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Found 6 papers, 5 papers with code
Domain-Specific Block Selection and Paired-View Pseudo-Labeling for Online Test-Time Adaptation
After blocks are adjusted for current test domain, we generate pseudo-labels by averaging given test images and corresponding flipped counterparts.
Enhancing Low-resolution Face Recognition with Feature Similarity Knowledge Distillation
This approach differs from conventional knowledge distillation frameworks, which use the L_p distance metrics and offer the advantage of converging well when reducing the distance between features of different resolutions.
Block Selection Method for Using Feature Norm in Out-of-distribution Detection
In this study, we first revealed that a norm of the feature map obtained from the other block than the last block can be a better indicator of OOD detection.
Out-of-Distribution Detection
Out of Distribution (OOD) Detection
Teaching Where to Look: Attention Similarity Knowledge Distillation for Low Resolution Face Recognition
Deep learning has achieved outstanding performance for face recognition benchmarks, but performance reduces significantly for low resolution (LR) images.
SleePyCo: Automatic Sleep Scoring with Feature Pyramid and Contrastive Learning
Conventionally, learning-based automatic sleep scoring on single-channel electroencephalogram (EEG) is actively studied because obtaining multi-channel signals during sleep is difficult.
Multiple Classification with Split Learning
We divided a single deep learning architecture into a common extractor, a cloud model and a local classifier for the distributed learning.
