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Towards Robust Event-guided Low-Light Image Enhancement: A Large-Scale Real-World Event-Image Dataset and Novel Approach
To this end, we propose a real-world (indoor and outdoor) dataset comprising over 30K pairs of images and events under both low and normal illumination conditions.
Adaptively Integrated Knowledge Distillation and Prediction Uncertainty for Continual Learning
The first one is to adaptively integrate multiple levels of old knowledge and transfer it to each block level in the new model.
Learning Discriminative Representation via Metric Learning for Imbalanced Medical Image Classification
Data imbalance between common and rare diseases during model training often causes intelligent diagnosis systems to have biased predictions towards common diseases.
PCCT: Progressive Class-Center Triplet Loss for Imbalanced Medical Image Classification
For the class-center involved triplet loss, the positive and negative samples in each triplet are replaced by their corresponding class centers, which enforces data representations of the same class closer to the class center.
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