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AGSFCOS: Based on attention mechanism and Scale-Equalizing pyramid network of object detection
In order to solve the above problems, Experiments show that our model has a certain improvement in accuracy compared with the current popular detection models on the COCO dataset, the designed attention mechanism module can capture contextual information well, improve detection accuracy, and use sepc network to help balance abstract and detailed information, and reduce the problem of semantic gap in the feature pyramid network.
DPN-SENet:A self-attention mechanism neural network for detection and diagnosis of COVID-19 from chest x-ray images
We propose a deep learning model that can help radiologists and clinicians use chest X-rays to diagnose COVID-19 cases and show the diagnostic features of pneumonia.
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