Optoelectronic memristive devices for optical reservoir computing
The current frame-based cameras employ various components such as sensors, signal converters, memory, and processors to analyze extensive frame-by-frame image sequences for motion recognition and prediction. This produces extensive redundant image data that cause the current machine vision system to...
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2024
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sg-ntu-dr.10356-1770662024-05-24T15:44:35Z Optoelectronic memristive devices for optical reservoir computing Toh, Sio Huan Ang Diing Shenp School of Electrical and Electronic Engineering EDSAng@ntu.edu.sg Engineering The current frame-based cameras employ various components such as sensors, signal converters, memory, and processors to analyze extensive frame-by-frame image sequences for motion recognition and prediction. This produces extensive redundant image data that cause the current machine vision system to face challenges related to high latency and power consumption. While addressing these concerns, it sparks the growing interest in creating cameras that emulate the functionalities of the human retina that is designed to solely detect and encode alterations in the visual scene, akin to its biological counterpart. Through the use of Reservoir Computing we are able to reduce the time taken to process data. By using the Physical Reservoir Computing using the physical dynamics of physical object to replace the reservoir. Bachelor's degree 2024-05-23T12:17:04Z 2024-05-23T12:17:04Z 2023 Final Year Project (FYP) Toh, S. H. (2023). Optoelectronic memristive devices for optical reservoir computing. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/177066 https://hdl.handle.net/10356/177066 en application/pdf Nanyang Technological University |
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The current frame-based cameras employ various components such as sensors, signal converters, memory, and processors to analyze extensive frame-by-frame image sequences for motion recognition and prediction. This produces extensive redundant image data that cause the current machine vision system to face challenges related to high latency and power consumption. While addressing these concerns, it sparks the growing interest in creating cameras that emulate the functionalities of the human retina that is designed to solely detect and encode alterations in the visual scene, akin to its biological counterpart. Through the use of Reservoir Computing we are able to reduce the time taken to process data. By using the Physical Reservoir Computing using the physical dynamics of physical object to replace the reservoir. |
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Ang Diing Shenp |
author_facet |
Ang Diing Shenp Toh, Sio Huan |
format |
Final Year Project |
author |
Toh, Sio Huan |
author_sort |
Toh, Sio Huan |
title |
Optoelectronic memristive devices for optical reservoir computing |
title_short |
Optoelectronic memristive devices for optical reservoir computing |
title_full |
Optoelectronic memristive devices for optical reservoir computing |
title_fullStr |
Optoelectronic memristive devices for optical reservoir computing |
title_full_unstemmed |
Optoelectronic memristive devices for optical reservoir computing |
title_sort |
optoelectronic memristive devices for optical reservoir computing |
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Nanyang Technological University |
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2024 |
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https://hdl.handle.net/10356/177066 |
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