Deep learning for overlapping objects detection with noise: a bibliometric analysis

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Deep learning for overlapping objects detection with noise: a bibliometric analysis

This study conducts a bibliometric analysis to investigate the utilization of deep learning for detecting overlapping objects in noisy environments. Despite the advancements in deep learning, accurately detecting overlapping objects amidst noise remains a significant challenge. Relevant publications...

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Bibliographic Details
Main Authors:	Hashim Rosli, Rozniza Ali, Muhamad Suzuri Hitam, Ashanira Mat Deris
Format:	Article
Language:	English
Published:	Penerbit Universiti Kebangsaan Malaysia 2024
Online Access:	http://journalarticle.ukm.my/25040/ http://journalarticle.ukm.my/25040/1/232%20%E2%80%93%20252.pdf

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