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cs.CV2024★ 1 cited
Bucketed Ranking-based Losses for Efficient Training of Object Detectors
Feyza Yavuz, Baris Can Cam, Adnan Harun Dogan +3
Ranking-based loss functions, such as Average Precision Loss and Rank&Sort Loss, outperform widely used score-based losses in object detection. These loss functions better align wi…
cs.CV2024★ 2 cited
RankED: Addressing Imbalance and Uncertainty in Edge Detection Using Ranking-based Losses
Bedrettin Cetinkaya, Sinan Kalkan, Emre Akbas
Detecting edges in images suffers from the problems of (P1) heavy imbalance between positive and negative classes as well as (P2) label uncertainty owing to disagreement between di…