YOLOv1 to YOLOv10: A complete overview of YOLO variants and their utility within the agricultural area
Authors: Mujadded Al Rabbani Alif, Muhammad Hussain
Summary: This survey investigates the transformative potential of varied YOLO variants, from YOLOv1 to the state-of-the-art YOLOv10, within the context of agricultural developments. The first goal is to elucidate how these cutting-edge object detection fashions can re-energise and optimize various elements of agriculture, starting from crop monitoring to livestock administration. It goals to attain key targets, together with the identification of up to date challenges in agriculture, an in depth evaluation of YOLO’s incremental developments, and an exploration of its particular purposes in agriculture. This is without doubt one of the first surveys to incorporate the newest YOLOv10, providing a contemporary perspective on its implications for precision farming and sustainable agricultural practices within the period of Synthetic Intelligence and automation. Additional, the survey undertakes a important evaluation of YOLO’s efficiency, synthesizes present analysis, and initiatives future tendencies. By scrutinizing the distinctive capabilities packed in YOLO variants and their real-world purposes, this survey supplies useful insights into the evolving relationship between YOLO variants and agriculture. The findings contribute in direction of a nuanced understanding of the potential for precision farming and sustainable agricultural practices, marking a major step ahead within the integration of superior object detection applied sciences throughout the agricultural sector