Jun 1, 2023 · Our loss is formed of three components. One leading objective ensures that the learned features are attracted to each designated learnable class ...
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Abstract: Loss functions play a major role in influencing the effectiveness of neural networks in content-based image retrieval (CBIR).
To this end, we introduce a novel repeller-attractor loss based on metric learning, which directly optimizes the. L. 2. metric, without pair generation.
Missing: Retrieval. | Show results with:Retrieval.
Apr 25, 2024 · The performance of neural networks in content-based image retrieval (CBIR) is highly influenced by the chosen loss (objective) function.
Missing: Based | Show results with:Based
May 7, 2024 · The performance of neural networks in content-based image retrieval (CBIR) is highly influenced by the chosen loss (objective) function.
Class Anchor Margin Loss for Content-Based Image Retrieval
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Jun 4, 2023 · Our loss is formed of three components. One leading objective ensures that the learned features are attracted to each designated learnable class ...
Feb 6, 2022 · Hi everyone I'm struggling with the triplet loss convergence. I'm trying to do a face verification (1:1 problem) with a minimum computer ...
Class Anchor Margin Loss for Content-Based Image Retrieval ... The performance of neural networks in content-based image retrieval (CBIR) is highly influenced by ...
We introduce a triplet-learning method for automated querying of medical image repositories based on a novel Opponent Class Adaptive Margin (OCAM) loss.
May 5, 2024 · Alexandru Ghita, Radu Tudor Ionescu: A New Loss for Image Retrieval: Class Anchor Margin. PAKDD (2) 2024: 43-54; 2023.
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