Trained Improved-YOLOv7 Models' Weights for weed detection

Published: 31 March 2026| Version 1 | DOI: 10.17632/c7r4w7sttr.1
Contributor:
Anindita Das

Description

best_yolov7.pt This file contains the trained weights of the baseline YOLOv7 model for weed and cotton detection from UAV imagery, representing the best-performing checkpoint based on mAP@0.5 evaluation. best_yolov7-cbam.pt This file contains the trained weights of the YOLOv7-CBAM model, which integrates attention mechanisms to enhance feature representation for improved weed detection in UAV imagery. best_yolov7-bifpn.pt This file contains the trained weights of the YOLOv7-BiFPN model, which incorporates enhanced multi-scale feature fusion to improve detection across varying object sizes in agricultural scenes. best_cb-yolov7.pt This file contains the trained weights of the proposed CB-YOLOv7 model, combining CBAM and BiFPN to achieve improved and more balanced weed and cotton detection performance.

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Computer Vision, YOLOv7

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