019. Available from: http://resolver.tudelft.nl/uuid:f8619273-0e7e-42e3-990b-67e2f6edc78a


Delft University of Technology

6. Elghlan, Faris (author). One-Class Classification: for high-dimensional data.

Degree: 2019, Delft University of Technology

This M.Sc. thesis report investigates the application of one-class classification techniques to complex high-dimensional data. The aim of a one-class classifier is to separate target… (more)

Subjects/Keywords: one-class; classification; high-dimensional; Autoencoder; GAN; Wasserstein Autoencoder; Pattern Recognition; Machine Learning; Deep Learning

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

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

APA (6th Edition):

Elghlan, F. (. (2019). One-Class Classification: for high-dimensional data. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:b5aabe84-8a8b-4841-848d-136ab6ce0825

Chicago Manual of Style (16th Edition):

Elghlan, Faris (author). “One-Class Classification: for high-dimensional data.” 2019. Masters Thesis, Delft University of Technology. Accessed February 27, 2021. http://resolver.tudelft.nl/uuid:b5aabe84-8a8b-4841-848d-136ab6ce0825.

MLA Handbook (7th Edition):

Elghlan, Faris (author). “One-Class Classification: for high-dimensional data.” 2019. Web. 27 Feb 2021.

Vancouver:

Elghlan F(. One-Class Classification: for high-dimensional data. [Internet] [Masters thesis]. Delft University of Technology; 2019. [cited 2021 Feb 27]. Available from: http://resolver.tudelft.nl/uuid:b5aabe84-8a8b-4841-848d-136ab6ce0825.

Council of Science Editors:

Elghlan F(. One-Class Classification: for high-dimensional data. [Masters Thesis]. Delft University of Technology; 2019. Available from: http://resolver.tudelft.nl/uuid:b5aabe84-8a8b-4841-848d-136ab6ce0825


Delft University of Technology

7. Pathak, Chinmay (author). Exploring normalizing flow for anomaly detection.

Degree: 2019, Delft University of Technology

Anomaly detection is a task of interest in many domains. Typical way of tackling this problem is using an unsupervised way. Recently, deep neural network… (more)

Subjects/Keywords: Anomaly Detection; Outlier detection; Autoencoder; Generative Algorithms; unsupervised learning; one-class classification; GLOW; Normalizing flows

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

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

APA (6th Edition):

Pathak, C. (. (2019). Exploring normalizing flow for anomaly detection. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:f5588df3-626d-42cc-8059-32e5bb16d852

Chicago Manual of Style (16th Edition):

Pathak, Chinmay (author). “Exploring normalizing flow for anomaly detection.” 2019. Masters Thesis, Delft University of Technology. Accessed February 27, 2021. http://resolver.tudelft.nl/uuid:f5588df3-626d-42cc-8059-32e5bb16d852.

MLA Handbook (7th Edition):

Pathak, Chinmay (author). “Exploring normalizing flow for anomaly detection.” 2019. Web. 27 Feb 2021.

Vancouver:

Pathak C(. Exploring normalizing flow for anomaly detection. [Internet] [Masters thesis]. Delft University of Technology; 2019. [cited 2021 Feb 27]. Available from: http://resolver.tudelft.nl/uuid:f5588df3-626d-42cc-8059-32e5bb16d852.

Council of Science Editors:

Pathak C(. Exploring normalizing flow for anomaly detection. [Masters Thesis]. Delft University of Technology; 2019. Available from: http://resolver.tudelft.nl/uuid:f5588df3-626d-42cc-8059-32e5bb16d852


Delft University of Technology

8. Garbacz, Mateusz (author). Time series forecast in non-stationary environment with occurrence of economic bubbles: Bitcoin Price prediction.

Degree: 2018, Delft University of Technology

 Being capable to foresee the future of a given financial asset as an investor, may lead to significant economic profits. Therefore, stock market prediction is… (more)

Subjects/Keywords: Bitcoin; Bubble; Prediction; Machine Learning; Deep Learning; Non-stationarity

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

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

APA (6th Edition):

Garbacz, M. (. (2018). Time series forecast in non-stationary environment with occurrence of economic bubbles: Bitcoin Price prediction. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:13d6eb0e-4b34-4a41-86a8-9cbab66ecfa0

Chicago Manual of Style (16th Edition):

Garbacz, Mateusz (author). “Time series forecast in non-stationary environment with occurrence of economic bubbles: Bitcoin Price prediction.” 2018. Masters Thesis, Delft University of Technology. Accessed February 27, 2021. http://resolver.tudelft.nl/uuid:13d6eb0e-4b34-4a41-86a8-9cbab66ecfa0.

MLA Handbook (7th Edition):

Garbacz, Mateusz (author). “Time series forecast in non-stationary environment with occurrence of economic bubbles: Bitcoin Price prediction.” 2018. Web. 27 Feb 2021.

Vancouver:

Garbacz M(. Time series forecast in non-stationary environment with occurrence of economic bubbles: Bitcoin Price prediction. [Internet] [Masters thesis]. Delft University of Technology; 2018. [cited 2021 Feb 27]. Available from: http://resolver.tudelft.nl/uuid:13d6eb0e-4b34-4a41-86a8-9cbab66ecfa0.

Council of Science Editors:

Garbacz M(. Time series forecast in non-stationary environment with occurrence of economic bubbles: Bitcoin Price prediction. [Masters Thesis]. Delft University of Technology; 2018. Available from: http://resolver.tudelft.nl/uuid:13d6eb0e-4b34-4a41-86a8-9cbab66ecfa0


Delft University of Technology

9. Lelekas, Ioannis (author). Top-Down Networks: A coarse-to-fine reimagination of CNNs.

Degree: 2020, Delft University of Technology

 Biological vision adopts a coarse-to-fine information processing pathway, from initial visual detection and binding of salient features of a visual scene, to the enhanced and… (more)

Subjects/Keywords: Computer Vision; Deep Learning; Convolutional Neural Networks; Top-Down; Fine-to-Coarse; Coarse-to-Fine; Adversarial attacks; Adversarial robustness; Gradcam; Object localization

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

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

APA (6th Edition):

Lelekas, I. (. (2020). Top-Down Networks: A coarse-to-fine reimagination of CNNs. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:11888a7b-1e54-424d-9daa-8ff48de58345

Chicago Manual of Style (16th Edition):

Lelekas, Ioannis (author). “Top-Down Networks: A coarse-to-fine reimagination of CNNs.” 2020. Masters Thesis, Delft University of Technology. Accessed February 27, 2021. http://resolver.tudelft.nl/uuid:11888a7b-1e54-424d-9daa-8ff48de58345.

MLA Handbook (7th Edition):

Lelekas, Ioannis (author). “Top-Down Networks: A coarse-to-fine reimagination of CNNs.” 2020. Web. 27 Feb 2021.

Vancouver:

Lelekas I(. Top-Down Networks: A coarse-to-fine reimagination of CNNs. [Internet] [Masters thesis]. Delft University of Technology; 2020. [cited 2021 Feb 27]. Available from: http://resolver.tudelft.nl/uuid:11888a7b-1e54-424d-9daa-8ff48de58345.

Council of Science Editors:

Lelekas I(. Top-Down Networks: A coarse-to-fine reimagination of CNNs. [Masters Thesis]. Delft University of Technology; 2020. Available from: http://resolver.tudelft.nl/uuid:11888a7b-1e54-424d-9daa-8ff48de58345


Delft University of Technology

10. Li, Yadong (author). Quantitative evaluation of Generative Adversarial Networks and improved training techniques.

Degree: 2018, Delft University of Technology

 Generative adversarial networks (GANs) are a class of generative models, for which the goal is to learn from training data and then to generate data… (more)

Subjects/Keywords: Generative Adversarial Networks; Quantitative Evaluation; Wasserstein GANs

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

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

APA (6th Edition):

Li, Y. (. (2018). Quantitative evaluation of Generative Adversarial Networks and improved training techniques. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:b01dcd2b-fdbd-4531-bf1b-0c0b2881df48

Chicago Manual of Style (16th Edition):

Li, Yadong (author). “Quantitative evaluation of Generative Adversarial Networks and improved training techniques.” 2018. Masters Thesis, Delft University of Technology. Accessed February 27, 2021. http://resolver.tudelft.nl/uuid:b01dcd2b-fdbd-4531-bf1b-0c0b2881df48.

MLA Handbook (7th Edition):

Li, Yadong (author). “Quantitative evaluation of Generative Adversarial Networks and improved training techniques.” 2018. Web. 27 Feb 2021.

Vancouver:

Li Y(. Quantitative evaluation of Generative Adversarial Networks and improved training techniques. [Internet] [Masters thesis]. Delft University of Technology; 2018. [cited 2021 Feb 27]. Available from: http://resolver.tudelft.nl/uuid:b01dcd2b-fdbd-4531-bf1b-0c0b2881df48.

Council of Science Editors:

Li Y(. Quantitative evaluation of Generative Adversarial Networks and improved training techniques. [Masters Thesis]. Delft University of Technology; 2018. Available from: http://resolver.tudelft.nl/uuid:b01dcd2b-fdbd-4531-bf1b-0c0b2881df48


Delft University of Technology

11. van Doorn, Felix (author). Rituals of Leaving: Predictive Modelling of Leaving Behaviour in Conversation.

Degree: 2018, Delft University of Technology

 In this thesis, leaving behaviour in a small group setting is studied. In the past, group conversations have mostly been studied in a static setting.… (more)

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

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

APA (6th Edition):

van Doorn, F. (. (2018). Rituals of Leaving: Predictive Modelling of Leaving Behaviour in Conversation. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:b13e7c6e-03ee-43b2-8b0a-6b79c5e31e5b

Chicago Manual of Style (16th Edition):

van Doorn, Felix (author). “Rituals of Leaving: Predictive Modelling of Leaving Behaviour in Conversation.” 2018. Masters Thesis, Delft University of Technology. Accessed February 27, 2021. http://resolver.tudelft.nl/uuid:b13e7c6e-03ee-43b2-8b0a-6b79c5e31e5b.

MLA Handbook (7th Edition):

van Doorn, Felix (author). “Rituals of Leaving: Predictive Modelling of Leaving Behaviour in Conversation.” 2018. Web. 27 Feb 2021.

Vancouver:

van Doorn F(. Rituals of Leaving: Predictive Modelling of Leaving Behaviour in Conversation. [Internet] [Masters thesis]. Delft University of Technology; 2018. [cited 2021 Feb 27]. Available from: http://resolver.tudelft.nl/uuid:b13e7c6e-03ee-43b2-8b0a-6b79c5e31e5b.

Council of Science Editors:

van Doorn F(. Rituals of Leaving: Predictive Modelling of Leaving Behaviour in Conversation. [Masters Thesis]. Delft University of Technology; 2018. Available from: http://resolver.tudelft.nl/uuid:b13e7c6e-03ee-43b2-8b0a-6b79c5e31e5b


Delft University of Technology

12. Uijens, Wouter (author). Activating frequencies: Exploring non-linearities in the Fourier domain.

Degree: 2018, Delft University of Technology

 Convolutional Neural Networks (CNNs) are achieving state of the art performance in computer vision. One downside of CNNs is their computational complexity. One way to… (more)

Subjects/Keywords: Machine Learning; Fourier Transform; Activation Function

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

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

APA (6th Edition):

Uijens, W. (. (2018). Activating frequencies: Exploring non-linearities in the Fourier domain. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:b6dfdac6-691d-44a4-bacb-645df5cfdeaf

Chicago Manual of Style (16th Edition):

Uijens, Wouter (author). “Activating frequencies: Exploring non-linearities in the Fourier domain.” 2018. Masters Thesis, Delft University of Technology. Accessed February 27, 2021. http://resolver.tudelft.nl/uuid:b6dfdac6-691d-44a4-bacb-645df5cfdeaf.

MLA Handbook (7th Edition):

Uijens, Wouter (author). “Activating frequencies: Exploring non-linearities in the Fourier domain.” 2018. Web. 27 Feb 2021.

Vancouver:

Uijens W(. Activating frequencies: Exploring non-linearities in the Fourier domain. [Internet] [Masters thesis]. Delft University of Technology; 2018. [cited 2021 Feb 27]. Available from: http://resolver.tudelft.nl/uuid:b6dfdac6-691d-44a4-bacb-645df5cfdeaf.

Council of Science Editors:

Uijens W(. Activating frequencies: Exploring non-linearities in the Fourier domain. [Masters Thesis]. Delft University of Technology; 2018. Available from: http://resolver.tudelft.nl/uuid:b6dfdac6-691d-44a4-bacb-645df5cfdeaf


Delft University of Technology

13. Wen, Xiaoming (author). Learning Scale-Aware Optical Flow.

Degree: 2018, Delft University of Technology

 Optical flow is a representation of projected real-world motion of the object between two consecutive images. The optical flow measures the pixel displacement on the… (more)

Subjects/Keywords: Optica Flow; CNN; Scale-Aware; Derivative

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

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

APA (6th Edition):

Wen, X. (. (2018). Learning Scale-Aware Optical Flow. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:7e29ed6a-b1d8-490b-bfa0-b576e6e7887c

Chicago Manual of Style (16th Edition):

Wen, Xiaoming (author). “Learning Scale-Aware Optical Flow.” 2018. Masters Thesis, Delft University of Technology. Accessed February 27, 2021. http://resolver.tudelft.nl/uuid:7e29ed6a-b1d8-490b-bfa0-b576e6e7887c.

MLA Handbook (7th Edition):

Wen, Xiaoming (author). “Learning Scale-Aware Optical Flow.” 2018. Web. 27 Feb 2021.

Vancouver:

Wen X(. Learning Scale-Aware Optical Flow. [Internet] [Masters thesis]. Delft University of Technology; 2018. [cited 2021 Feb 27]. Available from: http://resolver.tudelft.nl/uuid:7e29ed6a-b1d8-490b-bfa0-b576e6e7887c.

Council of Science Editors:

Wen X(. Learning Scale-Aware Optical Flow. [Masters Thesis]. Delft University of Technology; 2018. Available from: http://resolver.tudelft.nl/uuid:7e29ed6a-b1d8-490b-bfa0-b576e6e7887c


Delft University of Technology

14. Priadi Teguh Wibowo, Priadi (author). Automatic Running Event Visualization using Video from Multiple Camera.

Degree: 2019, Delft University of Technology

Visualizing runners trajectory from video data is not straightforward because the video data does not contain the explicit information of which runners appear in the… (more)

Subjects/Keywords: Computer Vision; Deep Learning; Visualization; Person Re-identification; Scene Text Recognition

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

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

APA (6th Edition):

Priadi Teguh Wibowo, P. (. (2019). Automatic Running Event Visualization using Video from Multiple Camera. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:9b246dbe-2708-4aa4-808b-36b92b040174

Chicago Manual of Style (16th Edition):

Priadi Teguh Wibowo, Priadi (author). “Automatic Running Event Visualization using Video from Multiple Camera.” 2019. Masters Thesis, Delft University of Technology. Accessed February 27, 2021. http://resolver.tudelft.nl/uuid:9b246dbe-2708-4aa4-808b-36b92b040174.

MLA Handbook (7th Edition):

Priadi Teguh Wibowo, Priadi (author). “Automatic Running Event Visualization using Video from Multiple Camera.” 2019. Web. 27 Feb 2021.

Vancouver:

Priadi Teguh Wibowo P(. Automatic Running Event Visualization using Video from Multiple Camera. [Internet] [Masters thesis]. Delft University of Technology; 2019. [cited 2021 Feb 27]. Available from: http://resolver.tudelft.nl/uuid:9b246dbe-2708-4aa4-808b-36b92b040174.

Council of Science Editors:

Priadi Teguh Wibowo P(. Automatic Running Event Visualization using Video from Multiple Camera. [Masters Thesis]. Delft University of Technology; 2019. Available from: http://resolver.tudelft.nl/uuid:9b246dbe-2708-4aa4-808b-36b92b040174


Delft University of Technology

15. Liu, Lu (author). People Detection from Overhead Cameras: A study of impact of occlusion on performance.

Degree: 2018, Delft University of Technology

During the last decades, people detection has received great attention in computer vision and pattern recognition because of its various applications. Though there are thousands… (more)

Subjects/Keywords: People Detection; Occlusion; Deep Learning

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

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

APA (6th Edition):

Liu, L. (. (2018). People Detection from Overhead Cameras: A study of impact of occlusion on performance. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:33a6b9b6-f26c-4ef1-8047-5c33d95487c6

Chicago Manual of Style (16th Edition):

Liu, Lu (author). “People Detection from Overhead Cameras: A study of impact of occlusion on performance.” 2018. Masters Thesis, Delft University of Technology. Accessed February 27, 2021. http://resolver.tudelft.nl/uuid:33a6b9b6-f26c-4ef1-8047-5c33d95487c6.

MLA Handbook (7th Edition):

Liu, Lu (author). “People Detection from Overhead Cameras: A study of impact of occlusion on performance.” 2018. Web. 27 Feb 2021.

Vancouver:

Liu L(. People Detection from Overhead Cameras: A study of impact of occlusion on performance. [Internet] [Masters thesis]. Delft University of Technology; 2018. [cited 2021 Feb 27]. Available from: http://resolver.tudelft.nl/uuid:33a6b9b6-f26c-4ef1-8047-5c33d95487c6.

Council of Science Editors:

Liu L(. People Detection from Overhead Cameras: A study of impact of occlusion on performance. [Masters Thesis]. Delft University of Technology; 2018. Available from: http://resolver.tudelft.nl/uuid:33a6b9b6-f26c-4ef1-8047-5c33d95487c6


Delft University of Technology

16. Starre, Rolf (author). Action Selection Policies for Walking Monte Carlo Tree Search.

Degree: 2018, Delft University of Technology

 Recent Reinforcement Learning methods have combined function approximation and Monte Carlo Tree Search and are able to learn by self-play up to a very high… (more)

Subjects/Keywords: Monte Carlo Tree Search; Reinforcement Learning; Exploration; Action selection policies

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

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

APA (6th Edition):

Starre, R. (. (2018). Action Selection Policies for Walking Monte Carlo Tree Search. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:3947ef53-eab3-46a2-9efc-fff985cd96c9

Chicago Manual of Style (16th Edition):

Starre, Rolf (author). “Action Selection Policies for Walking Monte Carlo Tree Search.” 2018. Masters Thesis, Delft University of Technology. Accessed February 27, 2021. http://resolver.tudelft.nl/uuid:3947ef53-eab3-46a2-9efc-fff985cd96c9.

MLA Handbook (7th Edition):

Starre, Rolf (author). “Action Selection Policies for Walking Monte Carlo Tree Search.” 2018. Web. 27 Feb 2021.

Vancouver:

Starre R(. Action Selection Policies for Walking Monte Carlo Tree Search. [Internet] [Masters thesis]. Delft University of Technology; 2018. [cited 2021 Feb 27]. Available from: http://resolver.tudelft.nl/uuid:3947ef53-eab3-46a2-9efc-fff985cd96c9.

Council of Science Editors:

Starre R(. Action Selection Policies for Walking Monte Carlo Tree Search. [Masters Thesis]. Delft University of Technology; 2018. Available from: http://resolver.tudelft.nl/uuid:3947ef53-eab3-46a2-9efc-fff985cd96c9


Delft University of Technology

17. Kolthof, Daan (author). Recognizing and Handling Negations in Machine Learning.

Degree: 2018, Delft University of Technology

 In several machine learning problems, a relatively small subproblem is present in which combinations of (negating) objects or structures result in a negation or otherwise… (more)

Subjects/Keywords: Machine Learning; Neural Networks; Natural Language Processing; sentiment analysis; sentiment classification; Word embedding; Negation Handling; Negation Recognition

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

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

APA (6th Edition):

Kolthof, D. (. (2018). Recognizing and Handling Negations in Machine Learning. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:caa1b4b3-59ca-4290-b95e-84190c54b787

Chicago Manual of Style (16th Edition):

Kolthof, Daan (author). “Recognizing and Handling Negations in Machine Learning.” 2018. Masters Thesis, Delft University of Technology. Accessed February 27, 2021. http://resolver.tudelft.nl/uuid:caa1b4b3-59ca-4290-b95e-84190c54b787.

MLA Handbook (7th Edition):

Kolthof, Daan (author). “Recognizing and Handling Negations in Machine Learning.” 2018. Web. 27 Feb 2021.

Vancouver:

Kolthof D(. Recognizing and Handling Negations in Machine Learning. [Internet] [Masters thesis]. Delft University of Technology; 2018. [cited 2021 Feb 27]. Available from: http://resolver.tudelft.nl/uuid:caa1b4b3-59ca-4290-b95e-84190c54b787.

Council of Science Editors:

Kolthof D(. Recognizing and Handling Negations in Machine Learning. [Masters Thesis]. Delft University of Technology; 2018. Available from: http://resolver.tudelft.nl/uuid:caa1b4b3-59ca-4290-b95e-84190c54b787


Delft University of Technology

18. Mandersloot, Jeroen (author). Model-based rare category detection for temporal data.

Degree: 2018, Delft University of Technology

 Rare category detection is the task of discovering rare classes in unlabelled and imbalanced datasets. Existing algorithms focus almost exclusively on static data in which… (more)

Subjects/Keywords: rare category detection; temporal data; semi-supervised learning; mixture models; markov random fields

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

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

APA (6th Edition):

Mandersloot, J. (. (2018). Model-based rare category detection for temporal data. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:80755ee1-95c9-4b7d-b828-fff818ceadd4

Chicago Manual of Style (16th Edition):

Mandersloot, Jeroen (author). “Model-based rare category detection for temporal data.” 2018. Masters Thesis, Delft University of Technology. Accessed February 27, 2021. http://resolver.tudelft.nl/uuid:80755ee1-95c9-4b7d-b828-fff818ceadd4.

MLA Handbook (7th Edition):

Mandersloot, Jeroen (author). “Model-based rare category detection for temporal data.” 2018. Web. 27 Feb 2021.

Vancouver:

Mandersloot J(. Model-based rare category detection for temporal data. [Internet] [Masters thesis]. Delft University of Technology; 2018. [cited 2021 Feb 27]. Available from: http://resolver.tudelft.nl/uuid:80755ee1-95c9-4b7d-b828-fff818ceadd4.

Council of Science Editors:

Mandersloot J(. Model-based rare category detection for temporal data. [Masters Thesis]. Delft University of Technology; 2018. Available from: http://resolver.tudelft.nl/uuid:80755ee1-95c9-4b7d-b828-fff818ceadd4


Delft University of Technology

19. Adhikari, Ajaya (author). Example and Feature importance-based Explanations for Black-box Machine Learning Models.

Degree: 2018, Delft University of Technology

 Machine Learning (ML) is a rapidly growing field. There has been a surge of complex black-box models with high performance. On the other hand, the… (more)

Subjects/Keywords: example-based explanation; explainable machine Learning; contrastive explanation; feature importance explanation; leafage

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

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

APA (6th Edition):

Adhikari, A. (. (2018). Example and Feature importance-based Explanations for Black-box Machine Learning Models. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:f8f9df3e-7668-418d-9dd2-92f4023e2187

Chicago Manual of Style (16th Edition):

Adhikari, Ajaya (author). “Example and Feature importance-based Explanations for Black-box Machine Learning Models.” 2018. Masters Thesis, Delft University of Technology. Accessed February 27, 2021. http://resolver.tudelft.nl/uuid:f8f9df3e-7668-418d-9dd2-92f4023e2187.

MLA Handbook (7th Edition):

Adhikari, Ajaya (author). “Example and Feature importance-based Explanations for Black-box Machine Learning Models.” 2018. Web. 27 Feb 2021.

Vancouver:

Adhikari A(. Example and Feature importance-based Explanations for Black-box Machine Learning Models. [Internet] [Masters thesis]. Delft University of Technology; 2018. [cited 2021 Feb 27]. Available from: http://resolver.tudelft.nl/uuid:f8f9df3e-7668-418d-9dd2-92f4023e2187.

Council of Science Editors:

Adhikari A(. Example and Feature importance-based Explanations for Black-box Machine Learning Models. [Masters Thesis]. Delft University of Technology; 2018. Available from: http://resolver.tudelft.nl/uuid:f8f9df3e-7668-418d-9dd2-92f4023e2187


Delft University of Technology

20. Brand, Patrick (author). Automated land use classification: Supervised segmentation of road structures on aerial images using shape regression.

Degree: 2019, Delft University of Technology

Recent advances in Artificial Intelligence and Computer Vision have been showed to be promising for automated land use classification of remotely sensed data. However, current… (more)

Subjects/Keywords: Computer vision; Deep learning; Remote sensing; Semantic segmentation; Shape regression; Land use

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

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

APA (6th Edition):

Brand, P. (. (2019). Automated land use classification: Supervised segmentation of road structures on aerial images using shape regression. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:9917401d-c38d-4ad8-9d5c-75657058c3e6

Chicago Manual of Style (16th Edition):

Brand, Patrick (author). “Automated land use classification: Supervised segmentation of road structures on aerial images using shape regression.” 2019. Masters Thesis, Delft University of Technology. Accessed February 27, 2021. http://resolver.tudelft.nl/uuid:9917401d-c38d-4ad8-9d5c-75657058c3e6.

MLA Handbook (7th Edition):

Brand, Patrick (author). “Automated land use classification: Supervised segmentation of road structures on aerial images using shape regression.” 2019. Web. 27 Feb 2021.

Vancouver:

Brand P(. Automated land use classification: Supervised segmentation of road structures on aerial images using shape regression. [Internet] [Masters thesis]. Delft University of Technology; 2019. [cited 2021 Feb 27]. Available from: http://resolver.tudelft.nl/uuid:9917401d-c38d-4ad8-9d5c-75657058c3e6.

Council of Science Editors:

Brand P(. Automated land use classification: Supervised segmentation of road structures on aerial images using shape regression. [Masters Thesis]. Delft University of Technology; 2019. Available from: http://resolver.tudelft.nl/uuid:9917401d-c38d-4ad8-9d5c-75657058c3e6


Delft University of Technology

21. Liu, Xin (author). Unsupervised Cross Domain Image Matching with Outlier Detection.

Degree: 2018, Delft University of Technology

This work proposes a method for matching images from different domains in an unsupervised manner, and detecting outlier samples in the target domain at the… (more)

Subjects/Keywords: Computer Vision; Domain Adaptation; Image Matching; Outlier Detection

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

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

APA (6th Edition):

Liu, X. (. (2018). Unsupervised Cross Domain Image Matching with Outlier Detection. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:fcd6c0f8-6618-4fdb-b8ad-e183b3a81b73

Chicago Manual of Style (16th Edition):

Liu, Xin (author). “Unsupervised Cross Domain Image Matching with Outlier Detection.” 2018. Masters Thesis, Delft University of Technology. Accessed February 27, 2021. http://resolver.tudelft.nl/uuid:fcd6c0f8-6618-4fdb-b8ad-e183b3a81b73.

MLA Handbook (7th Edition):

Liu, Xin (author). “Unsupervised Cross Domain Image Matching with Outlier Detection.” 2018. Web. 27 Feb 2021.

Vancouver:

Liu X(. Unsupervised Cross Domain Image Matching with Outlier Detection. [Internet] [Masters thesis]. Delft University of Technology; 2018. [cited 2021 Feb 27]. Available from: http://resolver.tudelft.nl/uuid:fcd6c0f8-6618-4fdb-b8ad-e183b3a81b73.

Council of Science Editors:

Liu X(. Unsupervised Cross Domain Image Matching with Outlier Detection. [Masters Thesis]. Delft University of Technology; 2018. Available from: http://resolver.tudelft.nl/uuid:fcd6c0f8-6618-4fdb-b8ad-e183b3a81b73


Delft University of Technology

22. Li, Jiahui (author). Attention-Aware Age-Agnostic Visual Place Recognition.

Degree: 2019, Delft University of Technology

 A cross-domain visual place recognition (VPR) task is proposed in this work, i.e., matching images of the same architectures depicted in different domains. VPR is… (more)

Subjects/Keywords: Computer Vision; Domain Adaptation; Image Matching; Attention Mechanism

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

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

APA (6th Edition):

Li, J. (. (2019). Attention-Aware Age-Agnostic Visual Place Recognition. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:250d37a9-bc0d-4f8f-8d1a-d31a98dc22d7

Chicago Manual of Style (16th Edition):

Li, Jiahui (author). “Attention-Aware Age-Agnostic Visual Place Recognition.” 2019. Masters Thesis, Delft University of Technology. Accessed February 27, 2021. http://resolver.tudelft.nl/uuid:250d37a9-bc0d-4f8f-8d1a-d31a98dc22d7.

MLA Handbook (7th Edition):

Li, Jiahui (author). “Attention-Aware Age-Agnostic Visual Place Recognition.” 2019. Web. 27 Feb 2021.

Vancouver:

Li J(. Attention-Aware Age-Agnostic Visual Place Recognition. [Internet] [Masters thesis]. Delft University of Technology; 2019. [cited 2021 Feb 27]. Available from: http://resolver.tudelft.nl/uuid:250d37a9-bc0d-4f8f-8d1a-d31a98dc22d7.

Council of Science Editors:

Li J(. Attention-Aware Age-Agnostic Visual Place Recognition. [Masters Thesis]. Delft University of Technology; 2019. Available from: http://resolver.tudelft.nl/uuid:250d37a9-bc0d-4f8f-8d1a-d31a98dc22d7


Delft University of Technology

23. Dhar, Aniket (author). Rotation invariant filters in CNNs: applied to segmentation of aerial images for land-use classification.

Degree: 2018, Delft University of Technology

Convolutional neural networks are showing incredible performance in image classification, segmentation, object detection and other computer vision applications in recent years. But they lack understanding… (more)

Subjects/Keywords: Computer Vision; Deep Learning; Machine Learning; Convolutional Neural Networks

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

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

APA (6th Edition):

Dhar, A. (. (2018). Rotation invariant filters in CNNs: applied to segmentation of aerial images for land-use classification. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:1624a31f-7976-425a-a2b6-d6937cc39895

Chicago Manual of Style (16th Edition):

Dhar, Aniket (author). “Rotation invariant filters in CNNs: applied to segmentation of aerial images for land-use classification.” 2018. Masters Thesis, Delft University of Technology. Accessed February 27, 2021. http://resolver.tudelft.nl/uuid:1624a31f-7976-425a-a2b6-d6937cc39895.

MLA Handbook (7th Edition):

Dhar, Aniket (author). “Rotation invariant filters in CNNs: applied to segmentation of aerial images for land-use classification.” 2018. Web. 27 Feb 2021.

Vancouver:

Dhar A(. Rotation invariant filters in CNNs: applied to segmentation of aerial images for land-use classification. [Internet] [Masters thesis]. Delft University of Technology; 2018. [cited 2021 Feb 27]. Available from: http://resolver.tudelft.nl/uuid:1624a31f-7976-425a-a2b6-d6937cc39895.

Council of Science Editors:

Dhar A(. Rotation invariant filters in CNNs: applied to segmentation of aerial images for land-use classification. [Masters Thesis]. Delft University of Technology; 2018. Available from: http://resolver.tudelft.nl/uuid:1624a31f-7976-425a-a2b6-d6937cc39895


Delft University of Technology

24. van Bekhoven, Sjoerd (author). Predicting voluntary employee turnover using core employee data.

Degree: 2017, Delft University of Technology

 Voluntary employee turnover is the process of an employee voluntarily choosing to resign from a company. High voluntary turnover has been shown to have negative… (more)

Subjects/Keywords: voluntary employee turnover; people analytics; binary classification; feature design; class imbalance; class overlap; feature importance

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

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

APA (6th Edition):

van Bekhoven, S. (. (2017). Predicting voluntary employee turnover using core employee data. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:95411815-890a-4aba-b6e0-336c9080cfc0

Chicago Manual of Style (16th Edition):

van Bekhoven, Sjoerd (author). “Predicting voluntary employee turnover using core employee data.” 2017. Masters Thesis, Delft University of Technology. Accessed February 27, 2021. http://resolver.tudelft.nl/uuid:95411815-890a-4aba-b6e0-336c9080cfc0.

MLA Handbook (7th Edition):

van Bekhoven, Sjoerd (author). “Predicting voluntary employee turnover using core employee data.” 2017. Web. 27 Feb 2021.

Vancouver:

van Bekhoven S(. Predicting voluntary employee turnover using core employee data. [Internet] [Masters thesis]. Delft University of Technology; 2017. [cited 2021 Feb 27]. Available from: http://resolver.tudelft.nl/uuid:95411815-890a-4aba-b6e0-336c9080cfc0.

Council of Science Editors:

van Bekhoven S(. Predicting voluntary employee turnover using core employee data. [Masters Thesis]. Delft University of Technology; 2017. Available from: http://resolver.tudelft.nl/uuid:95411815-890a-4aba-b6e0-336c9080cfc0


Delft University of Technology

25. van Garderen, Karin (author). Active Learning for Overlay Prediction in Semi-conductor Manufacturing.

Degree: 2018, Delft University of Technology

 In the manufacturing of semi-conductor devices there is a constant demand for increasing precision and yield. Measuring and controlling overlay errors is essential in this… (more)

Subjects/Keywords: Active Learning; Regression; Visualization

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

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

APA (6th Edition):

van Garderen, K. (. (2018). Active Learning for Overlay Prediction in Semi-conductor Manufacturing. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:21b8d90a-a30c-49ea-8ef3-6dc98da25b66

Chicago Manual of Style (16th Edition):

van Garderen, Karin (author). “Active Learning for Overlay Prediction in Semi-conductor Manufacturing.” 2018. Masters Thesis, Delft University of Technology. Accessed February 27, 2021. http://resolver.tudelft.nl/uuid:21b8d90a-a30c-49ea-8ef3-6dc98da25b66.

MLA Handbook (7th Edition):

van Garderen, Karin (author). “Active Learning for Overlay Prediction in Semi-conductor Manufacturing.” 2018. Web. 27 Feb 2021.

Vancouver:

van Garderen K(. Active Learning for Overlay Prediction in Semi-conductor Manufacturing. [Internet] [Masters thesis]. Delft University of Technology; 2018. [cited 2021 Feb 27]. Available from: http://resolver.tudelft.nl/uuid:21b8d90a-a30c-49ea-8ef3-6dc98da25b66.

Council of Science Editors:

van Garderen K(. Active Learning for Overlay Prediction in Semi-conductor Manufacturing. [Masters Thesis]. Delft University of Technology; 2018. Available from: http://resolver.tudelft.nl/uuid:21b8d90a-a30c-49ea-8ef3-6dc98da25b66


Delft University of Technology

26. Hulsebos, Madelon (author). Outlier detection in multivariate time series: Exploiting reconstructions from random projections.

Degree: 2018, Delft University of Technology

Subjects/Keywords: online learning; outlier detection; unsupervised learning; multivariate time series; random projections

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

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

APA (6th Edition):

Hulsebos, M. (. (2018). Outlier detection in multivariate time series: Exploiting reconstructions from random projections. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:0deb1a07-6b09-47e5-970a-b192eaea9591

Chicago Manual of Style (16th Edition):

Hulsebos, Madelon (author). “Outlier detection in multivariate time series: Exploiting reconstructions from random projections.” 2018. Masters Thesis, Delft University of Technology. Accessed February 27, 2021. http://resolver.tudelft.nl/uuid:0deb1a07-6b09-47e5-970a-b192eaea9591.

MLA Handbook (7th Edition):

Hulsebos, Madelon (author). “Outlier detection in multivariate time series: Exploiting reconstructions from random projections.” 2018. Web. 27 Feb 2021.

Vancouver:

Hulsebos M(. Outlier detection in multivariate time series: Exploiting reconstructions from random projections. [Internet] [Masters thesis]. Delft University of Technology; 2018. [cited 2021 Feb 27]. Available from: http://resolver.tudelft.nl/uuid:0deb1a07-6b09-47e5-970a-b192eaea9591.

Council of Science Editors:

Hulsebos M(. Outlier detection in multivariate time series: Exploiting reconstructions from random projections. [Masters Thesis]. Delft University of Technology; 2018. Available from: http://resolver.tudelft.nl/uuid:0deb1a07-6b09-47e5-970a-b192eaea9591


Delft University of Technology

27. van Dorth, Matthijs (author). Probabilistic Models for Personalized Faceted Search.

Degree: 2017, Delft University of Technology

Pattern Recognition & Bioinformatics Advisors/Committee Members: Reinders, Marcel (mentor), Loog, Marco (mentor), Liem, Cynthia (mentor), Kooij, Julian (mentor), Delft University of Technology (degree granting institution).

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

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

APA (6th Edition):

van Dorth, M. (. (2017). Probabilistic Models for Personalized Faceted Search. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:71486f25-5e91-4968-9a37-14907fee6481

Chicago Manual of Style (16th Edition):

van Dorth, Matthijs (author). “Probabilistic Models for Personalized Faceted Search.” 2017. Masters Thesis, Delft University of Technology. Accessed February 27, 2021. http://resolver.tudelft.nl/uuid:71486f25-5e91-4968-9a37-14907fee6481.

MLA Handbook (7th Edition):

van Dorth, Matthijs (author). “Probabilistic Models for Personalized Faceted Search.” 2017. Web. 27 Feb 2021.

Vancouver:

van Dorth M(. Probabilistic Models for Personalized Faceted Search. [Internet] [Masters thesis]. Delft University of Technology; 2017. [cited 2021 Feb 27]. Available from: http://resolver.tudelft.nl/uuid:71486f25-5e91-4968-9a37-14907fee6481.

Council of Science Editors:

van Dorth M(. Probabilistic Models for Personalized Faceted Search. [Masters Thesis]. Delft University of Technology; 2017. Available from: http://resolver.tudelft.nl/uuid:71486f25-5e91-4968-9a37-14907fee6481

.