Detection Performance
Detection performance, the accuracy and efficiency of identifying objects within data, is a central theme in numerous scientific fields, aiming to improve both the precision of object identification and the speed of detection. Current research heavily utilizes deep learning architectures, particularly variations of YOLO and transformer-based models, to enhance detection across diverse applications, from medical imaging to autonomous driving. Improvements focus on addressing challenges like small object detection, imbalanced datasets, and computational efficiency, ultimately impacting fields ranging from healthcare diagnostics to environmental monitoring and industrial automation.
Papers
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