LabVSP@NCHU
Research Field
Hao-Chiang Shao (Member, IEEE) earned his Ph.D. degree in electrical engineering from National Tsing Hua University, Taiwan, in 2012. Since August 2022, he has been affiliated with the Institute of Data Science & Information Computing at National Chung Hsing University, Taichung, Taiwan. Previously, he served as an Assistant Professor in the Department of Statistics and Information Science at Fu Jen Catholic University (2018–2022). Prior to that, he worked as an R&D engineer at the Computational Intelligence Technology Center, Industrial Technology Research Institute (ITRI), where he was honored with The Bronze Medal, Excellent Research Award of ITRI (2017–2018).
From 2012 to 2017, he held a postdoctoral researcher position at the Institute of Information Science, Academia Sinica, contributing to a series of Drosophila brain research projects. His diverse research interests span image processing, 2D+Z biomedical image atlasing, big industrial data analysis, computer vision, and machine learning.
My lab's research topics encompass areas such as image processing, computer vision, and deep learning. In recent years, our research projects have leaned towards collaboration with well-known domestic semiconductor manufacturers, international companies (for topics including image forgery detection, active learning for object detection, and image segmentation), as well as partnerships with domestic hospitals (such as Chang Gung Memorial Hospital) or corporate entities (Industrial Technology Research Institute). The primary research directions of my graduate students also focus on semiconductor image processing algorithms (including anomaly detection and active learning), medical image segmentation, biomedical forgery image detection, and biological image classification and recognition.
My recent research topics include (1) real-world highly-imbalanced data classification, (2) weakly-supervised fine-grained attribute pre-labelling, (3) retinal fundus image segmentation, (4) biomedical image forgery detection, and (5) active learning for segmentation, object detection, and EDA tools. Listed below are my publications from the last five years.
<Journal Papers>
[J10] Hao-Chiang Shao*, Chih-Ying Chen, Meng-Hsuan Chang, Chih-Han Yu, Chia-Wen Lin, and Ju-Wen Yang, “Retina-TransNet: A Gradient-Guided Few-Shot Retinal Vessel Segmentation Net”, IEEE Journal of Biomedical and Health Information, 27(10), pp.4902--4913, Oct. 2023. (SCI; impact factor 7.7, Q1, rank: 3/47).
[J09] Hao-Chiang Shao, Hsing-Lei Ping, Kuo-shiuan Chen, Weng-Tai Su, Chia-Wen Lin*, Shao-Yun Fang, Pin-Yen Tsai, and Yan-Hsiu Liu, “Keeping Deep Lithography Simulators Updated: Global-Local Shape-Based Novelty Detection and Active Learning”, Transactions on Computer-Aided Design of Integrated Circuits and Systems, 42(3), pp.1000--1014, March, 2023. (SCI; impact factor 2.807, Q2, rank: 119/273).
[J08] Giam Minh Trinh, Hao-Chiang Shao, Kevin Li-Chun Hsieh , Ching-Yu Lee, Hsiao-Wei Liu, Chen-Wei Lai, Sen-Yi Chou, Pei-I Tsai, Kuan-Jen Chen, Fang-Chieh Chang, Meng-Huang Wu, and Tsung-Jen Huang, “Detection of Lumbar Spondylolisthesis from X-ray Images Using Deep Learning Network”, pp. 1~17, Journal of Clinical Medicine, Vol. 11(18), 2022.
[J07] Hao-Chiang Shao, Kang-Yu Liu, Weng-Tai Su, Chia-Wen Lin*, and Jiwen Lu, “DotFAN: A Domain-Transferred Face Augmentation Net”, IEEE Transactions on Image Processing, pp.8759-8772, vol.30, Nov., 2021. (SCI; impact factor 10.856, Q1, rank: 9/273)
[J06] Hao-Chiang Shao, Hsin-Chieh Wang, Weng-Tai Su, and Chia-Wen Lin*, “Ensemble Learning with Manifold-Based Data Splitting for Noisy Label Correction”, IEEE Transactions on Multimedia, pp.1127~1140, vol. 24, 2022. (SCI; impact factor 6.513, Q1, rank: 5/108)
[J05] Hao-Chiang Shao*, Lu-Hung Hsu, Yung-Chang Chen, Ying-Chu Huang, Shih-Ting Huang, “Drosophila Brain Aligner: Registering 3D Point Clouds in 2D Parameterization Domain”, Journal of Information Science and Engineering, Jan., 2022. (SCI, Q4)
<Conference Papers>
[C24] Hao-Chiang Shao*, Szu-Chi Wu, Yen-Liang Chuo, Jyun-Hao Lin, Yuan-Rong Liao, and Tse-Yu Tseng, “RGBT2HS-Net: Reconstructing a hyper-spectral volume from an RGB-T stack via an attention-powered multiresolution framework”, IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Apr. 14-19, 2024, Seoul, Korea.
[C23] Hao-Chiang Shao*, Yu-Hsien Lin, and Chia-Wen Lin, “A Fine-grained Attribute Pre-labelling Method Based on Label Dependency and Feature Similarity Dynamics”, IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Apr. 14-19, 2024, Seoul, Korea.
[C22] Hao-Chiang Shao, Chia-Wen Lin, Shao-Yun Fang*, “Data-driven approaches for process simulation and optical proximity correction”, The 28th Asia and South Pacific Design Automation Conference (ASP-DAC 2023), Jan. 16-19, 2023, Tokyo, Japan.
[C21] Meng-Hsuan Chang, Chih-Ying Chen, Chih-Han Yu, Hao-Chiang Shao*, Chia-Wen Lin, “Vessel Segmentation and Dirt/Reflection Detection for Retinal Fundus Photographs”, IEEE International Conference on Image Processing (ICIP) 2022, Oct. 16~19, 2022, Bordeaux, France.
[C20] Chia-Sheng Cheng, Hao-Chiang Shao, and Chia-Wen Lin*, "Task-aware Few-shot Visual Classification with Improved Self-supervised Metric Learning", IEEE International Conference on Image Processing (ICIP) 2022, Oct. 16~19, 2022, Bordeaux, France.
[C19] Shih-Ting Huang, Yue Jiang, Hao-Chiang Shao*, “Convolution-based Soma Counting Algorithm for Confocal Microscopy Image Stacks”, BIOSIGNALS 2021 (Virtual), Vienna, Austria.
[J04] Hao-Chiang Shao, Chao-Yi Peng, Jun-Rei Wu, Chia-Wen Lin*, Shao-Yun Fang, Pin-Yen Tsai, and Yan-Hsiu Liu, “From IC Layout to Die Photograph: A CNN-based Data-Driven Approach”, IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, 40(5), pp.957--970, May, 2021. (SCI; impact factor 2.807, Q2, rank: 119/273)
[C18] Hao-Chiang Shao, Kang-Yu Liu, Chia-Wen Lin*, Jiwen Lu, “DotFAN: A Domain-transferred Face Augmentation Network”, ACCV 2020, Nov. 30~Dec. 4, 2020, (Virtual) Tokyo, Japan.
[C17] Hao-Chaing Shao*, Yi-Ming Wang, Yung-Chang Chen, “A Two-phase Segmentation Method For Drosophila Olfactory Glomeruli”, IEEE International Conference on Image Processing (ICIP) 2019, Sep. 22~25, 2019, Taipei, Taiwan.
[C16] Ziling Huang, Chia-Wen Lin*, Hao-Chiang Shao, Xiangsheng Huang, “Consistency Constrained Reconstruction of Depth Maps From Epipolar Plane Images”, IEEE ICASSP 2019, May 12~17, 2019, Brighton, UK.
<Patents>
[P02] Hao-Chiang Shao, US Patent, US 11,017,516,“Forgery detection system and its method for falsified biomedical experiment images”
- World Top-5 of ICASSP 2024 SP Grand Challenge on Hyperspectral Skin Vision, 2024.
- The Bronze Medal, Excellent Research Award of Industrial Technology Research Institute (ITRI), 2018.
- Best Paper Award, VLSI Design/CAD Symposium, 2020.
- Best Paper Award, The 33rd IPPR CVGIP-2020.
- Champion, 2019 MATLAB Deep Learning Competition (Asia, Taiwan Region): Unmanned Store Product Recognition", 2019.
- Enterprise Award, IDEAS SHOWxAI Product Image AI Recognition Competition 2019, held by Commercial Division, Ministry of Economic Affairs, R.O.C., 2019.
- Best Paper Award, IEEE International Conference on Awareness Science and Technology (iCAST), 2017.
- Ph.D., Department of Electrical Engineering, National Tsing Hua University, 2006~2012.
- M.S., Department of Electrical Engineering, National Tsing Hua University, 2001~2003
- B.S., Department of Electrical Engineering, National Tsing Hua University, 1997~2001