mAPm: multi-scale Attention Pyramid module for Enhanced scale-variation in RLD detection

arXiv:2402.16291v1 Announce Type: new
Abstract: Detecting objects across various scales remains a significant challenge in computer vision, particularly in tasks such as Rice Leaf Disease (RLD) detection, where objects exhibit considerable scale variations. Traditional object detection methods often struggle to address these variations, resulting in missed detections or reduced accuracy. In this study, we propose the multi-scale Attention Pyramid module (mAPm), a novel approach that integrates dilated convolutions into the Feature Pyramid Network (FPN) to enhance multi-scale information ex-traction. Additionally, …

abstract arxiv attention challenge computer computer vision cs.cv detection detection methods disease objects pyramid scale struggle tasks type variation vision