Research on an Intelligent Grading Method for Beef Freshness in Complex Backgrounds Based on the DEVA-ConvNeXt Model

This paper presents a novel DEVA-ConvNeXt model to address challenges in beef freshness grading, including data collection difficulties, complex backgrounds, and model accuracy issues. The Alpha-Background Generation Shift (ABG-Shift) technology enables rapid generation of beef image datasets with c...

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מידע ביבליוגרפי

Principais autores:	Xiuling Yu, Yifu Xu, Chenxiao Qu, Senyue Guo, Shuo Jiang, Linqiang Chen, Yang Zhou
פורמט:	Artigo
שפה:	Inglês
יצא לאור:	MDPI AG 2025-12-01
סדרה:	Foods
נושאים:	feature extraction enhancement beef quality evaluation background replacement dynamic non-local attention mechanism enhanced deep convolutional module
גישה מקוונת:	https://www.mdpi.com/2304-8158/14/24/4178
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