Abstract
By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-A new study on pattern recognition and artificial intelligence is now available. According to news originating from Na njing, People's Republic of China, by NewsRx correspondents, research stated, "T he main challenge for object detection in aerial images is small object detectio n." Funders for this research include National Natural Science Foundation of China. Our news reporters obtained a quote from the research from Nanjing University: " Most existing methods use feature fusion strategies to enhance small object feat ures in shallow layers but ignore the problem of inconsistent small object local region responses between feature layers, namely the semantic gap, which may lea d to underutilization of small object information in multiple feature layers. To lift the above limitations, we propose a scale enhancement module that adaptive ly passes valuable small object features in different feature layers to shallow layers to alleviate the semantic gap problem. In particular, the module includes the novel fine-coarse self-attention mechanism, which captures global contextua l information by performing strong interaction of pixel-level information at the local scale and weak interaction of regionlevel information at the global scal e. In addition, the anchor assignment strategy based on the Intersection over Un ion (IoU) metric is not favorable for small objects as the IoU metric for small objects has a lower tolerance for position deviation compared to large ones."
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