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Found 4 papers, 4 papers with code
Hard-aware Instance Adaptive Self-training for Unsupervised Cross-domain Semantic Segmentation
The divergence between labeled training data and unlabeled testing data is a significant challenge for recent deep learning models.
WUDA: Unsupervised Domain Adaptation Based on Weak Source Domain Labels
For scenarios where weak supervision and cross-domain problems coexist, this paper defines a new task: unsupervised domain adaptation based on weak source domain labels (WUDA).
Predicting Axillary Lymph Node Metastasis in Early Breast Cancer Using Deep Learning on Primary Tumor Biopsy Slides
Conclusion: Our study provides a novel DL-based biomarker on primary tumor CNB slides to predict the metastatic status of ALN preoperatively for patients with EBC.
LLVIP: A Visible-infrared Paired Dataset for Low-light Vision
It is very challenging for various visual tasks such as image fusion, pedestrian detection and image-to-image translation in low light conditions due to the loss of effective target areas.
Ranked #1 on
Thermal Infrared Pedestrian Detection
on LLVIP
