deep-residual-learning-for-image-recognition-2023-002

Kaiming He, Xiangyu Zhang, Shaoqing Ren, Jian Sun

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deep-residual-learning-for-image-recognition-2023-002

Kaiming He, Xiangyu Zhang, Shaoqing Ren, Jian SunUFTAN UNIVERSITYComputer Engineering2023

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This record links to the ResNet paper, which presents residual learning as a method for training very deep neural networks. It is suitable for testing external PDF access, computer vision metadata, long author lists, and technical abstracts in an institutional repository.

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Author: Kaiming He, Xiangyu Zhang, Shaoqing Ren, Jian Sun
Supervisor: Prof. Fatima S. Bello
Faculty: Engineering
Department: Computer Engineering
Document type: Final Year Project
Year: 2023
Keywords: residual networks, image recognition, convolutional neural networks, computer vision, deep learning
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License: all_rights_reserved

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Auto-generated from the record metadata: authors, journal title, DOI, volume, issue/serial, pages and publication date. Review before final academic use.

Kaiming He, Xiangyu Zhang, Shaoqing Ren, Jian Sun (2026). deep-residual-learning-for-image-recognition-2023-002 [Final Year Project]. UFTAN UNIVERSITY. https://inrepscholar.com/uftan-university/projects/941

Source fields used: Kaiming He, Xiangyu Zhang, Shaoqing Ren, Jian Sun

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deep-residual-learning-for-image-recognition-2023-002

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