Night vision with unmanned surface vehicle (USV)
Night vision technologies are implemented in Unmanned Surface Vehicles (USV) mainly for detection, recognition identification. Night vision technologies are Image Intensification, Active Illumination and Thermal Imaging. In this Final Year Project (FYP), this report focuses on my research on types...
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2021
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sg-ntu-dr.10356-1498212023-07-07T18:27:40Z Night vision with unmanned surface vehicle (USV) Ang, Claryl Hui Ern Wang Han School of Electrical and Electronic Engineering HW@ntu.edu.sg Engineering::Electrical and electronic engineering Night vision technologies are implemented in Unmanned Surface Vehicles (USV) mainly for detection, recognition identification. Night vision technologies are Image Intensification, Active Illumination and Thermal Imaging. In this Final Year Project (FYP), this report focuses on my research on types of cameras that accept low lighting conditions. Besides that, this research also involves sourcing code on a deep learning method for transferring night-time images to daytime images. Besides that, this research also includes object detection algorithms. The source code for transferring night-time to daytime images uses ToDayGan, a deep learning method. The types of object detection algorithms are Histogram of oriented gradients(HOG), Convolutional Neural Networks (CNNs) and You Only Look Once (YOLO). Bachelor of Engineering (Electrical and Electronic Engineering) 2021-06-09T06:01:22Z 2021-06-09T06:01:22Z 2021 Final Year Project (FYP) Ang, C. H. E. (2021). Night vision with unmanned surface vehicle (USV). Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/149821 https://hdl.handle.net/10356/149821 en A1151-201 application/pdf Nanyang Technological University |
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Engineering::Electrical and electronic engineering Ang, Claryl Hui Ern Night vision with unmanned surface vehicle (USV) |
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Night vision technologies are implemented in Unmanned Surface Vehicles (USV) mainly for detection, recognition identification. Night vision technologies are Image Intensification, Active Illumination and Thermal Imaging. In this Final Year Project (FYP), this report focuses on my research on types of cameras that accept low lighting conditions. Besides that, this research also involves sourcing code on a deep learning method for transferring night-time images to daytime images. Besides that, this research also includes object detection algorithms. The source code for transferring night-time to daytime images uses ToDayGan, a deep learning method. The types of object detection algorithms are Histogram of oriented gradients(HOG), Convolutional Neural Networks (CNNs) and You Only Look Once (YOLO). |
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Wang Han |
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Wang Han Ang, Claryl Hui Ern |
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Final Year Project |
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Ang, Claryl Hui Ern |
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Ang, Claryl Hui Ern |
title |
Night vision with unmanned surface vehicle (USV) |
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Night vision with unmanned surface vehicle (USV) |
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Night vision with unmanned surface vehicle (USV) |
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Night vision with unmanned surface vehicle (USV) |
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Night vision with unmanned surface vehicle (USV) |
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night vision with unmanned surface vehicle (usv) |
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Nanyang Technological University |
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2021 |
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https://hdl.handle.net/10356/149821 |
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