Lile Cai

Publication Activity (10 Years)

Years Active: 2013-2024
Publications (10 Years): 14

Top Topics

Active Learning

Top Venues

Publications

Xun Xu, Jingyi Liao, Lile Cai, Manh Cuong Nguyen, Kangkang Lu, Wanyue Zhang, Yasin Yazici, Chuan Sheng Foo
Revisiting pretraining for semi-supervised learning in the low-label regime. Neurocomputing 565 (2024)
Yinan He, Lile Cai, Jingyi Liao, Chuan-Sheng Foo
Hybrid Active Learning with Uncertainty-Weighted Embeddings. Trans. Mach. Learn. Res. 2024 (2024)
Sezin Kircali Ata, Zhi-Hui Kong, Anusha James, Lile Cai, Kiat Seng Yeo, Khin Mi Mi Aung, Chuan Sheng Foo, Ashish James
The Initialization Factor: Understanding its Impact on Active Learning for Analog Circuit Design. ISCAS (2024)
Zhihao Liang, Xun Xu, Shengheng Deng, Lile Cai, Tao Jiang, Kui Jia
Exploring Diversity-based Active Learning for 3D Object Detection in Autonomous Driving. CoRR (2022)
Lile Cai, Ramanpreet Singh Pahwa, Xun Xu, Jie Wang, Richard Chang, Lining Zhang, Chuan-Sheng Foo
Exploring Active Learning for Semiconductor Defect Segmentation. ICIP (2022)
Xun Xu, Jingyi Liao, Lile Cai, Cuong Manh Nguyen, Kangkang Lu, Wanyue Zhang, Yasin Yazici, Chuan Sheng Foo
Revisiting Pretraining for Semi-Supervised Learning in the Low-Label Regime. CoRR (2022)
Lile Cai, Xun Xu, Lining Zhang, Chuan-Sheng Foo
Exploring Spatial Diversity for Region-Based Active Learning. IEEE Trans. Image Process. 30 (2021)
Xian Shi, Xun Xu, Ke Chen, Lile Cai, Chuan Sheng Foo, Kui Jia
Label-Efficient Point Cloud Semantic Segmentation: An Active Learning Approach. CoRR (2021)
Lile Cai, Xun Xu, Jun Hao Liew, Chuan Sheng Foo
Revisiting Superpixels for Active Learning in Semantic Segmentation With Realistic Annotation Costs. CVPR (2021)
Lile Cai, Bin Zhao, Zhe Wang, Jie Lin, Chuan Sheng Foo, Mohamed M. Sabry Aly, Vijay Chandrasekhar
MaxpoolNMS: Getting Rid of NMS Bottlenecks in Two-Stage Object Detectors. CVPR (2019)
Lile Cai, Anne-Maelle Barneche, Arthur Herbout, Chuan Sheng Foo, Jie Lin, Vijay Ramaseshan Chandrasekhar, Mohamed M. Sabry Aly
TEA-DNN: the Quest for Time-Energy-Accuracy Co-optimized Deep Neural Networks. ISLPED (2019)
Lile Cai, Anne-Maelle Barneche, Arthur Herbout, Chuan Sheng Foo, Jie Lin, Vijay Ramaseshan Chandrasekhar, Mohamed M. Sabry
TEA-DNN: the Quest for Time-Energy-Accuracy Co-optimized Deep Neural Networks. CoRR (2018)
Lile Cai, Binh P. Nguyen, Chee-Kong Chui, Sim Heng Ong
A two-level clustering approach for multidimensional transfer function specification in volume visualization. Vis. Comput. 33 (2) (2017)
Lile Cai, Yiqun Li
Anomaly detection in thermal images using deep neural networks. ICIP (2017)
Lile Cai, Binh P. Nguyen, Chee-Kong Chui, Sim Heng Ong
Rule-Enhanced Transfer Function Generation for Medical Volume Visualization. Comput. Graph. Forum 34 (3) (2015)
Lile Cai, Wei-Liang Tay, Binh P. Nguyen, Chee-Kong Chui, Sim Heng Ong
Automatic transfer function design for medical visualization using visibility distributions and projective color mapping. Comput. Medical Imaging Graph. 37 (7-8) (2013)