12 citations · 16 across the 3 of their papers we have counts for
3 papers
Self-training with dual uncertainty for semi-supervised medical image segmentation
Zhanhong Qiu, Haitao Gan, Ming Shi +2
In the field of semi-supervised medical image segmentation, the shortage of labeled data is the fundamental problem. How to effectively learn image features from unlabeled images t…
Artifact-Tolerant Clustering-Guided Contrastive Embedding Learning for Ophthalmic Images
Min Shi, Anagha Lokhande, Mojtaba S. Fazli +10
Ophthalmic images and derivatives such as the retinal nerve fiber layer (RNFL) thickness map are crucial for detecting and monitoring ophthalmic diseases (e.g., glaucoma). For comp…
Transfer Learning Application of Self-supervised Learning in ARPES
Sandy Adhitia Ekahana, Genta Indra Winata, Y. Soh +3
Recent development in angle-resolved photoemission spectroscopy (ARPES) technique involves spatially resolving samples while maintaining the high-resolution feature of momentum spa…