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2020 – today
- 2024
- [j27]Chia-Hsiang Lin, Cheng-Ying Hsieh, Jhao-Ting Lin:
CODE-IF: A Convex/Deep Image Fusion Algorithm for Efficient Hyperspectral Super-Resolution. IEEE Trans. Geosci. Remote. Sens. 62: 1-18 (2024) - [j26]Chia-Hsiang Lin, Chih-Chung Hsu, Si-Sheng Young, Cheng-Ying Hsieh, Shen-Chieh Tai:
QRCODE: Quasi-Residual Convex Deep Network for Fusing Misaligned Hyperspectral and Multispectral Images. IEEE Trans. Geosci. Remote. Sens. 62: 1-15 (2024) - [j25]Jhao-Ting Lin, Chia-Hsiang Lin:
SuperRPCA: A Collaborative Superpixel Representation Prior-Aided RPCA for Hyperspectral Anomaly Detection. IEEE Trans. Geosci. Remote. Sens. 62: 1-16 (2024) - [j24]Chia-Hsiang Lin, Si-Sheng Young:
Signal Subspace Identification for Incomplete Hyperspectral Image With Applications to Various Inverse Problems. IEEE Trans. Geosci. Remote. Sens. 62: 1-16 (2024) - [j23]Po-Wei Tang, Chia-Hsiang Lin, Yangrui Liu:
Transformer-Driven Inverse Problem Transform for Fast Blind Hyperspectral Image Dehazing. IEEE Trans. Geosci. Remote. Sens. 62: 1-14 (2024) - [j22]Chia-Hsiang Lin, Yangrui Liu, Chong-Yung Chi, Chih-Chung Hsu, Hsuan Ren, Tony Q. S. Quek:
Hyperspectral Tensor Completion Using Low-Rank Modeling and Convex Functional Analysis. IEEE Trans. Neural Networks Learn. Syst. 35(8): 10736-10750 (2024) - [c36]Shih-Min Hsu, Tzu-Hsuan Lin, Chia-Hsiang Lin:
HyperQUEEN-MF: Hyperspectral Quantum Deep Network with Multi-Scale Feature Fusion For Quantum Image Super-Resolution. SAM 2024: 1-5 - [c35]Chia-Hsiang Lin, Si-Sheng Young, Li-Yu Chang, Cynthia S. J. Liu:
Synthesis of High-Resolution Formosat-8 Satellite Image using Fast Convex Deep Learning Algorithm. IGARSS 2024: 7657-7661 - [c34]Chia-Hsiang Lin, Chen-Yu Kuo, Si-Sheng Young:
Quantum Adversarial Learning for Hyperspectral Remote Sensing. IGARSS 2024: 7807-7811 - 2023
- [j21]Chia-Hsiang Lin, You-Yao Chen:
HyperQUEEN: Hyperspectral Quantum Deep Network For Image Restoration. IEEE Trans. Geosci. Remote. Sens. 61: 1-20 (2023) - [j20]Chia-Hsiang Lin, Man-Chun Chu, Po-Wei Tang:
CODE-MM: Convex Deep Mangrove Mapping Algorithm Based on Optical Satellite Images. IEEE Trans. Geosci. Remote. Sens. 61: 1-19 (2023) - [j19]Tzu-Hsuan Lin, Chia-Hsiang Lin:
Hyperspectral Change Detection Using Semi-Supervised Graph Neural Network and Convex Deep Learning. IEEE Trans. Geosci. Remote. Sens. 61: 1-18 (2023) - [c33]Tzu-Hsuan Lin, Chia-Hsiang Lin, Si-Sheng Young:
GNN-Based Small-Data Learning with Area-Control Mechanism for Hyperspectral Satellite Change Detection. APSIPA ASC 2023: 726-732 - [c32]Chia-Hsiang Lin, You-Yao Chen:
Quantum Deep Hyperspectral Satellite Remote Sensing. IGARSS 2023: 7316-7319 - [c31]Si-Sheng Young, Chia-Hsiang Lin, Jhao-Ting Lin:
CiDAR-Former: Cosine-Weighting Deep Abundance Reconstruction Transformer for Fast Unsupervised Hyperspectral Anomaly Detection. WHISPERS 2023: 1-5 - 2022
- [j18]Pai-Chuan Chang, Jhao-Ting Lin, Chia-Hsiang Lin, Po-Wei Tang, Yangrui Liu:
Optimization-Based Hyperspectral Spatiotemporal Super-Resolution. IEEE Access 10: 37477-37494 (2022) - [j17]Lulu Chen, Chiung-Ting Wu, Chia-Hsiang Lin, Rujia Dai, Chunyu Liu, Robert Clarke, Guoqiang Yu, Jennifer E. Van Eyk, David M. Herrington, Yue Wang:
swCAM: estimation of subtype-specific expressions in individual samples with unsupervised sample-wise deconvolution. Bioinform. 38(5): 1403-1410 (2022) - [j16]Chi-Han Lee, Ronald Y. Chang, Shin-Ming Cheng, Chia-Hsiang Lin, Chiu-Han Hsiao:
Joint Beamforming and Power Allocation for M2M/H2H Co-Existence in Green Dynamic TDD Networks: Low-Complexity Optimal Designs. IEEE Internet Things J. 9(6): 4799-4815 (2022) - [j15]Chia-Hsiang Lin, Tzu-Hsuan Lin:
All-Addition Hyperspectral Compressed Sensing for Metasurface-Driven Miniaturized Satellite. IEEE Trans. Geosci. Remote. Sens. 60: 1-15 (2022) - [j14]Chia-Hsiang Lin, Yen-Cheng Lin, Po-Wei Tang:
ADMM-ADAM: A New Inverse Imaging Framework Blending the Advantages of Convex Optimization and Deep Learning. IEEE Trans. Geosci. Remote. Sens. 60: 1-16 (2022) - [c30]Jhao-Ting Lin, Chia-Hsiang Lin:
Real-Time Hyperspectral Anomaly Detection using Collaborative Superpixel Representation with Boundary Refinement. IGARSS 2022: 1752-1755 - [c29]Tzu-Hsuan Lin, Chia-Hsiang Lin:
Single Hyperspectral Image Super-Resolution Using Admm-Adam Theory. IGARSS 2022: 1756-1759 - [c28]Pai-Chuan Chang, Jhao-Ting Lin, Chia-Hsiang Lin, Po-Wei Tang, Yangrui Liu:
A Fast Multidimensional Data Fusion Algorithm For Hyperspectral Spatiotemporal Super-Resolution. WHISPERS 2022: 1-5 - [c27]Chia-Hsiang Lin, Man-Chun Chu, Hone-Jay Chu:
High-Dimensional Multiresolution Satellite Image Classification: An Approach Blending The Advantages Of Convex Optimization And Deep Learning. WHISPERS 2022: 1-5 - [c26]Chia-Hsiang Lin, Tzu-Hsuan Lin, Ting-Hsuan Lin, Tang-Huang Lin:
Fast Reconstruction of Hyperspectral Image From its RGB Counterpart Using ADMM-Adam Theory. WHISPERS 2022: 1-5 - [c25]Yangrui Liu, Chia-Hsiang Lin, Yu-Chun Kuo:
Low-Rank Representation With Morphological-Attribute-Filter Based Regularization For Hyperspectral Anomaly Detection. WHISPERS 2022: 1-5 - [c24]Po-Wei Tang, Chia-Hsiang Lin:
Hyperspectral Dehazing Using Admm-Adam Theory. WHISPERS 2022: 1-5 - 2021
- [j13]Chih-Chung Hsu, Chia-Hsiang Lin, Chi-Hung Kao, Yen-Cheng Lin:
DCSN: Deep Compressed Sensing Network for Efficient Hyperspectral Data Transmission of Miniaturized Satellite. IEEE Trans. Geosci. Remote. Sens. 59(9): 7773-7789 (2021) - [j12]Chia-Hsiang Lin, José M. Bioucas-Dias:
Nonnegative Blind Source Separation for Ill-Conditioned Mixtures via John Ellipsoid. IEEE Trans. Neural Networks Learn. Syst. 32(5): 2209-2223 (2021) - [c23]Chia-Hsiang Lin, Yen-Cheng Lin, Po-Wei Tang, Man-Chun Chu:
Deep Hyperspectral Tensor Completion Just Using Small Data. IGARSS 2021: 2480-2483 - [c22]Chia-Hsiang Lin, Cheng-Yu Sie, Pang-Yu Lin, Jhao-Ting Lin:
Fast Unsupervised Spatiotemporal Super-Resolution for Multispectral Satellite Imaging Using Plug-and-Play Machinery Strategy. IGARSS 2021: 2568-2571 - [c21]Chia-Hsiang Lin, Yangrui Liu:
Blind Hyperspectral Inpainting Via John Ellipsoid. WHISPERS 2021: 1-5 - [c20]Chia-Hsiang Lin, Po-Wei Tang:
Inverse Problem Transform: Solving Hyperspectral Inpainting Via Deterministic Compressed Sensing. WHISPERS 2021: 1-5 - [i7]Chandradeep Singh, Chia-Hsiang Lin:
Reconfigurable Intelligent Surfaces Aided Communication: Capacity and Performance Analysis Over Rician Fading Channel. CoRR abs/2107.10937 (2021) - [i6]Kamal Singh, Chandradeep Singh, Chia-Hsiang Lin:
Low SNR Capacity of Keyhole MIMO Channel in Nakagami-m Fading With Full CSI. CoRR abs/2109.01817 (2021) - [i5]Chandradeep Singh, Chia-Hsiang Lin, Kamal Singh:
Capacity and Performance Analysis of RIS-Assisted Communication Over Rician Fading Channels. CoRR abs/2111.04783 (2021) - 2020
- [j11]Chia-Hsiang Lin, José M. Bioucas-Dias:
An Explicit and Scene-Adapted Definition of Convex Self-Similarity Prior With Application to Unsupervised Sentinel-2 Super-Resolution. IEEE Trans. Geosci. Remote. Sens. 58(5): 3352-3365 (2020) - [c19]Chia-Hsiang Lin, José M. Bioucas-Dias, Tzu-Hsuan Lin, Yen-Cheng Lin, Chi-Hung Kao:
A New Hyperspectral Compressed Sensing Method for Efficient Satellite Communications. SAM 2020: 1-5 - [c18]Chih-Chung Hsu, Wen-Hai Tseng, Hao-Ting Yang, Chia-Hsiang Lin, Chi-Hung Kao:
Rethinking Relation between Model Stacking and Recurrent Neural Networks for Social Media Prediction. ACM Multimedia 2020: 4585-4589
2010 – 2019
- 2019
- [j10]Yao-Rong Syu, Chia-Hsiang Lin, Chong-Yung Chi:
An Outlier-Insensitive Unmixing Algorithm With Spatially Varying Hyperspectral Signatures. IEEE Access 7: 15086-15101 (2019) - [j9]Lina Zhuang, Chia-Hsiang Lin, Mário A. T. Figueiredo, José M. Bioucas-Dias:
Regularization Parameter Selection in Minimum Volume Hyperspectral Unmixing. IEEE Trans. Geosci. Remote. Sens. 57(12): 9858-9877 (2019) - [c17]Andreas Lugmayr, Nam Hyung Joon, Yu Seung Won, Guisik Kim, Dokyeong Kwon, Chih-Chung Hsu, Chia-Hsiang Lin, Yuanfei Huang, Xiaopeng Sun, Wen Lu, Jie Li, Martin Danelljan, Xinbo Gao, Sefi Bell-Kligler, Assaf Shocher, Michal Irani, Radu Timofte, Manuel Fritsche, Shuhang Gu, Kuldeep Purohit, Praveen Kandula, Maitreya Suin, A. N. Rajagopalan:
AIM 2019 Challenge on Real-World Image Super-Resolution: Methods and Results. ICCV Workshops 2019: 3575-3583 - [c16]Chih-Chung Hsu, Chia-Hsiang Lin:
Dual Reconstruction with Densely Connected Residual Network for Single Image Super-Resolution. ICCV Workshops 2019: 3643-3650 - [c15]Wei-Cheng Zheng, Chia-Hsiang Lin, Kuo-Hsin Tseng, Chih-Yuan Huang, Tang-Huang Lin, Chia-Hsiang Wang, Chong-Yung Chi:
Unsupervised Change Detection in Multitemporal Multispectral Satellite Images: A Convex Relaxation Approach. IGARSS 2019: 1546-1549 - [c14]Chia-Hsiang Wang, Chia-Hsiang Lin, José M. Bioucas-Dias, Wei-Cheng Zheng, Kuo-Hsin Tseng:
Panchromatic Sharpening of Multispectral Satellite Imagery Via an Explicitly Defined Convex Self-Similarity Regularization. IGARSS 2019: 3129-3132 - [i4]Andreas Lugmayr, Martin Danelljan, Radu Timofte, Manuel Fritsche, Shuhang Gu, Kuldeep Purohit, Praveen Kandula, Maitreya Suin, A. N. Rajagopalan, Nam Hyung Joon, Yu Seung Won, Guisik Kim, Dokyeong Kwon, Chih-Chung Hsu, Chia-Hsiang Lin, Yuanfei Huang, Xiaopeng Sun, Wen Lu, Jie Li, Xinbo Gao, Sefi Bell-Kligler:
AIM 2019 Challenge on Real-World Image Super-Resolution: Methods and Results. CoRR abs/1911.07783 (2019) - [i3]Chih-Chung Hsu, Chia-Hsiang Lin:
Dual Reconstruction with Densely Connected Residual Network for Single Image Super-Resolution. CoRR abs/1911.08711 (2019) - 2018
- [j8]Chia-Hsiang Lin, Ruiyuan Wu, Wing-Kin Ma, Chong-Yung Chi, Yue Wang:
Maximum Volume Inscribed Ellipsoid: A New Simplex-Structured Matrix Factorization Framework via Facet Enumeration and Convex Optimization. SIAM J. Imaging Sci. 11(2): 1651-1679 (2018) - [j7]Chia-Hsiang Lin, Fei Ma, Chong-Yung Chi, Chih-Hsiang Hsieh:
A Convex Optimization-Based Coupled Nonnegative Matrix Factorization Algorithm for Hyperspectral and Multispectral Data Fusion. IEEE Trans. Geosci. Remote. Sens. 56(3): 1652-1667 (2018) - [j6]Chia-Hsiang Lin, Chong-Yung Chi, Lulu Chen, David J. Miller, Yue Wang:
Detection of Sources in Non-Negative Blind Source Separation by Minimum Description Length Criterion. IEEE Trans. Neural Networks Learn. Syst. 29(9): 4022-4037 (2018) - [c13]Chia-Hsiang Lin, José M. Bioucas-Dias:
New Theory for Unmixing ILL-Conditioned Hyperspectral Mixtures. SAM 2018: 430-434 - [c12]Chia-Hsiang Lin, José M. Bioucas-Dias:
Linear Spectral Unmixing via Matrix Factorization: Identifiability Criteria for Sparse Abundances. IGARSS 2018: 6155-6158 - [c11]Chia-Hsiang Lin, José M. Bioucas-Dias:
Provably and Roubst Blind Source Seperation of Ill-Conditioned Hyperspectral Mixtures. SSP 2018: 333-337 - 2017
- [j5]Guixian Xu, Chia-Hsiang Lin, Weiguo Ma, Shanzhi Chen, Chong-Yung Chi:
Outage Constrained Robust Hybrid Coordinated Beamforming for Massive MIMO Enabled Heterogeneous Cellular Networks. IEEE Access 5: 13601-13616 (2017) - [c10]Guixian Xu, Chia-Hsiang Lin, Weiguo Ma, Chong-Yung Chi:
Outage constrained robust hybrid coordinated beamforming for massive MIMO enabled heterogeneous cellular networks. ICC 2017: 1-7 - 2016
- [j4]Arul-Murugan Ambikapathi, Tsung-Han Chan, Chia-Hsiang Lin, Fei-Shih Yang, Chong-Yung Chi, Yue Wang:
Convex-Optimization-Based Compartmental Pharmacokinetic Analysis for Prostate Tumor Characterization Using DCE-MRI. IEEE Trans. Biomed. Eng. 63(4): 707-720 (2016) - [j3]Chia-Hsiang Lin, Chong-Yung Chi, Yu-Hsiang Wang, Tsung-Han Chan:
A Fast Hyperplane-Based Minimum-Volume Enclosing Simplex Algorithm for Blind Hyperspectral Unmixing. IEEE Trans. Signal Process. 64(8): 1946-1961 (2016) - 2015
- [j2]Chia-Hsiang Lin, Wing-Kin Ma, Wei-Chiang Li, Chong-Yung Chi, Arul-Murugan Ambikapathi:
Identifiability of the Simplex Volume Minimization Criterion for Blind Hyperspectral Unmixing: The No-Pure-Pixel Case. IEEE Trans. Geosci. Remote. Sens. 53(10): 5530-5546 (2015) - [c9]Chia-Hsiang Lin, Chong-Yung Chi, Yu-Hsiang Wang, Tsung-Han Chan:
A fast hyperplane-based MVES algorithm for hyperspectral unmixing. ICASSP 2015: 1384-1388 - [c8]Wing-Kin Ma, Chia-Hsiang Lin, Wei-Chiang Li, Chong-Yung Chi:
When can the minimum volume enclosing simplex identify the endmembers correctly when there is no pure pixel? WHISPERS 2015: 1-4 - [i2]Chia-Hsiang Lin, Chong-Yung Chi, Yu-Hsiang Wang, Tsung-Han Chan:
A Fast Hyperplane-Based Minimum-Volume Enclosing Simplex Algorithm for Blind Hyperspectral Unmixing. CoRR abs/1510.08917 (2015) - 2014
- [i1]Chia-Hsiang Lin, Wing-Kin Ma, Wei-Chiang Li, Chong-Yung Chi, Arul-Murugan Ambikapathi:
Identifiability of the Simplex Volume Minimization Criterion for Blind Hyperspectral Unmixing: The No Pure-Pixel Case. CoRR abs/1406.5273 (2014) - 2013
- [c7]Chia-Hsiang Lin, Arul-Murugan Ambikapathi, Wei-Chiang Li, Chong-Yung Chi:
On the endmember identifiability of Craig's criterion for hyperspectral unmixing: A statistical analysis for three-source case. ICASSP 2013: 2139-2143 - [c6]Arul-Murugan Ambikapathi, Tsung-Han Chan, Chia-Hsiang Lin, Chong-Yung Chi:
Convex geometry based outlier-insensitive estimation of number of endmembers in hyperspectral images. WHISPERS 2013: 1-4 - 2010
- [j1]Chia-Hsiang Lin, Chun-Yu Hsieh, Ke-Horng Chen:
A Li-Ion Battery Charger With Smooth Control Circuit and Built-In Resistance Compensator for Achieving Stable and Fast Charging. IEEE Trans. Circuits Syst. I Regul. Pap. 57-I(2): 506-517 (2010)
2000 – 2009
- 2008
- [c5]Chia-Hsiang Lin, Hong-Wei Huang, Ke-Horng Chen:
Fast transient technique (FTT) in buck current-mode DC-DC converters for low-voltage SoC systems. CICC 2008: 25-28 - [c4]Chia-Hsiang Lin, Hong-Wei Huang, Ke-Horng Chen:
Built-in resistance compensation (BRC) technique for fast charging Li-Ion battery charger. CICC 2008: 33-36 - [c3]Hong-Wei Huang, Chia-Hsiang Lin, Ke-Horng Chen:
High-performance low-dropout regulator achieved by fast transient mechanism. ESSCIRC 2008: 350-353 - [c2]Chia-Hsiang Lin, Chi-Lin Chen, Yu-Huei Lee, Shih-Jung Wang, Chun-Yu Hsieh, Hong-Wei Huang, Ke-Horng Chen:
Fast charging technique for Li-Ion battery charger. ICECS 2008: 618-621 - [c1]Hong-Wei Huang, Chia-Hsiang Lin, Ke-Horng Chen:
A programmable dual hysteretic window comparator. ISCAS 2008: 1930-1933
Coauthor Index
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last updated on 2024-11-08 20:30 CET by the dblp team
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