14 citations · 27 across the 3 of their papers we have counts for
3 papers
cs.CV2025★ 13 cited
Exploring Spatial Diversity for Region-based Active Learning
Lile Cai, Xun Xu, Lining Zhang +1
State-of-the-art methods for semantic segmentation are based on deep neural networks trained on large-scale labeled datasets. Acquiring such datasets would incur large annotation c…
cs.CV2025★ 14 cited
Exploring Active Learning for Semiconductor Defect Segmentation
Lile Cai, Ramanpreet Singh Pahwa, Xun Xu +4
The development of X-Ray microscopy (XRM) technology has enabled non-destructive inspection of semiconductor structures for defect identification. Deep learning is widely used as t…
cs.CV2025
Exploring Active Learning for Label-Efficient Training of Semantic Neural Radiance Field
Yuzhe Zhu, Lile Cai, Kangkang Lu +2
Neural Radiance Field (NeRF) models are implicit neural scene representation methods that offer unprecedented capabilities in novel view synthesis. Semantically-aware NeRFs not onl…