June 17, 2024, 4:46 a.m. | Mujadded Al Rabbani Alif, Muhammad Hussain

cs.CV updates on arXiv.org arxiv.org

arXiv:2406.10139v1 Announce Type: new
Abstract: This survey investigates the transformative potential of various YOLO variants, from YOLOv1 to the state-of-the-art YOLOv10, in the context of agricultural advancements. The primary objective is to elucidate how these cutting-edge object detection models can re-energise and optimize diverse aspects of agriculture, ranging from crop monitoring to livestock management. It aims to achieve key objectives, including the identification of contemporary challenges in agriculture, a detailed assessment of YOLO's incremental advancements, and an exploration of its …

abstract application art arxiv context cs.cv detection diverse domain edge object potential review state survey type variants yolo yolov10

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