TeaPickingNet: Towards Robust Recognition of Fine-Grained Picking Actions in Tea Gardens Using an Attention-Enhanced Framework

With the emergence of smart agriculture, precise behavior recognition in tea gardens has become increasingly important for operational monitoring and intelligent management. However, existing behavior detection systems face limitations when deployed in real-world agricultural environments, particula...

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Bibliografische gegevens

Hoofdauteurs:	Ru Han, Ye Zheng, Lei Shu, Grzegorz Cielniak
Formaat:	Artigo
Taal:	Inglês
Gepubliceerd in:	MDPI AG 2025-11-01
Reeks:	Agriculture
Onderwerpen:	tea garden picking behavior recognition YOLOv5 Faster R-CNN deep learning attention mechanism
Online toegang:	https://www.mdpi.com/2077-0472/15/23/2441
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