A color vision approach based on the autoencoder technique and deep neural networks for reconstructing color images under various lighting conditions

This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science, 2022.

Opis bibliograficzny
Główni autorzy:	Faisal, Asm, Ahmad, Ashhab, Tazwar, Asif
Kolejni autorzy:	Alam, Md. Ashraful
Format:	Praca dyplomowa
Język:	English
Wydane:	Brac University 2024
Hasła przedmiotowe:	Autoencoder Image reconstruction Deep neural networks Color vision Neural networks (Computer science)
Dostęp online:	http://hdl.handle.net/10361/23943

id	10361-23943
record_format	dspace
spelling	10361-239432024-08-29T21:03:12Z A color vision approach based on the autoencoder technique and deep neural networks for reconstructing color images under various lighting conditions Faisal, Asm Ahmad, Ashhab Tazwar, Asif Alam, Md. Ashraful Department of Computer Science and Engineering, Brac University Autoencoder Image reconstruction Deep neural networks Color vision Neural networks (Computer science) This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science, 2022. Cataloged from PDF version of thesis. Includes bibliographical references (pages 67-69). We present a color vision system that utilizes deep neural net- works to normalize pictures using the autoencoder algorithm. Image processing, encoding, and decoding are the three essen- tial processes in the proposed paradigm. An effective image processing approach is utilized to downsize acquired pictures into a finite image resolution equal to the number of input nodes of an autoencoder in the image processing section. En- coding and decoding procedures are included in the Autoen- coder. Second, a deep neural network-based encoding process creates a code for an input picture, and a deep neural network- based decoding process reconstructs the original image from the encoder’s code. Convolutional neural networks were used to train the autoencoder with over ten thousand scaled pic- ture datasets. The results of the experiments showed that the suggested model can recreate predetermined normalized pic- tures from original photographs, which may be employed in sophisticated color vision applications. Asm Faisal Ashhab Ahmad Asif Tazwar B.Sc. in Computer Science 2024-08-29T05:13:42Z 2024-08-29T05:13:42Z 2022 2022-01 Thesis ID 16201049 ID 17301162 ID 21301732 http://hdl.handle.net/10361/23943 en Brac University theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. 69 pages application/pdf Brac University
institution	Brac University
collection	Institutional Repository
language	English
topic	Autoencoder Image reconstruction Deep neural networks Color vision Neural networks (Computer science)
spellingShingle	Autoencoder Image reconstruction Deep neural networks Color vision Neural networks (Computer science) Faisal, Asm Ahmad, Ashhab Tazwar, Asif A color vision approach based on the autoencoder technique and deep neural networks for reconstructing color images under various lighting conditions
description	This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science, 2022.
author2	Alam, Md. Ashraful
author_facet	Alam, Md. Ashraful Faisal, Asm Ahmad, Ashhab Tazwar, Asif
format	Thesis
author	Faisal, Asm Ahmad, Ashhab Tazwar, Asif
author_sort	Faisal, Asm
title	A color vision approach based on the autoencoder technique and deep neural networks for reconstructing color images under various lighting conditions
title_short	A color vision approach based on the autoencoder technique and deep neural networks for reconstructing color images under various lighting conditions
title_full	A color vision approach based on the autoencoder technique and deep neural networks for reconstructing color images under various lighting conditions
title_fullStr	A color vision approach based on the autoencoder technique and deep neural networks for reconstructing color images under various lighting conditions
title_full_unstemmed	A color vision approach based on the autoencoder technique and deep neural networks for reconstructing color images under various lighting conditions
title_sort	color vision approach based on the autoencoder technique and deep neural networks for reconstructing color images under various lighting conditions
publisher	Brac University
publishDate	2024
url	http://hdl.handle.net/10361/23943
work_keys_str_mv	AT faisalasm acolorvisionapproachbasedontheautoencodertechniqueanddeepneuralnetworksforreconstructingcolorimagesundervariouslightingconditions AT ahmadashhab acolorvisionapproachbasedontheautoencodertechniqueanddeepneuralnetworksforreconstructingcolorimagesundervariouslightingconditions AT tazwarasif acolorvisionapproachbasedontheautoencodertechniqueanddeepneuralnetworksforreconstructingcolorimagesundervariouslightingconditions AT faisalasm colorvisionapproachbasedontheautoencodertechniqueanddeepneuralnetworksforreconstructingcolorimagesundervariouslightingconditions AT ahmadashhab colorvisionapproachbasedontheautoencodertechniqueanddeepneuralnetworksforreconstructingcolorimagesundervariouslightingconditions AT tazwarasif colorvisionapproachbasedontheautoencodertechniqueanddeepneuralnetworksforreconstructingcolorimagesundervariouslightingconditions
_version_	1814308717152174080

A color vision approach based on the autoencoder technique and deep neural networks for reconstructing color images under various lighting conditions

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