| Revisiting superpixels for active learning in semantic segmentation with realistic annotation costs L Cai, X Xu, JH Liew, CS Foo Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2021 | 65 | 2021 |
| Label-efficient point cloud semantic segmentation: An active learning approach X Shi, X Xu, K Chen, L Cai, CS Foo, K Jia arXiv preprint arXiv:2101.06931, 2021 | 38 | 2021 |
| Maxpoolnms: getting rid of nms bottlenecks in two-stage object detectors L Cai, B Zhao, Z Wang, J Lin, CS Foo, MS Aly, V Chandrasekhar Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2019 | 33 | 2019 |
| Anomaly detection in thermal images using deep neural networks C Lile, L Yiqun 2017 IEEE International conference on image processing (ICIP), 2299-2303, 2017 | 31 | 2017 |
| Automatic transfer function design for medical visualization using visibility distributions and projective color mapping L Cai, WL Tay, BP Nguyen, CK Chui, SH Ong Computerized Medical Imaging and Graphics 37 (7-8), 450-458, 2013 | 27 | 2013 |
| TEA-DNN: the quest for time-energy-accuracy co-optimized deep neural networks L Cai, AM Barneche, A Herbout, CS Foo, J Lin, VR Chandrasekhar, ... 2019 IEEE/ACM International Symposium on Low Power Electronics and Design …, 2019 | 22 | 2019 |
| A two-level clustering approach for multidimensional transfer function specification in volume visualization L Cai, BP Nguyen, CK Chui, SH Ong The Visual Computer 33, 163-177, 2017 | 21 | 2017 |
| Exploring diversity-based active learning for 3d object detection in autonomous driving Z Liang, X Xu, S Deng, L Cai, T Jiang, K Jia arXiv preprint arXiv:2205.07708, 2022 | 20 | 2022 |
| Rule‐Enhanced Transfer Function Generation for Medical Volume Visualization LL Cai, BP Nguyen, CK Chui, SH Ong Computer Graphics Forum 34 (3), 121-130, 2015 | 14 | 2015 |
| Exploring spatial diversity for region-based active learning L Cai, X Xu, L Zhang, CS Foo IEEE Transactions on Image Processing 30, 8702-8712, 2021 | 10 | 2021 |
| Revisiting pretraining for semi-supervised learning in the low-label regime X Xu, J Liao, L Cai, MC Nguyen, K Lu, W Zhang, Y Yazici, CS Foo Neurocomputing 565, 126971, 2024 | 6 | 2024 |
| 3d defect detection and metrology of hbms using semi-supervised deep learning RS Pahwa, R Chang, W Jie, Z Ziyuan, C Lile, X Xun, FC Sheng, ... 2023 IEEE 73rd Electronic Components and Technology Conference (ECTC), 943-950, 2023 | 6 | 2023 |
| Improved bump detection and defect identification for hbms using refined machine learning approach W Jie, R Chang, X Xun, C Lile, CS Foo, RS Pahwa 2022 IEEE 24th Electronics Packaging Technology Conference (EPTC), 848-853, 2022 | 5 | 2022 |
| Exploring active learning for semiconductor defect segmentation L Cai, RS Pahwa, X Xu, J Wang, R Chang, L Zhang, CS Foo 2022 IEEE International Conference on Image Processing (ICIP), 1796-1800, 2022 | 3 | 2022 |
| Hybrid Active Learning with Uncertainty-Weighted Embeddings Y He, L Cai, J Liao, CS Foo Transactions on Machine Learning Research, 2024 | | 2024 |
| Label-Efficient Point Cloud Semantic Segmentation: A Holistic Active Learning Approach X Shi, L Cai, K Chen, CS Foo, K Jia, X Xu World Scientific Annual Review of Artificial Intelligence, 2024 | | 2024 |
| The Initialization Factor: Understanding its Impact on Active Learning for Analog Circuit Design SK Ata, ZH Kong, A James, L Cai, KS Yeo, KMM Aung, CS Foo, A James 2024 IEEE International Symposium on Circuits and Systems (ISCAS), 1-5, 2024 | | 2024 |
