| Towards Efficient Model Compression via Learned Global Ranking TW Chin, R Ding, C Zhang, D Marculescu Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2020 | 186 | 2020 |
| Regularizing activation distribution for training binarized deep networks R Ding, TW Chin, Z Liu, D Marculescu Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2019 | 131 | 2019 |
| Adascale: Towards real-time video object detection using adaptive scaling TW Chin, R Ding, D Marculescu MLSys 2019: The Conference on Machine Learning and Systems, 2019 | 83 | 2019 |
| Designing Adaptive Neural Networks for Energy-Constrained Image Classification D Stamoulis, TW Chin, AK Prakash, H Fang, S Sajja, M Bognar, ... Proceedings of the International Conference on Computer-Aided Design, 2018 | 74 | 2018 |
| Layer-compensated pruning for resource-constrained convolutional neural networks TW Chin, C Zhang, D Marculescu NeurIPS 2018 Workshop MLPCD 2, 2018 | 54 | 2018 |
| Flying iot: Toward low-power vision in the sky H Genc, Y Zu, TW Chin, M Halpern, VJ Reddi IEEE micro 37 (6), 40-51, 2017 | 52 | 2017 |
| Understanding the impact of label granularity on cnn-based image classification Z Chen, R Ding, TW Chin, D Marculescu 2018 IEEE international conference on data mining workshops (ICDMW), 895-904, 2018 | 35 | 2018 |
| Flightnns: Lightweight quantized deep neural networks for fast and accurate inference R Ding, Z Liu, TW Chin, D Marculescu, RD Blanton Proceedings of the 56th Annual Design Automation Conference 2019, 1-6, 2019 | 28 | 2019 |
| One Weight Bitwidth to Rule Them All TW Chin, PIJ Chuang, V Chandra, D Marculescu ECCV Workshops (Best paper in Embedded Vision Workshop), 2020 | 23 | 2020 |
| Joslim: Joint Widths and Weights Optimization for Slimmable Neural Networks TW Chin, AS Morcos, D Marculescu ECML-PKDD (Research Track), 2021 | 16* | 2021 |
| Domain-specific approximation for object detection TW Chin, CL Yu, M Halpern, H Genc, SL Tsao, VJ Reddi IEEE Micro 38 (1), 31-40, 2018 | 16 | 2018 |
| Renofeation: A Simple Transfer Learning Method for Improved Adversarial Robustness TW Chin, C Zhang, D Marculescu CVPR Workshops (Best paper in Fair, Data Efficient and Trusted Computer Vision), 2021 | 14* | 2021 |
| Towards efficient model compression via learned global ranking. 2020 IEEE TW Chin, R Ding, C Zhang, D Marculescu CVF Conference on Computer Vision and Pattern Recognition (CVPR), 1515-1525, 2020 | 8 | 2020 |
| Width Transfer: On the (In) variance of Width Optimization TW Chin, D Marculescu, AS Morcos CVPR Workshops (Efficient Deep Learning for Computer Vision), 2021 | 5 | 2021 |
| Optimizing sensor-cloud architectures for real-time autonomous drone operation H Genc, TW Chin, M Halpern, VJ Reddi Sensors to Cloud Architectures Workshop (SCAW), 2017 | 5 | 2017 |
| QUIDAM: A Framework for Quantization-aware DNN Accelerator and Model Co-Exploration A Inci, S Virupaksha, A Jain, TW Chin, V Thallam, R Ding, D Marculescu ACM Transactions on Embedded Computing Systems 22 (2), 1-21, 2023 | 4 | 2023 |
| Ant: Adapt network across time for efficient video processing F Liang, TW Chin, Y Zhou, D Marculescu Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022 | 4 | 2022 |
| Flexible, lightweight quantized deep neural networks R Ding, Z Liu, TW Chin, D Marculescu, RD Blanton US Patent 11,521,074, 2022 | 1 | 2022 |
| Transfer Learning TW Chin, C Zhang Computer Vision: A Reference Guide, 1269-1273, 2021 | 1 | 2021 |
| Improving the accuracy of the leakage power estimation of embedded CPUs TW Chin, SL Tsao, KW Hung, PS Huang Design, Automation & Test in Europe Conference & Exhibition (DATE), 2017 …, 2017 | 1 | 2017 |
Diana MarculescuThe University of Texas at AustinVerified email at utexas.edu
