Citation

Teoh, Andrew Beng Jin and Ong, Thian Song and Lim, Kian Ming and Lee, Chin Poo (2024) Guest Editorial: Special issue on advances in representation learning for computer vision. CAAI Transactions on Intelligence Technology, 9 (1). pp. 1-3. ISSN 2468-2322

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Abstract

Deep learning has been a catalyst for a transformative revolution in machine learning and computer vision in the past decade. Within these research domains, methods grounded in deep learning have exhibited exceptional performance across a spectrum of tasks. The success of deep learning methods can be attributed to their capability to derive potent representations from data, integral for a myriad of downstream applications. These representations encapsulate the intrinsic structure, features, or latent variables characterising the underlying statistics of visual data. Despite these achievements, the challenge persists in effectively conducting representation learning of visual data with deep models, particularly when confronted with vast and noisy datasets. This special issue is a dedicated platform for researchers worldwide to disseminate their latest, high-quality articles, aiming to enhance readers' comprehension of the principles, limitations, and diverse applications of representation learning in computer vision.

Item Type:	Article
Uncontrolled Keywords:	Machine learning and computer vision
Subjects:	Q Science > QA Mathematics > QA71-90 Instruments and machines > QA75.5-76.95 Electronic computers. Computer science
Divisions:	Faculty of Information Science and Technology (FIST)
Depositing User:	Ms Nurul Iqtiani Ahmad
Date Deposited:	04 Mar 2024 02:08
Last Modified:	04 Mar 2024 02:08
URII:	http://shdl.mmu.edu.my/id/eprint/12151

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