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You searched for +publisher:"Delft University of Technology" +contributor:("Kooij, Julian"). Showing records 1 – 23 of 23 total matches.

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Delft University of Technology

1. Ammerlaan, Jelle (author). Traffic Gesture Classification for Intelligent Vehicles.

Degree: 2020, Delft University of Technology

 Self-driving vehicles have shown rapid development in recent years and continue to move towards full autonomy. For high or full automation, self-driving vehicles will have… (more)

Subjects/Keywords: Machine Learning; Intelligent Vehicles; Traffic Gestures; Pose estimation; Gesture recognition

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APA (6th Edition):

Ammerlaan, J. (. (2020). Traffic Gesture Classification for Intelligent Vehicles. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:6272db65-b324-40cf-83aa-6d7caf3c7917

Chicago Manual of Style (16th Edition):

Ammerlaan, Jelle (author). “Traffic Gesture Classification for Intelligent Vehicles.” 2020. Masters Thesis, Delft University of Technology. Accessed November 29, 2020. http://resolver.tudelft.nl/uuid:6272db65-b324-40cf-83aa-6d7caf3c7917.

MLA Handbook (7th Edition):

Ammerlaan, Jelle (author). “Traffic Gesture Classification for Intelligent Vehicles.” 2020. Web. 29 Nov 2020.

Vancouver:

Ammerlaan J(. Traffic Gesture Classification for Intelligent Vehicles. [Internet] [Masters thesis]. Delft University of Technology; 2020. [cited 2020 Nov 29]. Available from: http://resolver.tudelft.nl/uuid:6272db65-b324-40cf-83aa-6d7caf3c7917.

Council of Science Editors:

Ammerlaan J(. Traffic Gesture Classification for Intelligent Vehicles. [Masters Thesis]. Delft University of Technology; 2020. Available from: http://resolver.tudelft.nl/uuid:6272db65-b324-40cf-83aa-6d7caf3c7917


Delft University of Technology

2. van Hilten, Arno (author). Segmenting and Detecting Carotid Plaque Components in MRI.

Degree: 2018, Delft University of Technology

Cardiovascular diseases and stroke are currently the leading causes of death worldwide. Atherosclerotic plaque is a mostly asymptotic vascular disease, but rupture of an atherosclerotic… (more)

Subjects/Keywords: Machine Learning; Deep Learning; Multiple Instance Learning; Segmentation; Detection; Plaque Components; Carotid Artery; MRI

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APA (6th Edition):

van Hilten, A. (. (2018). Segmenting and Detecting Carotid Plaque Components in MRI. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:9bce7f8a-8d69-4b48-98c4-fc4e6600b63d

Chicago Manual of Style (16th Edition):

van Hilten, Arno (author). “Segmenting and Detecting Carotid Plaque Components in MRI.” 2018. Masters Thesis, Delft University of Technology. Accessed November 29, 2020. http://resolver.tudelft.nl/uuid:9bce7f8a-8d69-4b48-98c4-fc4e6600b63d.

MLA Handbook (7th Edition):

van Hilten, Arno (author). “Segmenting and Detecting Carotid Plaque Components in MRI.” 2018. Web. 29 Nov 2020.

Vancouver:

van Hilten A(. Segmenting and Detecting Carotid Plaque Components in MRI. [Internet] [Masters thesis]. Delft University of Technology; 2018. [cited 2020 Nov 29]. Available from: http://resolver.tudelft.nl/uuid:9bce7f8a-8d69-4b48-98c4-fc4e6600b63d.

Council of Science Editors:

van Hilten A(. Segmenting and Detecting Carotid Plaque Components in MRI. [Masters Thesis]. Delft University of Technology; 2018. Available from: http://resolver.tudelft.nl/uuid:9bce7f8a-8d69-4b48-98c4-fc4e6600b63d


Delft University of Technology

3. Hafner, Frank (author). Cross-Modal Re-identification of Persons between RGB and Depth.

Degree: 2018, Delft University of Technology

 Cross-modal person re-identification is the task to re-identify a person which was sensedin a first modality, like in visible light (RGB), in a second modality,… (more)

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APA (6th Edition):

Hafner, F. (. (2018). Cross-Modal Re-identification of Persons between RGB and Depth. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:6797b0e2-5a20-444f-8d32-a73581e00ff5

Chicago Manual of Style (16th Edition):

Hafner, Frank (author). “Cross-Modal Re-identification of Persons between RGB and Depth.” 2018. Masters Thesis, Delft University of Technology. Accessed November 29, 2020. http://resolver.tudelft.nl/uuid:6797b0e2-5a20-444f-8d32-a73581e00ff5.

MLA Handbook (7th Edition):

Hafner, Frank (author). “Cross-Modal Re-identification of Persons between RGB and Depth.” 2018. Web. 29 Nov 2020.

Vancouver:

Hafner F(. Cross-Modal Re-identification of Persons between RGB and Depth. [Internet] [Masters thesis]. Delft University of Technology; 2018. [cited 2020 Nov 29]. Available from: http://resolver.tudelft.nl/uuid:6797b0e2-5a20-444f-8d32-a73581e00ff5.

Council of Science Editors:

Hafner F(. Cross-Modal Re-identification of Persons between RGB and Depth. [Masters Thesis]. Delft University of Technology; 2018. Available from: http://resolver.tudelft.nl/uuid:6797b0e2-5a20-444f-8d32-a73581e00ff5


Delft University of Technology

4. van Schouwenburg, Sietse (author). Evaluating SLAM in an urban dynamic environment.

Degree: 2019, Delft University of Technology

 Simultaneous Localization And Mapping (SLAM) algorithms provide accurate localization for autonomous vehicles and provide essential information for the path planning module. However, SLAM algorithms as-… (more)

Subjects/Keywords: SLAM; simulation; computer vision; simulataneous localization and mapping; localization; mapping; visual SLAM; ORB SLAM; CARLA

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APA (6th Edition):

van Schouwenburg, S. (. (2019). Evaluating SLAM in an urban dynamic environment. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:af041e54-7660-4fb1-b68c-0af3aaf27c52

Chicago Manual of Style (16th Edition):

van Schouwenburg, Sietse (author). “Evaluating SLAM in an urban dynamic environment.” 2019. Masters Thesis, Delft University of Technology. Accessed November 29, 2020. http://resolver.tudelft.nl/uuid:af041e54-7660-4fb1-b68c-0af3aaf27c52.

MLA Handbook (7th Edition):

van Schouwenburg, Sietse (author). “Evaluating SLAM in an urban dynamic environment.” 2019. Web. 29 Nov 2020.

Vancouver:

van Schouwenburg S(. Evaluating SLAM in an urban dynamic environment. [Internet] [Masters thesis]. Delft University of Technology; 2019. [cited 2020 Nov 29]. Available from: http://resolver.tudelft.nl/uuid:af041e54-7660-4fb1-b68c-0af3aaf27c52.

Council of Science Editors:

van Schouwenburg S(. Evaluating SLAM in an urban dynamic environment. [Masters Thesis]. Delft University of Technology; 2019. Available from: http://resolver.tudelft.nl/uuid:af041e54-7660-4fb1-b68c-0af3aaf27c52


Delft University of Technology

5. Lee, Seong Hun (author). Stability-based Scale Estimation of Monocular SLAM for Autonomous Quadrotor Navigation.

Degree: 2017, Delft University of Technology

 We propose a novel method to deal with the scale ambiguity in monocular SLAM based on control stability. We analytically show that (1) using unscaled… (more)

Subjects/Keywords: monocular SLAM; autonomous navigation; scale estimation; quadrotor; MAV; visual SLAM

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APA (6th Edition):

Lee, S. H. (. (2017). Stability-based Scale Estimation of Monocular SLAM for Autonomous Quadrotor Navigation. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:015f322f-9d86-4717-b2e2-74cf25bfa70c

Chicago Manual of Style (16th Edition):

Lee, Seong Hun (author). “Stability-based Scale Estimation of Monocular SLAM for Autonomous Quadrotor Navigation.” 2017. Masters Thesis, Delft University of Technology. Accessed November 29, 2020. http://resolver.tudelft.nl/uuid:015f322f-9d86-4717-b2e2-74cf25bfa70c.

MLA Handbook (7th Edition):

Lee, Seong Hun (author). “Stability-based Scale Estimation of Monocular SLAM for Autonomous Quadrotor Navigation.” 2017. Web. 29 Nov 2020.

Vancouver:

Lee SH(. Stability-based Scale Estimation of Monocular SLAM for Autonomous Quadrotor Navigation. [Internet] [Masters thesis]. Delft University of Technology; 2017. [cited 2020 Nov 29]. Available from: http://resolver.tudelft.nl/uuid:015f322f-9d86-4717-b2e2-74cf25bfa70c.

Council of Science Editors:

Lee SH(. Stability-based Scale Estimation of Monocular SLAM for Autonomous Quadrotor Navigation. [Masters Thesis]. Delft University of Technology; 2017. Available from: http://resolver.tudelft.nl/uuid:015f322f-9d86-4717-b2e2-74cf25bfa70c


Delft University of Technology

6. Wang, Ziqi (author). Depth-aware Instance Segmentation with a Discriminative Loss Function.

Degree: 2018, Delft University of Technology

This work explores the possibility of incorporating depth information into a deep neural network to improve accuracy of RGB instance segmentation. The baseline of this… (more)

Subjects/Keywords: Deep Learning; Computer Vision; instance segmentation; Intelligent Vehicles

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APA (6th Edition):

Wang, Z. (. (2018). Depth-aware Instance Segmentation with a Discriminative Loss Function. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:02bd3582-3304-4595-baa6-c6fcca755418

Chicago Manual of Style (16th Edition):

Wang, Ziqi (author). “Depth-aware Instance Segmentation with a Discriminative Loss Function.” 2018. Masters Thesis, Delft University of Technology. Accessed November 29, 2020. http://resolver.tudelft.nl/uuid:02bd3582-3304-4595-baa6-c6fcca755418.

MLA Handbook (7th Edition):

Wang, Ziqi (author). “Depth-aware Instance Segmentation with a Discriminative Loss Function.” 2018. Web. 29 Nov 2020.

Vancouver:

Wang Z(. Depth-aware Instance Segmentation with a Discriminative Loss Function. [Internet] [Masters thesis]. Delft University of Technology; 2018. [cited 2020 Nov 29]. Available from: http://resolver.tudelft.nl/uuid:02bd3582-3304-4595-baa6-c6fcca755418.

Council of Science Editors:

Wang Z(. Depth-aware Instance Segmentation with a Discriminative Loss Function. [Masters Thesis]. Delft University of Technology; 2018. Available from: http://resolver.tudelft.nl/uuid:02bd3582-3304-4595-baa6-c6fcca755418


Delft University of Technology

7. Resink, Tim (author). Vehicle motion prediction for autonomous driving: A deep learning model based on vehicle interaction and road geometry using a semantic map.

Degree: 2019, Delft University of Technology

 To be able to understand the dynamic driving environment, an autonomous vehicle needs to predict the mo- tion of other traffic participants in the driving… (more)

Subjects/Keywords: Autonomous driving; Motion prediction; Deep learning

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APA (6th Edition):

Resink, T. (. (2019). Vehicle motion prediction for autonomous driving: A deep learning model based on vehicle interaction and road geometry using a semantic map. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:bb469461-b879-40fd-abbc-1a6e0233bf1b

Chicago Manual of Style (16th Edition):

Resink, Tim (author). “Vehicle motion prediction for autonomous driving: A deep learning model based on vehicle interaction and road geometry using a semantic map.” 2019. Masters Thesis, Delft University of Technology. Accessed November 29, 2020. http://resolver.tudelft.nl/uuid:bb469461-b879-40fd-abbc-1a6e0233bf1b.

MLA Handbook (7th Edition):

Resink, Tim (author). “Vehicle motion prediction for autonomous driving: A deep learning model based on vehicle interaction and road geometry using a semantic map.” 2019. Web. 29 Nov 2020.

Vancouver:

Resink T(. Vehicle motion prediction for autonomous driving: A deep learning model based on vehicle interaction and road geometry using a semantic map. [Internet] [Masters thesis]. Delft University of Technology; 2019. [cited 2020 Nov 29]. Available from: http://resolver.tudelft.nl/uuid:bb469461-b879-40fd-abbc-1a6e0233bf1b.

Council of Science Editors:

Resink T(. Vehicle motion prediction for autonomous driving: A deep learning model based on vehicle interaction and road geometry using a semantic map. [Masters Thesis]. Delft University of Technology; 2019. Available from: http://resolver.tudelft.nl/uuid:bb469461-b879-40fd-abbc-1a6e0233bf1b


Delft University of Technology

8. Ramsaha, Puranjay (author). Development of vehicle-cyclist interaction model for scenario generation/validation.

Degree: 2018, Delft University of Technology

The number of road accidents is increasing all over the world. When Vulnerable Road Users (VRU) are involved in an accident, they are prone to… (more)

Subjects/Keywords: HMM; interaction; cyclist; Car

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APA (6th Edition):

Ramsaha, P. (. (2018). Development of vehicle-cyclist interaction model for scenario generation/validation. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:3de49bca-cba6-4fb5-8454-e1daec162ec4

Chicago Manual of Style (16th Edition):

Ramsaha, Puranjay (author). “Development of vehicle-cyclist interaction model for scenario generation/validation.” 2018. Masters Thesis, Delft University of Technology. Accessed November 29, 2020. http://resolver.tudelft.nl/uuid:3de49bca-cba6-4fb5-8454-e1daec162ec4.

MLA Handbook (7th Edition):

Ramsaha, Puranjay (author). “Development of vehicle-cyclist interaction model for scenario generation/validation.” 2018. Web. 29 Nov 2020.

Vancouver:

Ramsaha P(. Development of vehicle-cyclist interaction model for scenario generation/validation. [Internet] [Masters thesis]. Delft University of Technology; 2018. [cited 2020 Nov 29]. Available from: http://resolver.tudelft.nl/uuid:3de49bca-cba6-4fb5-8454-e1daec162ec4.

Council of Science Editors:

Ramsaha P(. Development of vehicle-cyclist interaction model for scenario generation/validation. [Masters Thesis]. Delft University of Technology; 2018. Available from: http://resolver.tudelft.nl/uuid:3de49bca-cba6-4fb5-8454-e1daec162ec4


Delft University of Technology

9. van Laar, Patrick (author). Acoustic recognition of motorized vehicles with a moving listener.

Degree: 2019, Delft University of Technology

New measures have to be taken to combat fatalities caused by traffic accidents. Intelligent vehicles have the potential to increase safety, but depend heavily on… (more)

Subjects/Keywords: Acoustic perception; Intelligent Vehicles; Machine Learning

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APA (6th Edition):

van Laar, P. (. (2019). Acoustic recognition of motorized vehicles with a moving listener. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:3e74c3a7-9099-48c0-ab26-afb0fa785629

Chicago Manual of Style (16th Edition):

van Laar, Patrick (author). “Acoustic recognition of motorized vehicles with a moving listener.” 2019. Masters Thesis, Delft University of Technology. Accessed November 29, 2020. http://resolver.tudelft.nl/uuid:3e74c3a7-9099-48c0-ab26-afb0fa785629.

MLA Handbook (7th Edition):

van Laar, Patrick (author). “Acoustic recognition of motorized vehicles with a moving listener.” 2019. Web. 29 Nov 2020.

Vancouver:

van Laar P(. Acoustic recognition of motorized vehicles with a moving listener. [Internet] [Masters thesis]. Delft University of Technology; 2019. [cited 2020 Nov 29]. Available from: http://resolver.tudelft.nl/uuid:3e74c3a7-9099-48c0-ab26-afb0fa785629.

Council of Science Editors:

van Laar P(. Acoustic recognition of motorized vehicles with a moving listener. [Masters Thesis]. Delft University of Technology; 2019. Available from: http://resolver.tudelft.nl/uuid:3e74c3a7-9099-48c0-ab26-afb0fa785629


Delft University of Technology

10. Immerzeel, Ronald (author). Robust Tracking Approach for Dealing with Classification Uncertainty.

Degree: 2018, Delft University of Technology

Every year about 1.25 million people die as a result of road traffic accidents. Besides the traffic on the road increases every day, including the… (more)

Subjects/Keywords: Object tracking; Classification; RCA-CPHD; classification uncertainty; Multiple Model CPHD

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APA (6th Edition):

Immerzeel, R. (. (2018). Robust Tracking Approach for Dealing with Classification Uncertainty. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:abe30b3f-b2f4-4a4e-9b34-fc42159a0e0e

Chicago Manual of Style (16th Edition):

Immerzeel, Ronald (author). “Robust Tracking Approach for Dealing with Classification Uncertainty.” 2018. Masters Thesis, Delft University of Technology. Accessed November 29, 2020. http://resolver.tudelft.nl/uuid:abe30b3f-b2f4-4a4e-9b34-fc42159a0e0e.

MLA Handbook (7th Edition):

Immerzeel, Ronald (author). “Robust Tracking Approach for Dealing with Classification Uncertainty.” 2018. Web. 29 Nov 2020.

Vancouver:

Immerzeel R(. Robust Tracking Approach for Dealing with Classification Uncertainty. [Internet] [Masters thesis]. Delft University of Technology; 2018. [cited 2020 Nov 29]. Available from: http://resolver.tudelft.nl/uuid:abe30b3f-b2f4-4a4e-9b34-fc42159a0e0e.

Council of Science Editors:

Immerzeel R(. Robust Tracking Approach for Dealing with Classification Uncertainty. [Masters Thesis]. Delft University of Technology; 2018. Available from: http://resolver.tudelft.nl/uuid:abe30b3f-b2f4-4a4e-9b34-fc42159a0e0e


Delft University of Technology

11. Zijlmans, Jeroen (author). Improving Monocular SLAM: using Depth Estimating CNN.

Degree: 2018, Delft University of Technology

 To bring down the number of traffic accidents and increase people’s mobility companies, such as Robot Engineering Systems (RES) try to put automated vehicles on… (more)

Subjects/Keywords: monocular SLAM; Depth-estimating CNN; ORB-SLAM

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APA (6th Edition):

Zijlmans, J. (. (2018). Improving Monocular SLAM: using Depth Estimating CNN. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:af8aad54-e594-4cfe-a2ef-a3b3f302a4d5

Chicago Manual of Style (16th Edition):

Zijlmans, Jeroen (author). “Improving Monocular SLAM: using Depth Estimating CNN.” 2018. Masters Thesis, Delft University of Technology. Accessed November 29, 2020. http://resolver.tudelft.nl/uuid:af8aad54-e594-4cfe-a2ef-a3b3f302a4d5.

MLA Handbook (7th Edition):

Zijlmans, Jeroen (author). “Improving Monocular SLAM: using Depth Estimating CNN.” 2018. Web. 29 Nov 2020.

Vancouver:

Zijlmans J(. Improving Monocular SLAM: using Depth Estimating CNN. [Internet] [Masters thesis]. Delft University of Technology; 2018. [cited 2020 Nov 29]. Available from: http://resolver.tudelft.nl/uuid:af8aad54-e594-4cfe-a2ef-a3b3f302a4d5.

Council of Science Editors:

Zijlmans J(. Improving Monocular SLAM: using Depth Estimating CNN. [Masters Thesis]. Delft University of Technology; 2018. Available from: http://resolver.tudelft.nl/uuid:af8aad54-e594-4cfe-a2ef-a3b3f302a4d5


Delft University of Technology

12. Wymenga, Jan (author). Weather Condition Estimation in Automated Vehicles.

Degree: 2018, Delft University of Technology

This work presents a multi-sensor approach for weather condition estimation in automated vehicles. Using combined data from weather sensors (barometer, hygrometer, etc) and an in-vehicle… (more)

Subjects/Keywords: weather types; machine learning; intelligent vehicles; vision; driving; weather

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APA (6th Edition):

Wymenga, J. (. (2018). Weather Condition Estimation in Automated Vehicles. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:421b3c6d-b85e-4876-a963-4094b35dea94

Chicago Manual of Style (16th Edition):

Wymenga, Jan (author). “Weather Condition Estimation in Automated Vehicles.” 2018. Masters Thesis, Delft University of Technology. Accessed November 29, 2020. http://resolver.tudelft.nl/uuid:421b3c6d-b85e-4876-a963-4094b35dea94.

MLA Handbook (7th Edition):

Wymenga, Jan (author). “Weather Condition Estimation in Automated Vehicles.” 2018. Web. 29 Nov 2020.

Vancouver:

Wymenga J(. Weather Condition Estimation in Automated Vehicles. [Internet] [Masters thesis]. Delft University of Technology; 2018. [cited 2020 Nov 29]. Available from: http://resolver.tudelft.nl/uuid:421b3c6d-b85e-4876-a963-4094b35dea94.

Council of Science Editors:

Wymenga J(. Weather Condition Estimation in Automated Vehicles. [Masters Thesis]. Delft University of Technology; 2018. Available from: http://resolver.tudelft.nl/uuid:421b3c6d-b85e-4876-a963-4094b35dea94


Delft University of Technology

13. Raipuria, Geetank (author). Vehicle Trajectory Prediction Using Road Structure.

Degree: 2017, Delft University of Technology

 An autonomous vehicle should be able to operate amidst numerous other human-driven vehicles, each driving on its own trajectory. To safely navigate in such a… (more)

Subjects/Keywords: Trajectory Prediction; Road Structure; Context; Long-term; Recurrent Neural Network; Interactive Multiple Model Filter; Path Planning; Automated driving

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APA (6th Edition):

Raipuria, G. (. (2017). Vehicle Trajectory Prediction Using Road Structure. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:6cae1b47-f44e-4b74-8bfd-9098ce843e68

Chicago Manual of Style (16th Edition):

Raipuria, Geetank (author). “Vehicle Trajectory Prediction Using Road Structure.” 2017. Masters Thesis, Delft University of Technology. Accessed November 29, 2020. http://resolver.tudelft.nl/uuid:6cae1b47-f44e-4b74-8bfd-9098ce843e68.

MLA Handbook (7th Edition):

Raipuria, Geetank (author). “Vehicle Trajectory Prediction Using Road Structure.” 2017. Web. 29 Nov 2020.

Vancouver:

Raipuria G(. Vehicle Trajectory Prediction Using Road Structure. [Internet] [Masters thesis]. Delft University of Technology; 2017. [cited 2020 Nov 29]. Available from: http://resolver.tudelft.nl/uuid:6cae1b47-f44e-4b74-8bfd-9098ce843e68.

Council of Science Editors:

Raipuria G(. Vehicle Trajectory Prediction Using Road Structure. [Masters Thesis]. Delft University of Technology; 2017. Available from: http://resolver.tudelft.nl/uuid:6cae1b47-f44e-4b74-8bfd-9098ce843e68


Delft University of Technology

14. Bormans, Robbert (author). Deep segmentation of the drivable path of a self-driving vehicle using external data: Influence of domain shift factors and depth information.

Degree: 2018, Delft University of Technology

 Robot Care Systems (RCS) is involved in the development of the WEpod, an autonomous shuttle which can transfer up to six people. Based on a… (more)

Subjects/Keywords: Drivable Path; Domain Adaptation; Convolutional Neural Networks; Top View Transformation; Self-driving car

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APA (6th Edition):

Bormans, R. (. (2018). Deep segmentation of the drivable path of a self-driving vehicle using external data: Influence of domain shift factors and depth information. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:f3a713cc-f4f8-4e54-a8cb-136ce18ef849

Chicago Manual of Style (16th Edition):

Bormans, Robbert (author). “Deep segmentation of the drivable path of a self-driving vehicle using external data: Influence of domain shift factors and depth information.” 2018. Masters Thesis, Delft University of Technology. Accessed November 29, 2020. http://resolver.tudelft.nl/uuid:f3a713cc-f4f8-4e54-a8cb-136ce18ef849.

MLA Handbook (7th Edition):

Bormans, Robbert (author). “Deep segmentation of the drivable path of a self-driving vehicle using external data: Influence of domain shift factors and depth information.” 2018. Web. 29 Nov 2020.

Vancouver:

Bormans R(. Deep segmentation of the drivable path of a self-driving vehicle using external data: Influence of domain shift factors and depth information. [Internet] [Masters thesis]. Delft University of Technology; 2018. [cited 2020 Nov 29]. Available from: http://resolver.tudelft.nl/uuid:f3a713cc-f4f8-4e54-a8cb-136ce18ef849.

Council of Science Editors:

Bormans R(. Deep segmentation of the drivable path of a self-driving vehicle using external data: Influence of domain shift factors and depth information. [Masters Thesis]. Delft University of Technology; 2018. Available from: http://resolver.tudelft.nl/uuid:f3a713cc-f4f8-4e54-a8cb-136ce18ef849


Delft University of Technology

15. Bos, Evert (author). Including traffic light recognition in general object detection with YOLOv2.

Degree: 2019, Delft University of Technology

With an in vehicle camera many different things can be done that are essential for ADAS or autonomous driving mode in a vehicle. First, it… (more)

Subjects/Keywords: Traffic Light recognition; machine learning; YOLO; object detection; COCO; LISA

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

APA (6th Edition):

Bos, E. (. (2019). Including traffic light recognition in general object detection with YOLOv2. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:09f32632-04eb-4907-9100-766590dc2d03

Chicago Manual of Style (16th Edition):

Bos, Evert (author). “Including traffic light recognition in general object detection with YOLOv2.” 2019. Masters Thesis, Delft University of Technology. Accessed November 29, 2020. http://resolver.tudelft.nl/uuid:09f32632-04eb-4907-9100-766590dc2d03.

MLA Handbook (7th Edition):

Bos, Evert (author). “Including traffic light recognition in general object detection with YOLOv2.” 2019. Web. 29 Nov 2020.

Vancouver:

Bos E(. Including traffic light recognition in general object detection with YOLOv2. [Internet] [Masters thesis]. Delft University of Technology; 2019. [cited 2020 Nov 29]. Available from: http://resolver.tudelft.nl/uuid:09f32632-04eb-4907-9100-766590dc2d03.

Council of Science Editors:

Bos E(. Including traffic light recognition in general object detection with YOLOv2. [Masters Thesis]. Delft University of Technology; 2019. Available from: http://resolver.tudelft.nl/uuid:09f32632-04eb-4907-9100-766590dc2d03


Delft University of Technology

16. Glastra, Thom (author). Enabling GLOSA for on-street operating traffic light controllers.

Degree: 2020, Delft University of Technology

 The bottleneck of the maximum road volume in urban areas is the maximum capacity of the traffic flow on the intersection, which is coordinated with… (more)

Subjects/Keywords: Traffic flow; Traffic light controller; TLC; Predictive controller; Prediction model; Decentralized control; Model predictive control; green light optimal speed advise; GLOSA

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

APA (6th Edition):

Glastra, T. (. (2020). Enabling GLOSA for on-street operating traffic light controllers. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:63a21739-a200-4375-8f19-641352e504b2

Chicago Manual of Style (16th Edition):

Glastra, Thom (author). “Enabling GLOSA for on-street operating traffic light controllers.” 2020. Masters Thesis, Delft University of Technology. Accessed November 29, 2020. http://resolver.tudelft.nl/uuid:63a21739-a200-4375-8f19-641352e504b2.

MLA Handbook (7th Edition):

Glastra, Thom (author). “Enabling GLOSA for on-street operating traffic light controllers.” 2020. Web. 29 Nov 2020.

Vancouver:

Glastra T(. Enabling GLOSA for on-street operating traffic light controllers. [Internet] [Masters thesis]. Delft University of Technology; 2020. [cited 2020 Nov 29]. Available from: http://resolver.tudelft.nl/uuid:63a21739-a200-4375-8f19-641352e504b2.

Council of Science Editors:

Glastra T(. Enabling GLOSA for on-street operating traffic light controllers. [Masters Thesis]. Delft University of Technology; 2020. Available from: http://resolver.tudelft.nl/uuid:63a21739-a200-4375-8f19-641352e504b2


Delft University of Technology

17. 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

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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 November 29, 2020. 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. 29 Nov 2020.

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 2020 Nov 29]. 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

18. Wang, Johnny (author). Grey Matter Age Prediction as a Biomarker for Risk of Dementia: A Population-based Study.

Degree: 2019, Delft University of Technology

The gap between predicted brain age and chronological age could serve as biomarker for early-stage neurodegeneration and as potentially as a risk indicator for dementia.… (more)

Subjects/Keywords: Deep Learning; Age prediction; Dementia; Biomarker; Brain; Magnetic Resonance Imaging; Voxel-based morphometry; Survival analysis

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

APA (6th Edition):

Wang, J. (. (2019). Grey Matter Age Prediction as a Biomarker for Risk of Dementia: A Population-based Study. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:1fda41dd-745e-4d4d-8098-d9212148153a

Chicago Manual of Style (16th Edition):

Wang, Johnny (author). “Grey Matter Age Prediction as a Biomarker for Risk of Dementia: A Population-based Study.” 2019. Masters Thesis, Delft University of Technology. Accessed November 29, 2020. http://resolver.tudelft.nl/uuid:1fda41dd-745e-4d4d-8098-d9212148153a.

MLA Handbook (7th Edition):

Wang, Johnny (author). “Grey Matter Age Prediction as a Biomarker for Risk of Dementia: A Population-based Study.” 2019. Web. 29 Nov 2020.

Vancouver:

Wang J(. Grey Matter Age Prediction as a Biomarker for Risk of Dementia: A Population-based Study. [Internet] [Masters thesis]. Delft University of Technology; 2019. [cited 2020 Nov 29]. Available from: http://resolver.tudelft.nl/uuid:1fda41dd-745e-4d4d-8098-d9212148153a.

Council of Science Editors:

Wang J(. Grey Matter Age Prediction as a Biomarker for Risk of Dementia: A Population-based Study. [Masters Thesis]. Delft University of Technology; 2019. Available from: http://resolver.tudelft.nl/uuid:1fda41dd-745e-4d4d-8098-d9212148153a


Delft University of Technology

19. GAO, Xinyu (author). Sensor Data Fusion of Lidar and Camera for Road User Detection.

Degree: 2018, Delft University of Technology

Object detection is one of the most important research topics in autonomous vehicles. The detection systems of autonomous vehicles nowadays are mostly image-based ones which… (more)

Subjects/Keywords: 3D object detection; Lidar; Camera; sensor fusion

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

APA (6th Edition):

GAO, X. (. (2018). Sensor Data Fusion of Lidar and Camera for Road User Detection. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:e310da67-98b2-4288-b656-15da36e3f12a

Chicago Manual of Style (16th Edition):

GAO, Xinyu (author). “Sensor Data Fusion of Lidar and Camera for Road User Detection.” 2018. Masters Thesis, Delft University of Technology. Accessed November 29, 2020. http://resolver.tudelft.nl/uuid:e310da67-98b2-4288-b656-15da36e3f12a.

MLA Handbook (7th Edition):

GAO, Xinyu (author). “Sensor Data Fusion of Lidar and Camera for Road User Detection.” 2018. Web. 29 Nov 2020.

Vancouver:

GAO X(. Sensor Data Fusion of Lidar and Camera for Road User Detection. [Internet] [Masters thesis]. Delft University of Technology; 2018. [cited 2020 Nov 29]. Available from: http://resolver.tudelft.nl/uuid:e310da67-98b2-4288-b656-15da36e3f12a.

Council of Science Editors:

GAO X(. Sensor Data Fusion of Lidar and Camera for Road User Detection. [Masters Thesis]. Delft University of Technology; 2018. Available from: http://resolver.tudelft.nl/uuid:e310da67-98b2-4288-b656-15da36e3f12a


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

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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 November 29, 2020. 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. 29 Nov 2020.

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 2020 Nov 29]. 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. Yu, Rui (author). Lane Change Intention Recognition Models Using Hidden Markov Models and Relevance Vector Machines.

Degree: 2019, Delft University of Technology

The development of intelligent vehicle and autonomous driving asked a higher requirement of ADAS on its functionality. Currently, ADAS systems are able to detect and… (more)

Subjects/Keywords: Intention Recognition; Lane Change; Hidden Markov Model; Relevance Vector Machine

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

APA (6th Edition):

Yu, R. (. (2019). Lane Change Intention Recognition Models Using Hidden Markov Models and Relevance Vector Machines. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:a4ea860a-46d1-498b-9742-152e92f55ace

Chicago Manual of Style (16th Edition):

Yu, Rui (author). “Lane Change Intention Recognition Models Using Hidden Markov Models and Relevance Vector Machines.” 2019. Masters Thesis, Delft University of Technology. Accessed November 29, 2020. http://resolver.tudelft.nl/uuid:a4ea860a-46d1-498b-9742-152e92f55ace.

MLA Handbook (7th Edition):

Yu, Rui (author). “Lane Change Intention Recognition Models Using Hidden Markov Models and Relevance Vector Machines.” 2019. Web. 29 Nov 2020.

Vancouver:

Yu R(. Lane Change Intention Recognition Models Using Hidden Markov Models and Relevance Vector Machines. [Internet] [Masters thesis]. Delft University of Technology; 2019. [cited 2020 Nov 29]. Available from: http://resolver.tudelft.nl/uuid:a4ea860a-46d1-498b-9742-152e92f55ace.

Council of Science Editors:

Yu R(. Lane Change Intention Recognition Models Using Hidden Markov Models and Relevance Vector Machines. [Masters Thesis]. Delft University of Technology; 2019. Available from: http://resolver.tudelft.nl/uuid:a4ea860a-46d1-498b-9742-152e92f55ace


Delft University of Technology

22. Jargot, Dominik (author). Deep End-to-end Network for 3D Object Detection in the Context of Autonomous Driving.

Degree: 2019, Delft University of Technology

Nowadays, autonomous driving is a trending topic in the automotive field. One of the most crucial challenges of autonomous driving research is environment perception. Currently,… (more)

Subjects/Keywords: 3D object detection; Thesis; Intelligent Vehicles; Deep Learning; Machine Learning; Camera; Lidar

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

APA (6th Edition):

Jargot, D. (. (2019). Deep End-to-end Network for 3D Object Detection in the Context of Autonomous Driving. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:6389d77c-007d-455f-8e84-10a4f9b57a9d

Chicago Manual of Style (16th Edition):

Jargot, Dominik (author). “Deep End-to-end Network for 3D Object Detection in the Context of Autonomous Driving.” 2019. Masters Thesis, Delft University of Technology. Accessed November 29, 2020. http://resolver.tudelft.nl/uuid:6389d77c-007d-455f-8e84-10a4f9b57a9d.

MLA Handbook (7th Edition):

Jargot, Dominik (author). “Deep End-to-end Network for 3D Object Detection in the Context of Autonomous Driving.” 2019. Web. 29 Nov 2020.

Vancouver:

Jargot D(. Deep End-to-end Network for 3D Object Detection in the Context of Autonomous Driving. [Internet] [Masters thesis]. Delft University of Technology; 2019. [cited 2020 Nov 29]. Available from: http://resolver.tudelft.nl/uuid:6389d77c-007d-455f-8e84-10a4f9b57a9d.

Council of Science Editors:

Jargot D(. Deep End-to-end Network for 3D Object Detection in the Context of Autonomous Driving. [Masters Thesis]. Delft University of Technology; 2019. Available from: http://resolver.tudelft.nl/uuid:6389d77c-007d-455f-8e84-10a4f9b57a9d


Delft University of Technology

23. 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).

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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 November 29, 2020. 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. 29 Nov 2020.

Vancouver:

van Dorth M(. Probabilistic Models for Personalized Faceted Search. [Internet] [Masters thesis]. Delft University of Technology; 2017. [cited 2020 Nov 29]. 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

.