國立成功大學電機工程學系 教師個人頁面
English Version
林家祥 副教授
地址
電機系館9樓92907室
Email
TEL
06-2757575 ext.62335
實驗室網站連結
高光譜智慧運算實驗室
(R92931/ext.62400-1666)
學經歷
學歷
清華大學電機系(2010)
清華大學通訊所(2016)
經歷
2014，香港中文大學，研究助理
2015-2016，美國維吉尼亞理工，研究助理
2017，香港中文大學，博士後
2017-2018，葡萄牙里斯本大學，博士後
2018，中央大學太空遙測中心，助理教授
2019-2021，成功大學電機系，助理教授
2019-2021，成功大學敏求學院，助理教授
2019，葡萄牙里斯本大學，訪問教授
2022-2023，成功大學數據科學中心《演算法與最佳化組》，組長
2022-2024，臺灣太空科學聯盟《資料分析及軟體研發組》，Affiliated Member
2023-2025，成功大學國際事務處《國際關係組》，組長
2022-present，成功大學敏求學院，副教授
2022-present，成功大學電機系，副教授
2024-present，臺灣太空科學聯盟《國際合作組》，Affiliated Member
2024-present，國家理論中心《數學組》，Affiliated Member
2025-present，中國工程師學會高雄市分會《資訊組》，副組長
研究領域
  • 太空遙測 / 衛星數據分析
  • 高光譜 / 多光譜 / RGB影像處理
  • 盲訊號處理 / 非監督式機器學習
  • 人工智慧 / 機器學習 / 深度學習
  • 量子深度學習 / 量子經典混合式AI
  • 量子影像處理 / 量子機器學習
  • 快速演算法設計 / 凸優化理論
  • 3D光學異物檢測 / 影像超解析
  • 3D電腦視覺 / 模式識別
  • 生物醫學 / 腦科學
  • 5G/6G無線通訊
著作
期刊論文( Journal )
more
less
  1. Chia-Hsiang Lin, W.-H. Li, S.-M. Hsu, and H.-J. Chu, “A full-spectrum time-reversal deep network for label imbalance learning: A case study with novel ground-truth labeling strategy for mangrove forest change detection,” IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2025.
  2. P.-W. Tang, Chia-Hsiang Lin, J.-K. Huang, and A. R. Huete, “A quantum-empowered SPEI drought forecasting algorithm using spatially-aware mamba network,” IEEE Transactions on Geoscience and Remote Sensing, 2025.
  3. Chia-Hsiang Lin, and S.-S. Young, “HyperKING: Quantum-classical generative adversarial networks for hyperspectral image restoration,” IEEE Transactions on Geoscience and Remote Sensing, 2025.
  4. Chia-Hsiang Lin, Z.-C. Leng, C.-H. Yu, L. Bharali, C.-L. Lin, B.-H. Mao, and T.-Y. Tu, “Microscopic-based analysis of nuclei in spheroids via SUNSHINE: An on-chip workflow integrating optical clearing, fluorescence calibration and supervoxel segmentation,” Computers in Biology and Medicine, 2025.
  5. Chia-Hsiang Lin, and J.-T. Lin, “PRIME: Unsupervised multispectral unmixing using virtual quantum prism and convex geometry,” IEEE Transactions on Geoscience and Remote Sensing, 2025.
  6. Chia-Hsiang Lin, P.-W. Tang, and A. R. Huete, “Quantum feature-empowered deep classification for fast mangrove mapping,” IEEE Transactions on Geoscience and Remote Sensing, 2024.
  7. Chia-Hsiang Lin, T.-H. Lin, and J. Chanussot, “Quantum information-empowered graph neural network for hyperspectral change detection,” IEEE Transactions on Geoscience and Remote Sensing, 2024
  8. J.-T. Lin, and Chia-Hsiang Lin, “SuperRPCA: A collaborative superpixel representation prior-aided RPCA for hyperspectral anomaly detection,” IEEE Transactions on Geoscience and Remote Sensing, 2024.
  9. S.-S. Young, Chia-Hsiang Lin, and Z.-C. Leng, “Unsupervised abundance matrix reconstruction transformer guided fractional attention mechanism for hyperspectral anomaly detection,” IEEE Transactions on Neural Networks and Learning Systems, 2024.
  10. Chia-Hsiang Lin, C.-Y. Hsieh, and J.-T. Lin, “CODE-IF: A convex/deep image fusion algorithm for efficient hyperspectral super-resolution,” IEEE Transactions on Geoscience and Remote Sensing, 2024.
  11. Chia-Hsiang Lin, and S.-S. Young, “Signal subspace identification for incomplete hyperspectral image with applications to various inverse problems,” IEEE Transactions on Geoscience and Remote Sensing, 2024.
  12. Chia-Hsiang Lin, C.-C. Hsu, S.-S. Young, C.-Y. Hsieh, and S.-C. Tai, “QRCODE: Quasi-Residual Convex Deep Network for Fusing Misaligned Hyperspectral and Multispectral Images,” IEEE Transactions on Geoscience and Remote Sensing, vol. 62, pp. 1-15, 2024.
  13. P.-W. Tang, Chia-Hsiang Lin, and Y.-R. Liu,“Transformer-driven inverse problem transform for fast blind hyperspectral image dehazing,” IEEE Transactions on Geoscience and Remote Sensing, 2024.
  14. Chia-Hsiang Lin, S.-H. Huang, T.-H. Lin, and P.-C. Wu, “Metasurface-empowered snapshot hyperspectral imaging with convex/deep (CODE) small-data learning theory,” Nature Communications, 2023.
  15. Chia-Hsiang Lin, M.-C. Chu, and P.-W. Tang,“CODE-MM: Convex deep mangrove mapping algorithm based on optical satellite images,” IEEE Transactions on Geoscience and Remote Sensing, 2023.
  16. Chia-Hsiang Lin, and T.-H. Lin, "Hyperspectral change detection using semi-supervised graph neural network and convex deep learning," IEEE Transactions on Geoscience and Remote Sensing, vol. 61, pp. 1-18, 2023.
  17. Chia-Hsiang Lin, and Y.-Y. Chen, “HyperQUEEN: Hyperspectral quantum deep network for image restoration,” IEEE Transactions on Geoscience and Remote Sensing, vol. 61, pp. 1-20, 2023.
  18. Chia-Hsiang Lin, Y. Liu, C.-Y. Chi, C.-C. Hsu, H. Ren, and T. Q. S. Quek, “Hyperspectral tensor completion using low-rank modeling and convex functional analysis,” IEEE Transactions on Neural Networks and Learning Systems, 2023.
  19. P.-C. Chuan, J.-T. Lin, Chia-Hsiang Lin, P.-W. Tang, and Y. Liu, “Optimization-based hyperspectral spatiotemporal super-resolution,” IEEE Access, vol. 10, pp. 37477-37494, 2022.
  20. C.-H. Lee, R. Chang, S.-M. Cheng, Chia-Hsiang Lin, and C.-H. Hsiao, “Joint beamforming and power allocation for M2M/H2H co-existence in green dynamic TDD networks: Low-complexity optimal designs,” IEEE Internet of Things Journal, vol. 9, no. 6, pp. 4799-4815, 2022.
  21. L. Chen, C.-T. Wu, Chia-Hsiang Lin, R. Dai, C. Liu, R. Clarke, G. Yu, J. E. Van Eyk, D. M. Herrington, and Y. Wang, “swCAM: estimation of subtype-specific expressions in individual samples with unsupervised sample-wise deconvolution,” Bioinformatics, vol. 38, no, 5, pp. 1403-1410, 2022.
  22. Chia-Hsiang Lin, Y.-C. Lin, and P.-W. Tang, “ADMM-ADAM: A new inverse imaging framework blending the advantages of convex optimization and deep learning,” IEEE Transactions on Geoscience and Remote Sensing, vol. 60, pp. 1-16, 2021.
  23. Chia-Hsiang Lin, Y.-S. Chen, J.-T. Lin, H.-C. Wu, H.-T. Kuo, C.-F. Lin, P. Chen, and P.-C. Wu, “Automatic inverse design of high-performance beam-steering metasurfaces via genetic-type tree optimization,” Nano Letters, vol. 21, no. 12, pp. 4981-4989, 2021.
  24. Chia-Hsiang Lin and J. M. Bioucas-Dias, “Nonnegative blind source separation for ill-conditioned mixtures via John ellipsoid,” IEEE Transactions on Neural Networks and Learning Systems, vol. 32, no. 5, pp. 2209-2223, May 2021.
  25. Chia-Hsiang Lin and T.-H. Lin, “All-addition hyperspectral compressed sensing for metasurface-driven miniaturized satellite,” IEEE Transactions on Geoscience and Remote Sensing, vol. 60, pp. 1-15, 2021.
  26. C.-C. Hsu, Chia-Hsiang Lin, C.-H. Kao, and Y.-C. Lin, “DCSN: Deep compressed sensing network for efficient hyperspectral data transmission of miniaturized satellite,” IEEE Transactions on Geoscience and Remote Sensing, vol. 59, no. 9, pp. 7773-7789, 2020.
  27. Chia-Hsiang Lin and J. M. Bioucas-Dias, “An explicit and scene-adapted definition of convex self-similarity prior with application to unsupervised Sentinel-2 super-resolution,” IEEE Transactions on Geoscience and Remote Sensing, vol. 58, no. 5, pp. 3352-3365, May 2020.
  28. L. Zhuang, Chia-Hsiang Lin, M. A. T. Figueiredo, and J. M. Bioucas-Dias, “Regularization parameter selection in minimum volume hyperspectral unmixing,” IEEE Transactions on Geoscience and Remote Sensing, vol. 57, no. 12, pp. 9858-9877, Dec. 2019.
  29. Y.-R. Syu, Chia-Hsiang Lin, C.-Y. Chi, “An outlier-insensitive unmixing algorithm with spatially varying hyperspectral signatures,” IEEE Access, vol. 7, pp. 15086-15101, Jan. 2019.
  30. Chia-Hsiang Lin, C.-Y. Chi, L. Chen, D. J. Miller, and Y. Wang, “Detection of sources in non-negative blind source separation by minimum description length criterion,” IEEE Transactions on Neural Networks and Learning Systems, vol. 29, no. 9, pp. 4022-4037, Sep. 2018.
  31. Chia-Hsiang Lin, R. Wu, W.-K. Ma, C.-Y. Chi, and Y. Wang, “Maximum volume inscribed ellipsoid: A new simplex-structured matrix factorization framework via facet enumeration and convex optimization,” SIAM Journal on Imaging Sciences, vol. 11, no. 2, pp. 1651-1679, 2018.
  32. Chia-Hsiang Lin, F. Ma, C.-Y. Chi, and C.-H. Hsieh, “A convex optimization based coupled non-negative matrix factorization algorithm for hyperspectral and multispectral data fusion,” IEEE Transactions on Geoscience and Remote Sensing, vol. 56, no. 3, pp. 1652-1667, Mar. 2018.
  33. G. Xu, Chia-Hsiang Lin, W. Ma, S. Chen, and C.-Y. Chi, “Outage constrained robust hybrid coordinated beamforming for massive MIMO enabled heterogeneous cellular networks,” IEEE Access, vol. 5, pp. 13601-13616, Mar. 2017.
  34. Chia-Hsiang Lin, C.-Y. Chi, Y.-H. Wang, and T.-H. Chan, “A fast hyperplane-based minimum-volume enclosing simplex algorithm for blind hyperspectral unmixing,” IEEE Transactions on Signal Processing, vol. 64, no. 8, pp. 1946-1961, Apr. 2016.
  35. A. Ambikapathi, T.-H. Chan, Chia-Hsiang Lin, F.-S. Yang, C.-Y. Chi, and Y. Wang, “Convex optimization-based compartmental pharmacokinetic analysis for prostate tumor characterization using DCE-MRI,” IEEE Transactions on Biomedical Engineering, vol. 63, no. 4, pp. 707-720, Apr. 2016.
  36. Chia-Hsiang Lin, W.-K. Ma, W.-C. Li, C.-Y. Chi, and A. Ambikapathi, “Identifiability of the simplex volume minimization criterion for blind hyperspectral unmixing: The no pure-pixel case,” IEEE Transactions on Geoscience and Remote Sensing, vol. 53, no. 10, pp. 5530-5546, Oct. 2015.
會議論文( Conference )
more
less
  1. Chia-Hsiang Lin, C.-Y. Liang, and P.-W. Tang, “μ-HCD: Annotation-free and scalable long short-term memory hyperspectral calibration for change detection,” IEEE WHISPERS, Bellaterra, Spain, Nov. 12-14, 2025.
  2. Chia-Hsiang Lin, S.-S. Young, and R. Langari, “Quantum fuzzy detection of anomaly objects using hyperspectral generative adversarial learning,” IEEE WHISPERS, Bellaterra, Spain, Nov. 12-14, 2025.
  3. Chia-Hsiang Lin, J.-T. Chen, and S.-M. Hsu, “Interpretable Sentinel-converted hyperspectral data using deep image prior and spatiospectral super-resolution deep unfolding,” IEEE WHISPERS, Bellaterra, Spain, Nov. 12-14, 2025.
  4. S.-J. Huang, Chia-Hsiang Lin, and P.-W. Tang “Quantum-inspired deep hyperspectral dehazing algorithm,” IEEE WHISPERS, Bellaterra, Spain, Nov. 12-14, 2025.
  5. S.-S. Young, Chia-Hsiang Lin, S.-J. Huang, and S.-Q. Chen, “Fuzzy-driven quantum detection with spatial-frequency hyperspectral network,” IPPR Conference on Computer Vision, Graphics, and Image Processing, Taipei, Taiwan, Aug. 24-26, 2025.
  6. Chia-Hsiang Lin, and S.-S. Young, “Quantum-inspired virtual prism for multispectral unmixing,” IEEE IGARSS, Brisbane, Australia, Aug. 3-8, 2025.
  7. Chia-Hsiang Lin, P.-W. Tang, J.-K. Huang, C. Kung, and A. R. Huete, “Quantum-assisted mangrove forest mapping algorithm,” IEEE IGARSS, Brisbane, Australia, Aug. 3-8, 2025.
  8. Chia-Hsiang Lin, P.-Y. Chiu, J.-T. Lin, S.-P. Chen, and Charles Lin, “HydroQUEEN: Hydrological detection using CYGNSS and quantum deep AI,” IEEE IGARSS, Brisbane, Australia, Aug. 3-8, 2025.
  9. Chia-Hsiang Lin, T.-H. Lin, C.-Y. Liang, and J. Chanussot, “Hybrid quantum-classical network for hyperspectral change detection,” IEEE IGARSS, Brisbane, Australia, Aug. 3-8, 2025.
  10. Chia-Hsiang Lin, S.-S. Young, C. Liu, L.-Y. Chang, and T.-Y. Liao, “Image resolution enhancing of Sentinel-2 red edge bands via Pléiades-1 multispectral data and fast convex deep learning,” SPIE Asia-Pacific Remote Sensing Symposium, Kaohsiung, Taiwan, Dec. 2-4, 2024.
  11. C.-W. Fan, C.-F. Cheng, Z.-C. Leng, C. Hsu, Chia-Hsiang Lin, and Y.-N. Chang, “A fast unsupervised small-data-driven neuroimaging algorithm for detection of Alzheimer's disease,” TSBME Global Conference on Biomedical Engineering (GCBME), Tainan, Taiwan, Nov. 1-3, 2024.
  12. Z.-C. Leng, B.-H. Mao, C.-H. Yu, Chia-Hsiang Lin, and T.-Y. Tu, “Evaluation of cell nuclei in spheroids using SENSE: A method combining fluorescence calibration and supervoxel segmentation techniques,” TSBME Global Conference on Biomedical Engineering (GCBME), Tainan, Taiwan, Nov. 1-3, 2024.
  13. S.-S. Young, Chia-Hsiang Lin, J.-Y. Chen, and J.-K. Huang, “HyperQUEEN-CD: Quantum neural network for unsupervised hyperspectral change detection,” IPPR Conference on Computer Vision, Graphics, and Image Processing, Hualien, Taiwan, Aug. 18-20, 2024.
  14. G.-J. Wei, Chia-Hsiang Lin, and S.-M. Hsu, “A channel-wise quantum attention mechanism for RGB and hyperspectral image super-resolution,” IPPR Conference on Computer Vision, Graphics, and Image Processing, Hualien, Taiwan, Aug. 18-20, 2024.
  15. (Invited Paper) S.-M. Hsu, T.-H. Lin, and Chia-Hsiang Lin, “HyperQUEEN-MF: Hyperspectral quantum deep network with multi-scale feature fusion for quantum image super-resolution,” accepted by IEEE SAM, Corvallis, OR, USA, July 8-11, 2024.
  16. Chia-Hsiang Lin, C.-Y. Kuo, and S.-S. Young, “Quantum adversarial learning for hyperspectral remote sensing,” IEEE IGARSS, Athens, Greece, July 7-12, 2024.
  17. Chia-Hsiang Lin, S.-S. Young, L.-Y. Chang, and Cynthia S.J. Liu, “Synthesis of high-resolution FORMOSAT-8 satellite image using fast convex deep learning algorithm,” IEEE IGARSS, Athens, Greece, July 7-12, 2024.
  18. S.-S. Young, Chia-Hsiang Lin, and J.-T. Lin, “CiDAR-Former: Cosine-weighting deep abundance reconstruction transformer for fast unsupervised hyperspectral anomaly detection,” IEEE WHISPERS, Athens, Greece, Oct. 31-Nov. 2, 2023.
  19. (Invited Paper) T.-H. Lin, and Chia-Hsiang Lin, and S.-S. Young, “GNN-based small-data learning with area-control mechanism for hyperspectral satellite change detection,” Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC), Taipei, Taiwan, Oct. 31-Nov. 3, 2023.
  20. Chia-Hsiang Lin, and Y.-Y. Chen, “Quantum deep hyperspectral satellite remote sensing,” IEEE IGARSS, Pasadena, California, July 16-21, 2023.
  21. Chia-Hsiang Lin, M.-C. Chu, and H.-J. Chu, “High-dimensional multiresolution satellite image classification: An approach blending the advantages of convex optimization and deep learning,” IEEE WHISPERS, Rome, Italy, Sep. 13-16, 2022.
  22. Chia-Hsiang Lin, T.-H. Lin, T.-H. Lin, and T.-H. Lin, “Fast reconstruction of hyperspectral image from its RGB counterpart using ADMM-Adam theory,” IEEE WHISPERS, Rome, Italy, Sep. 13-16, 2022.
  23. Y. Liu, Chia-Hsiang Lin, and Y.-C. Kuo, “Low-rank representation with morphological-attribute-filter based regularization for hyperspectral anomaly detection,” IEEE WHISPERS, Rome, Italy, Sep. 13-16, 2022.
  24. P.-W. Tang, and Chia-Hsiang Lin, “Hyperspectral dehazing using ADMM-Adam theory,” IEEE WHISPERS, Rome, Italy, Sep. 13-16, 2022.
  25. P.-C. Chuan, J.-T. Lin, Chia-Hsiang Lin, P.-W. Tang, and Y. Liu, “A fast multidimensional data fusion algorithm for hyperspectral spatiotemporal super-resolution,” IEEE WHISPERS, Rome, Italy, Sep. 13-16, 2022.
  26. Chia-Hsiang Lin, M.-C. Chu, and T.-H. Lin, “Convex optimization aided deep classification of ESA's Sentinel-2 satellite image,” IPPR Conference on Computer Vision, Graphics, and Image Processing, Nantou, Taiwan, Aug. 18-20, 2022.
  27. Chia-Hsiang Lin, T.-H. Lin, Y.-Y. Lai, K.-H. Yu, and T.-H. Lin, “Reconstructing hyperspectral image from its RGB counterpart: An approach blending deep learning and convex optimization,” IPPR Conference on Computer Vision, Graphics, and Image Processing, Nantou, Taiwan, Aug. 18-20, 2022.
  28. Chia-Hsiang Lin, C.-C. Hsu, S.-W. Jian, and Y.-C. Kuo, “Convex feature-aligned quasiresidual network for alignment-free deep high-dimensional image fusion,” IPPR Conference on Computer Vision, Graphics, and Image Processing, Nantou, Taiwan, Aug. 18-20, 2022.
  29. Y. Liu, Chia-Hsiang Lin, Z.-C. Leng, and C.-Y. Hsieh, “Convex hyperspectral anomaly detection algorithm using random dictionary without column-sparsity-promoting regularization,” IPPR Conference on Computer Vision, Graphics, and Image Processing, Nantou, Taiwan, Aug. 18-20, 2022.
  30. T.-H. Lin, and Chia-Hsiang Lin, “Single hyperspectral image super-resolution using ADMM-Adam theory,” IEEE IGARSS, Kuala Lumpur, Malaysia, July 17-22, 2022.
  31. J.-T. Lin, and Chia-Hsiang Lin, “Real-time hyperspectral anomaly detection using collaborative superpixel representation with boundary refinement,” IEEE IGARSS, Kuala Lumpur, Malaysia, July 17-22, 2022.
  32. C.-H. Yu, Z.-C. Leng, Y. Liu, J.-Y. Huang, Chia-Hsiang Lin, and T.-Y. Tu, “A total solutioning workflow for sample processing and precise nuclei quantification in 3D tumor spheroids using unsupervised algorithm,” World Congress of Biomechanics, Taipei, Taiwan, Jul. 10-14, 2022.
  33. A. Hassanfiroozi, Chia-Hsiang Lin, J.-T. Lin, and P.-C. Wu, “High-performance metasurfaces for wavefront engineering,” Materials Research Society Fall Meeting & Exhibit, Boston, MA, USA, Nov. 28 - Dec. 3, 2021.
  34. C.-H. Kao, Chia-Hsiang Lin, S.-W. Jian, and P.-Y. Lin, “Solving hyperspectral single-image super-resolution via fusion-based inverse problem transform,” The 34th IPPR Conference on Computer Vision, Graphics, and Image Processing, Taipei, Taiwan, Aug. 22-24, 2021.
  35. Chia-Hsiang Lin, Y.-S. Chen, J.-T. Lin, Y.-C. Cheng, A. Hassanfiroozi, H.-C. Wu, H.-T. Kuo, and P.-C. Wu, “Toward high-performance plasmonic metasurfaces: From forward to inverse design approach,” SPIE Optics and Photonics, San Diego, CA, USA, Aug. 1-5, 2021.
  36. Chia-Hsiang Lin, C.-Y. Sie, P.-Y. Lin, and J.-T. Lin, “Fast unsupervised spatiotemporal super-resolution for multispectral satellite imaging using plug-and-play machinery strategy,” IEEE IGARSS, Brussels, Belgium, July 11-16, 2021.
  37. Chia-Hsiang Lin, Y.-C. Lin, P.-W. Tang, and M.-C. Chu, “Deep hyperspectral tensor completion just using small data,” IEEE IGARSS, Brussels, Belgium, July 11-16, 2021.
  38. Chia-Hsiang Lin and P.-W. Tang, “Inverse problem transform: Solving hyperspectral inpainting via deterministic compressed sensing,” IEEE WHISPERS, Amsterdam, Netherlands, Mar. 24-26, 2021.
  39. Chia-Hsiang Lin and Y. Liu, “Blind hyperspectral inpainting via John ellipsoid,” IEEE WHISPERS, Amsterdam, Netherlands, Mar. 24-26, 2021.
  40. Chia-Hsiang Lin, Y.-S. Chen, J.-T. Lin, and P.-C. Wu, “Inverse design of non-periodical metasurfaces via high-performance automatic optimization,” Optics & Photonics Taiwan International Conference (OPTIC), Taipei, Taiwan, Dec. 3-5, 2020.
  41. (Invited Paper) (Top Performance Award) C.-C. Hsu, W.-H. Zheng, H.-T. Yang, Chia-Hsiang Lin, and C.-H. Kao, “Rethinking relation between model stacking and recurrent neural networks for social media prediction,” ACM Multimedia, Seattle, WA, USA, Oct. 12-16, 2020.
  42. Y.-C. Hung*, Chia-Hsiang Lin*, F.-Y. Wang, and S.-H. Yang, “Penetrating terahertz hyperspectral unmixing via Löwner-John ellipsoid: An unsupervised algorithm,” International Conference on Infrared, Millimeter, and Terahertz Waves (IRMMW-THz), Buffalo, NY, USA, Sep. 13-18, 2020. (*Contributed Equally)
  43. (Invited Paper) C.-C. Hsu, Y.-C. Lin, C.-H. Kao, and Chia-Hsiang Lin, “Deep joint compression and super-resolution low-rank network for fast hyperspectral data transmission,” The 33rd IPPR Conference on Computer Vision, Graphics, and Image Processing, Hsinchu, Taiwan, Aug. 16-18, 2020.
  44. (Invited Paper) T.-H. Lin, Chia-Hsiang Lin, Y. Liu, and C.-H. Kao, “A simple spatial-spectral proximal compression method for high-dimensional imagery with proximal computing based blind reconstruction,” The 33rd IPPR Conference on Computer Vision, Graphics, and Image Processing, Hsinchu, Taiwan, Aug. 16-18, 2020.
  45. (Invited Paper) (Outstanding Paper Award) C.-Y. Sie, Chia-Hsiang Lin, P.-W. Tang, and Y.-C. Lin, “Solving the algebraic hyperspectral inpainting problem: A fast hyperplane geometry based approach,” The 33rd IPPR Conference on Computer Vision, Graphics, and Image Processing, Hsinchu, Taiwan, Aug. 16-18, 2020.
  46. (Invited Paper) Chia-Hsiang Lin, J. M. Bioucas-Dias, T.-H. Lin, Y.-C. Lin, and C.-H. Kao, “A new hyperspectral compressed sensing method for efficient satellite communications,” IEEE SAM, Hangzhou, China, June 8-11, 2020.
  47. W.-C. Zheng, K.-H. Tseng, and Chia-Hsiang Lin, “Unsupervised change detection using convex relaxation and dynamic threshold selection in remotely sensed images ,” American Geophysical Union (AGU) Fall Meeting, San Francisco, CA, USA, Dec. 9-13, 2019.
  48. (Invited Paper) C.-C. Hsu, and Chia-Hsiang Lin, “Dual reconstruction with densely connected residual network for single image super-resolution,” IEEE International Conference on Computer Vision (ICCV), Seoul, Korea, Oct. 27 - Nov. 2, 2019.
  49. T.-Y. Lin, H. Ren, and Chia-Hsiang Lin, “Bathymetry estimation via convex geometry in multispectral satellite imagery: A case study in Dongsha Atoll,” The 38th Conference on Surveying and Geoinformatics, Taoyuan, Taiwan, Aug. 29-30, 2019.
  50. C.-H. Wang, K.-H. Tseng, and Chia-Hsiang Lin, “Waterline detection using fusion based super-resolution of multispectral satellite image with self-similarity,” The 38th Conference on Surveying and Geoinformatics, Taoyuan, Taiwan, Aug. 29-30, 2019.
  51. W.-C. Zheng, Chia-Hsiang Lin, K.-H. Tseng, C.-Y. Huang, T.-H. Lin, C.-H. Wang, and C.-Y. Chi, “Unsupervised change detection in multitemporal multispectral satellite images: A convex relaxation approach,” IEEE IGARSS, Yokohama, Japan, July 28 - Aug. 2, 2019.
  52. (Interactive Session Prize Paper Award) C.-H. Wang, Chia-Hsiang Lin, J. M. Bioucas-Dias, W.-C. Zheng, K.-H. Tseng, “Panchromatic sharpening of multispectral satellite imagery via an explicitly defined convex self-similarity regularization” IEEE IGARSS, Yokohama, Japan, July 28 - Aug. 2, 2019.
  53. W-C. Zheng, Chia-Hsiang Lin, K.-H. Tseng, C.-Y. Huang, and T.-H. Lin, “Criterion design and large-scale optimization algorithm for blind change detection in multispectral images,” International Symposium on Remote Sensing, Taipei, Taiwan, Apr. 17-19, 2019.
  54. C.-H. Wang, Chia-Hsiang Lin, and K.-H. Tseng, “Patch similarity guided super-resolution algorithm for fusing panchromatic and multispectral images,” International Symposium on Remote Sensing, Taipei, Taiwan, Apr. 17-19, 2019.
  55. Chia-Hsiang Lin and J. M. Bioucas-Dias, “Linear spectral unmixing via matrix factorization: Identifiability criteria for sparse abundances,” in Proc. IEEE IGARSS, Valencia, Spain, July 23-27, 2018.
  56. (Invited Paper) Chia-Hsiang Lin and J. M. Bioucas-Dias, “New theory for unmixing ill-conditioned hyperspectral mixtures,” in Proc. IEEE SAM, Sheffield, UK, July 8-11, 2018.
  57. Chia-Hsiang Lin and J. M. Bioucas-Dias, “Provably and robust blind source separation of ill-conditioned hyperspectral mixtures,” in Proc. IEEE SSP, Freiburg, Germany, June 10-13, 2018.
  58. G. Xu, Chia-Hsiang Lin, W. Ma, and C.-Y. Chi, “Outage constrained robust hybrid coordinated beamforming for massive MIMO enabled heterogeneous cellular networks,” in Proc. IEEE ICC, Paris, France, May 21-25, 2017.
  59. W.-K. Ma, Chia-Hsiang Lin, W.-C. Li, and C.-Y. Chi, “When can the minimum volume enclosing simplex identify the endmembers correctly when there is no pure pixel?,” in Proc. IEEE WHISPERS, Tokyo, Japan, June 2-5, 2015.
  60. Chia-Hsiang Lin, C.-Y. Chi, Y.-H. Wang, and T.-H. Chan, “A fast hyperplane-based MVES algorithm for hyperspectral unmixing,” in Proc. IEEE ICASSP, Brisbane, Australia, Apr. 19-24, 2015.
  61. (Invited Paper) A. Ambikapathi, T.-H. Chan, Chia-Hsiang Lin, and C.-Y. Chi, “Convex geometry based outlier-insensitive estimation of number of endmembers in hyperspectral images,” in Proc. IEEE WHISPERS, Gainesville, Florida, USA, June 25-28, 2013.
  62. Chia-Hsiang Lin, A. Ambikapathi, W.-C. Li, and C.-Y. Chi, “On the endmember identifiability of Craig’s criterion for hyperspectral unmixing: A statistical analysis for three-source case,” in Proc. IEEE ICASSP, Vancouver, Canada, May 26-31, 2013.
專利
more
less
其他
more
less
  1. [書籍著作] C.-Y. Chi, W.-C. Li, and Chia-Hsiang Lin, Convex Optimization for Signal Processing and Communications: From Fundamentals to Applications, CRC Press, Boca Raton, FL, Feb. 2017. (432 pages)
  2. [書籍著作] 電子工業出版社，「信號處理與通信中的凸優化：從基礎到應用」（作者：祁忠勇、李威錆、林家祥）（譯者：陳翔、沉超），2020年12月出版。
  3. [技術轉移] 獲授權公司：元太科技工業股份有限公司；技術名稱：基於非量子或量子深度學習之空間抖色，2024
研究計劃
  1. 基於非量子或量子深度學習之空間抖色，元太科技工業股份有限公司，主持人，2024~2027
  2. 國家重點領域國際合作聯盟「113年度整合型計畫」：新太空世代跨領域能量建構與鍵結：基於量子人工智能與凸演算法之光學衛星異物偵測，教育部，主持人，2024~2026
  3. 永續躍升計畫「拔尖案」：應用智慧水下載具與深度學習強化影像分析建構台灣沿海生態系統高時間解析觀測平台(共同主持)，教育部，2025~2026
  4. 超皇后：深度量子高光譜太空遙測，國科會(2030跨世代年輕學者方案「新秀學者研究計畫」)，主持人，2023~2027
  5. 應用智慧運算方法進行衛星紅邊波段影像模擬研究，國家太空中心，主持人，2023~2024
  6. 前瞻衛星成像之數學理論與超穎光柵設計，教育部，主持人，2019~2022
  7. 建構動態地電阻譜：整合數值解析法暨災防應用(共同主持)，教育部，2019
  8. 基於凸幾何與大數據優化之前瞻盲蔽訊號源分離與高光譜超解析度成像，科技部(愛因斯坦培植計畫)，主持人，2018~2023
開授課程
107學年度下學期
108學年度上學期
108學年度下學期
109學年度上學期
109學年度下學期
110學年度上學期
110學年度下學期
111學年度上學期
111學年度下學期
112學年度上學期
112學年度下學期
113學年度上學期
113學年度下學期
114學年度上學期
指導學生
本學年度 實驗室成員
博士班
林子亘
湯柏緯
林昭廷
甯子釗
楊斯盛
許奭民
龔哲
黃建凱
碩士班
李維恆
陳之硯
范城瑋
梁詠升
林瑋浚
林伯育
柳辰諭
黃詩哲
陳芮庭
邱柏穎
梁菁芸
劉韋志
邱于恩
張光德
專題生
陳 蓁
魏子翔
郭智翔
張騏斐
特殊榮譽
  1. 李國鼎研究獎 K. T. Li Research Award, 2025.
  2. Outstanding Patent, Center for Corporate Relations and Technology Transfer, NCKU, 2025. (企業關係與技轉中心優質專利徵選)
  3. Excellent Poster Exhibition Award, Communications Engineering Program, National Science and Technology Council, 2025.
  4. IEEE Senior Member, 2024.
  5. 臺灣綜合大學「年輕學者創新研發優等獎」（工程領域）Excellence Award from Young Scholar Innovative R&D Results Selection of Taiwan Comprehensive University System, 2024.
  6. GENESYS Logic Paper Excellence Award, 2024. (創惟科技論文「卓越獎」36 萬)
  7. Excellent EMI Teaching Innovation Award of University Social Responsibility (USR) from NCKU, 2024. (教學創新與大學社會責任：EMI創新教學優良教師)
  8. 中華民國青年獎章（學術拔萃類）The Republic of China Youth Medal Award, 2024.
  9. Excellent Poster Exhibition Award, Communications Engineering Program, National Science and Technology Council, 2024.
  10. 國科會 2030 跨世代「新秀學者」Emerging Young Scholar Award from National Science and Technology Council (2030 Cross-Generation Young Scholars Program), from 2023 to 2027.
  11. Teaching Excellence Award from NCKU, 2023. (校級教學優良獎)
  12. Excellent Mentor Award from NCKU, 2023. (輔導優良導師)
  13. Excellent Poster Exhibition Award, Communications Engineering Program, National Science and Technology Council, 2023.
  14. 中國電機工程學會「優秀青年電機工程師獎」Outstanding Youth Electrical Engineer Award from The Chinese Institute of Electrical Engineering, 2022.
  15. FutureTech Award from National Science & Technology Council, 2022. (國科會「未來科技獎」)
  16. Outstanding Paper Award (x2) from IPPR Conference on Computer Vision, Graphics, and Image Processing (CVGIP), 2022.
  17. Excellent Poster Exhibition Award, Communications Engineering Program, Ministry of Science and Technology, 2022.
  18. IEEE 中華民國第一分會「最佳年輕學者」Best Young Professional Member Award from IEEE Tainan Section, 2021.
  19. Outstanding Paper Award from IPPR Conference on Computer Vision, Graphics, and Image Processing (CVGIP), 2021.
  20. Excellent Research Project Award, Communications Engineering Program, Ministry of Science and Technology, 2021.
  21. Top Performance Award, Social Media Prediction Challenge, ACM Multimedia, 2020.
  22. Outstanding Paper Award from IPPR Conference on Computer Vision, Graphics, and Image Processing (CVGIP), 2020.
  23. Symposium Interactive Session Prize Paper Award (IGARSS'19) from IEEE Geoscience & Remote Sensing Society, 2020.
  24. 3rd Place (Objective) and 5th Place (Subjective), AIM Real World Super-Resolution Challenge, IEEE International Conference on Computer Vision (ICCV), 2019.
  25. 科技部「愛因斯坦學者」Einstein Grant Award from Ministry of Science and Technology, from 2018 to 2023.
  26. Best Doctoral Dissertation Award from IEEE Geoscience & Remote Sensing Society, 2016.
  27. Outstanding Doctoral Dissertation Award from Chinese Image Processing and Pattern Recognition (IPPR) Society, 2016.
NCKU EE