成功大學統計學系

系所成員
姓名 許志仲
職稱 副教授
專長領域 多媒體資訊安全、影像處理、電腦視覺、機器學習、深度學習
E-mail cchsu@gs.ncku.edu.tw
辦公室 管理學院統計系館3樓62321室
聯絡電話 (06)2757575~53641
個人網頁 https://cchsu.info
1. Ph.D. National Tsing Hua University (NTHU), Electrical Engineering, Taiwan, September. 2014. Ph.D. dissertation topic: Quality enhancement and assessment for image/video resizing. Advisor: Prof. Chia-Wen Lin. 清大電機博士。
2. M.S.  National Yunlin University of Science and Technology (Yuntech), Taiwan, Electrical Engineering, June 2006. Thesis topic: “Studies of improving coding performance and encryption in various image compression techniques”. Advisor: Prof. Hsuan-Ting Chang. 雲科大電機碩士。
3. B.S.  Lingtung University of Science and Technology, Management Information Systems, Taiwan, June 2004. Project topic: "Parallel encryption system for image authentication. " 嶺東資管學士。
4. A.S. National Chin-Yi University of Technology, Department of Electronic Engineering, Taiwan, June 2022, Project topic: Robust watermarking for image and audio signals. "勤益科大電子科副學士"

 

Experiences (相關經歷):

Industrial Employment

 

  • Co-Founder & CTO, SKOPY Inc. (NTHU Incubation Center). Oct. 2017-Feb. 2018.
  • Co-Founder & Project Director, Eye-Digit. Inc., Feb. 2011 – Feb. 2013.
  •  

Academic Services

  • Assistant Professor, Department of Management Information Systems, National Pingtung university of Science and Technology, Feb. 2018-Feb. 2021.
  • Vice-Chairman, IEEE SPS Tainan Chapter, Feb. 2020 –Present.Committee of Career Development, National Pingtung University of Science and Technology (NPUST), August 2019—Present.
  • Committee of Teacher Grievances, NPUST, August 2019—Present.
  • Curriculum Committee in College of Management, NPUST, August 2018—Present.
  • Committee of Distance Learning, NPUST, August 2018 – Present.
  • NPUST AOL (Assurance of Learning) Vice Chairmain in AACSB Group, February 2018 – Present.
  1. Selected Journal Papers (* corresponding author)

    1. G.L. Chen and C.C. Hsu*, “Jointly Defending DeepFake Manipulation and Adversarial Attack using Decoy Mechanism,” IEEE Transactions on Pattern Analysis and Machine Intelligence (IF: 24.31, 2/276=1%), to appear.
    2. C.H. Lin, Y. Liu, C.Y. Chi, C.C. Hsu, H. Ren, & T.Q. Quek, “Hyperspectral Tensor Completion Using Low-Rank Modeling and Convex Functional Analysis,” IEEE Transactions on Neural Networks and Learning Systems (IF:14.225, 5/276=2%), to appear.
    3. J.Y. Yang, T.C. Lee, W.T. Liao, C.C. Hsu*, “Multi-Head Self-Attention Mechanism Enabled Individualized Hemoglobin Prediction and Treatment Recommendation Systems in Anemia Management for Hemodialysis Patients,” in Heliyon (IF: 2.85, Rank: 27/138=19% Q1), (accepted)
    4. C.Y. Wei, W.Y. Huang, C.Y. Jian, C.C.H. Hsu, C.C. Hsu, et al., “Semantic segmentation guided detector for segmentation, classification, and lesion mapping of acute ischemic stroke in MRI images,” in NeuroImageClinical (IF: 4.88, Rank 29/288=10%), (accepted)
    5. H. Fang, F. Li, H. Fu, X. Sun, X. Cao, F. Lin, J. Son, S. Kim, G. Quellec, S. Matta, S. M, Shankaranarayana, Y.T. Chen, C.H. Wang, N. A Shah, C.Y. Yen Lee, C.-C. Hsu et al., “ADAM Challenge: Detecting Age-related Macular Degeneration from Fundus Images,” in IEEE Transactions on Medical Imaging (IF: 10.05, Rank=21/693=3%), doi: 10.1109/TMI.2022.3172773, May 2022.
    6. C.C. Hsu, C. -H. Lin, C. -H. Kao and Y. -C. Lin, “DCSN: Deep Compressed Sensing Network for Efficient Hyperspectral Data Transmission of Miniaturized Satellite,” in IEEE Transactions on Geoscience and Remote Sensing, vol. 59, no. 9, pp. 7773-7789, Sept. 2021. (IF: 5.85, Rank 29/1409=2% in Electrical and Electronic Engineering)
    7. C.C. Hsu, Y. X. Zhuang, and C. Y. Lee, “Deep Fake Image Detection Based on Pairwise Learning,” Appl Sci-Basel, vol. 10, no. 1, p. 370, Jan 2020. (IF: 2.47, Rank 41/275 in General Engineering)
    8. C.C. Hsu, C. W. Lin, W. T. Su, and G. Cheung, “SiGAN: Siamese Generative Adversarial Network for Identity-Preserving Face Hallucination,” IEEE Transactions on Image Processing, vol. 28, no. 12, pp. 6225-6236, Dec 2019. (IF:9.34, Rank: 5/334=1% in Computer Graphics and Computer-Aided Design Software).
    9. C.C. Hsu and C.-W. Lin, “Cnn-based joint clustering and representation learning with feature drift compensation for large-scale image data,” IEEE Transactions on Multimedia, vol. 20, no. 2, pp. 421-429, 2017. (IF:6.051, Rank: 2/195=1% in Media Technology).
    10. C.C. Hsu, L. Kang, and C. Lin, “Temporally Coherent Super-Resolution of Textured Video via Dynamic Texture Synthesis,” IEEE Transactions on Image Processing, vol. 24, no. 3, pp. 919 – 931, 2015. (IF:9.34, Rank: 5/334=1% in Computer Graphics and Computer-Aided Design Software).
    11. W. Kang, C.C. Hsu, B. Q. Zhuang, C. W. Lin, and C. H. Yeh, “Learning-Based Joint Super-Resolution and Deblocking for a Highly Compressed Image,” Ieee Transactions on Multimedia, vol. 17, no. 7, pp. 921-934, Jul 2015. (IF:6.051, Rank: 2/195=1% in Media Technology).
    12. C.C. Hsu, C. W. Lin, Y. M. Fang, and W. S. Lin, “Objective Quality Assessment for Image Retargeting Based on Perceptual Geometric Distortion and Information Loss,” Ieee Journal of Selected Topics in Signal Processing, vol. 8, no. 3, pp. 377-389, Jun 2014. (IF:6.688, Rank: 7/543=1% in Signal Processing).
  1. Selected Conference Papers 

    1. C. C. Hsu, Y. Z. Jiang, and W. H. Huang, “Swift Concurrent Semantic Segmentation and Object Detection on Edge Devices,” IEEE International Conference on Multimedia and Expo (ICME) Workshop, Brisbane, Australia, 10-14 July 2023.
    2. C. C. Hsu, C.Y. Jian, C.M. Lee, C.H. Tsai, and S.C. Tai, “Bag of Tricks of Hybrid Network for COVID-19 Detection of CT Scans,” IEEE International Conference on Acoustics, Speech, & Signal Processing (ICASSP), June 2023.
    3. C.C. Hsu and M.Z. Ke, “Seeing is NOT Believing: Toward Forgery Detection for Hyperspectral Image,” IEEE International Geoscience and Remote Sensing Symposium (IGARSS), July 2023.
    4. C.C. Hsu, C.H. Tsai, G.L. Chen, S.D. Ma, and S.C. Dai, “Spatial-Slice Feature Learning using Visual Transformer and Essential Slices Selection Module for COVID-19 Detection of CT Scans in the Wild,” European Conference on Computer Vision (ECCV) Workshop, 23-27 Oct. 2022.
    5. C.C. Hsu, P.J. Tsai, T.C. Yeh, and X.U. Hou, “A Comprehensive Study of Spatiotemporal Feature Learning for Social Medial Popularity Prediction,” 30th ACM international conference on Multimedia, 10-14 Oct. 2022.
    6. C.C. Hsu, C. Lee, S. Tai, and Y. Jiang, “Augmented-Training-Aware Bisenet for Real-Time Semantic Segmentation,” in 2022 IEEE International Conference on Multimedia and Expo Workshops (ICMEW), Taipei City, Taiwan, 2022 pp. 1-6.
    7. B.S. Huang, C.C. Hsu, W.T. Liao, H.Y. Kao, and X.Y. Wang, “DCSN: Deformable Convolutional Semantic Segmentation Neural Network for Non-Rigid Scenes,” IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 22-27 May 2022.
    8. G.L. Chen, C.C. Hsu, and M.H. Wu, “Adaptive Distribution Learning with Statistical Hypothesis Testing for COVID-19 CT Scan Classification,” in Proc. of IEEE/CVF International Conference on Computer Vision Workshop (ICCVW), Oct. 2021.
    9. C.C. Hsu, C, Lee, C. Lin, K.M. Hung, Y.L. Lin, X.Y. Wang, “Efficient-ROD: Efficient Radar Object Detection based on Densely Connected Residual Network,” in Proc. of ACM International Conference on Multimedia Retrieval (ICMR), 21-24 Aug., 2021.
    10. C.-C. Hsu, W.-H. Tseng, H.-T. Yang, C.-H. Lin, and C.-H. Kao, “Rethinking Relation between Model Stacking and Recurrent Neural Networks for Social Media Prediction,” in Proceedings of the 28th ACM International Conference on Multimedia, 2020, pp. 4585-4589.
    11. C.-C. Hsu, W.-H. Tseng, and H.-T. Yang, “Learning to Predict Risky Driving Behaviors for Autonomous Driving,” in 2020 IEEE International Conference on Consumer Electronics-Taiwan (ICCE-Taiwan), 2020: IEEE, pp. 1-2.
    12. Y.-X. Zhuang and C.-C. Hsu, “Detecting Generated Image Based on a Coupled Network with Two-Step Pairwise Learning,” in 2019 IEEE International Conference on Image Processing (ICIP), 2019: IEEE, pp. 3212-3216. (Best Student Paper Award)
    13. C.-C. Hsu, L.-W. Kang, C.-Y. Lee, J.-Y. Lee, Z.-X. Zhang, and S.-M. Wu, “Popularity prediction of social media based on multi-modal feature mining,” in Proceedings of the 27th ACM International Conference on Multimedia, 2019, pp. 2687-2691.
    14. Lugmayr et al., “Aim 2019 challenge on real-world image super-resolution: Methods and results,” in 2019 IEEE/CVF International Conference on Computer Vision Workshop (ICCVW), 2019: IEEE, pp. 3575-3583.
    15. C.-C. Hsu, C.-H. Hung, C.-Y. Jian, and Y.-X. Zhuang, “Stronger Baseline for Vehicle Re-Identification in the Wild,” in 2019 IEEE Visual Communications and Image Processing (VCIP), 2019: IEEE, pp. 1-4.
    16. C.-C. Hsu and C.-H. Lin, “Dual Reconstruction with Densely Connected Residual Network for Single Image Super-Resolution,” in IEEE International Conference on Computer Vision Workshop (ICCVW), 2019.
    17. W.-T. Su, C.-C. Hsu, Z. Huang, C.-W. Lin, and G. Cheung, “Joint pairwise learning and image clustering based on a siamese cnn,” in 2018 25th IEEE International Conference on Image Processing (ICIP), 2018: IEEE, pp. 1992-1996.
    18. C.-C. Hsu et al., “An iterative refinement approach for social media headline prediction,” in Proceedings of the 26th ACM international conference on Multimedia, 2018, pp. 2008-2012.
    19. C.-C. Hsu, C.-Y. Lee, and Y.-X. Zhuang, “Learning to detect fake face images in the wild,” in 2018 International Symposium on Computer, Consumer and Control (IS3C), 2018: IEEE, pp. 388-391.
    20. C.-C. Hsu et al., “Social media prediction based on residual learning and random forest,” in Proceedings of the 25th ACM international conference on Multimedia, 2017, pp. 1865-1870. (Oral & Best Grand Challenge Paper Award)
    21. C.-C. Hsu and C.-W. Lin, “Objective quality assessment for video retargeting based on spatio-temporal distortion analysis,” in 2017 IEEE Visual Communications and Image Processing (VCIP), 2017: IEEE, pp. 1-4.
    22. C.-C. Hsu and C.-W. Lin, “Unsupervised convolutional neural networks for large-scale image clustering,” in 2017 IEEE International Conference on Image Processing (ICIP), 2017: IEEE, pp. 390-394.
    23. W.-T. Su, C.-C. Hsu, C.-W. Lin, and W. Lin, “Supervised-learning based face hallucination for enhancing face recognition,” in 2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2016: IEEE, pp. 1751-1755.
    24. C.-C. Hsu, L.-W. Kang, and C.-W. Lin, “Video super-resolution via dynamic texture synthesis,” in 2014 IEEE 16th International Workshop on Multimedia Signal Processing (MMSP), 2014: IEEE, pp. 1-6.
    25. L.-W. Kang, B. Zhuang, C.-C. Hsu, C.-W. Lin, and C.-H. Yeh, “Self-learning-based low-quality single image super-resolution,” in IEEE Workshop Multimedia Signal Processing (MMSP), Sardinia, Italy, Sept. 2013, 2013. (Top 10% Paper Award)
    26. C.-C. Hsu, C.-W. Lin, Y. Fang, and W. Lin, “Objective quality assessment for image retargeting based on perceptual distortion and information loss,” in 2013 Visual Communications and Image Processing (VCIP), 2013: IEEE, pp. 1-6.
    27. C.-C. Hsu and C.-W. Lin, “Image super-resolution via feature-based affine transform,” in 2011 IEEE 13th International Workshop on Multimedia Signal Processing, 2011: IEEE, pp. 1-5.
    28. C.-C. Hsu, C.-W. Lin, C.-T. Hsu, H.-Y. M. Liao, and J.-Y. Yu, “Face hallucination using Bayesian global estimation and local basis selection,” in 2010 IEEE International Workshop on Multimedia Signal Processing, 2010: IEEE, pp. 449-453.
    29. C.-C. Hsu, T.-Y. Hung, C.-W. Lin, and C.-T. Hsu, “Video forgery detection using correlation of noise residue,” in 2008 IEEE 10th workshop on multimedia signal processing, 2008: IEEE, pp. 170-174.

Patents

  1. C. Hsu and T.C. Lee, “System and method for diagnosing gastrointestinal neoplasm,” US Patent (Enclosing publication)
  2. 童曉儒, 許志仲, 張文誠, “影像辨識方法”, Taiwan Patent, 2018.
  3. 許志仲與張軒韶,”影像辨識系統及其操作方法,” Taiwan Patent #201329874, 2013.
  4. 許志仲與林嘉文,”利用仿射轉換建立影像資料庫之方法,” Taiwan Patent #201317938, 2013.
  5. Chih-Chung Hsu and Chia-Wen Lin, “Method and system for example-based face hallucination,” USA patent # 8,488,913, 2013.
  6. Chih-Chung Hsu and Chia-Wen Lin, “Super-resolution method and system for human face based on sample,” China patent #CN102298775 B, 2013.
  7. 林嘉文與許志仲,”以樣本為基礎之人臉超解析度方法與系統,” Taiwan Patent #201145181, 2011.
  8. 張廷政, 張軒庭, 與許志仲, “應用於網際網路上之分散式並聯加密方法,” Taiwan Patent #094122766, 2005.
  9. 許志仲, 王焜潔, 與張廷政, “應用於網際網路上之分散式加密方法,” Taiwan Patent #093135605, 2004.
  • International Awards

    • Winner, COV19D Challenge, MIA-Workshop in International Conference on Acoustics, Speech, & Signal Processing (ICASSP), June 2023.
    • 2nd place, USV Obstacle Detection, IEEE/CVF Winter Conference on Applications of Computer Vision (WACV) Workshop on Maritime Computer Vision (MaCVi), Jan. 7 2023.
    • Winner, COV19D Challenge, MIA-Workshop in European Conference on Computer Vision (ECCV), Oct. 2022.
    • 4th place, COVID Infection Prediction Challenge, International Conference on Image Analysis and Processing, May 2022.
    • 3rd place, Low-power Deep Learning Semantic Segmentation Model Compression Competition for Traffic Scene in Asian Countries, ICME2022, May 2022.
    • Winner, Outdoor Semantic Segmentation Challenge, DAGM German Conference on Pattern Recognition (GCPR), Sept. 2021.
    • 3rd place, COV19D Challenge, MIA-Workshop in IEEE/CVF International Conference on Computer Vision (ICCV), Oct. 2021.
    • 6th place (Top 2%), ROD Challenge, ACM International Conference on Multimedia Retrieval (ICMR), Apr. 2021.
    • Top-Performance Award, Social Media Prediction Challenge on ACM Multimedia, Oct. 2020.
    • 4th place, IEEE SPS Video and Image Processing Challenge CUP, IEEE International Conference on Image Processing (ICIP), Sept. 2020.
    • 3rd place, Visual Inductive Priors for Data-Efficient Computer Vision (VIPriors) Challenge (Semantic Segmentation track), European Conference on Computer Vision (ECCV), Aug. 2020.
    • 3rd place, Automatic Detection Challenge on Age-related Macular Degeneration (ADAM), IEEE International Symposium on Biomedical Imaging (ISBI), Apr. 2020.
    • 4th place, Grand Challenge: Embedded Deep Learning Object Detection Model Compression Competition for Traffic in Asian Countries, IEEE International Conference on Multimedia & Expo (ICME), Feb. 2020.
    • 3rd Place, Learning to Drive Challenge (Autonomous Driving Workshop), IEEE International Conference on Computer Vision (ICCV), Nov. 2019.
    • 5th Place, AIM Real-World Image Super-Resolution Challenge: Track1, Nov. ICCV, 2019
    • Best Student Paper Award (from 2071 submissions), IEEE International Conference on Image Processing (ICIP), Sept. 2019
    • 3rd Place, Vehicle Re-identification Challenge, IEEE International Conference on Visual Communications and Image Processing (VCIP), Dec. 2019.
    • 5nd Place, Embedded Deep Learning Object Detection Model Competition, International Workshop on Multimedia Signal Processing (MMSP), Oct. 2019.
    • Best-Performance Award, Social Media Prediction Challenge on ACM Multimedia, Oct. 2019.
    • Top-Performance Award, Social Media Headline Prediction Challenge on ACM Multimedia, Oct. 2018.

    Domestic Awards

    • Excellent Master Thesis Award, TAAI, Dec. 2022. (Student: Guan-Lin Chen)
    • Best Master Thesis Award, Chinese Statistical Association(Taiwan), Dec. 2022. (Student: Guan-Lin Chen)
    • Excellent Master Thesis Award, IPPR Conference on Computer Vision, Graphics, and Image Processing (CVGIP), Aug. 2022. (Student: Guan-Lin Chen)
    • Excellent Paper Award*2, IPPR Conference on Computer Vision, Graphics, and Image Processing (CVGIP), Aug. 2022.
    • Best Paper Award, CVGIP, Aug. 2021.

Refer to https://cchus.info