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2020 – today
- 2023
[j10]Chih-Chung Hsu, Li-Wei Kang
, Shih-Yu Chen, I-Shan Wang, Ching-Hao Hong, Chuan-Yu Chang:
Deep learning-based vehicle trajectory prediction based on generative adversarial network for autonomous driving applications. Multim. Tools Appl. 82(7): 10763-10780 (2023)- [j9]Guan-Lin Chen, Chih-Chung Hsu:
Jointly Defending DeepFake Manipulation and Adversarial Attack Using Decoy Mechanism. IEEE Trans. Pattern Anal. Mach. Intell. 45(8): 9922-9931 (2023) - [c44]Ju-Yeh Yang, Tsung-Chun Lee, Chih-Yu Jian, Chih-Chung Hsu:
Multimodality-aware Intra-dialytic Hypotension Classifier: A Bilingual NLP Approach to Classify Dialysis Records. BCB 2023: 82:1 - [c43]Chih-Chung Hsu, Chih-Yu Jian, Chia-Ming Lee, Chi-Han Tsai, Shen-Chieh Tai:
Bag of Tricks of Hybrid Network for Covid-19 Detection of CT Scans. ICASSP Workshops 2023: 1-4 - [c42]Chih-Chung Hsu, Pi-Ju Tsai:
Identical Twins Verification with Fine-grained Recognition. ICCE-Taiwan 2023: 75-76 - [c41]Chih-Chung Hsu, Sophia Yang, Xiu-Yu Hou, Yu-An Jhang:
Prior-Guided Parallel Residual Bi-Fusion Network in USV Obstacle Detection. ICCE-Taiwan 2023: 107-108 - [c40]Chih-Chung Hsu, Pei-Jun Lee:
FPGA Implementation of Floating Point Linear Programming. ICSSE 2023: 152-156 - [c39]Chih-Chung Hsu, Yu-An Jhang, Min-Tso Ko:
Seeing is Not Believing: Toward Forgery Detection for Hyperspectral Image. IGARSS 2023: 5858-5861 - [c38]Chih-Chung Hsu, Chia-Ming Lee, Xiu-Yu Hou, Chi-Han Tsai:
Gradient Boost Tree Network based on Extensive Feature Analysis for Popularity Prediction of Social Posts. ACM Multimedia 2023: 9451-9455 - [c37]Benjamin Kiefer, Matej Kristan, Janez Pers, Lojze Zust, Fabio Poiesi, Fabio Augusto de Alcantara Andrade, Alexandre Bernardino, Matthew Dawkins, Jenni Raitoharju, Yitong Quan, Adem Atmaca, Timon Höfer, Qiming Zhang, Yufei Xu, Jing Zhang, Dacheng Tao, Lars Sommer, Raphael Spraul, Hangyue Zhao, Hongpu Zhang, Yanyun Zhao, Jan Lukas Augustin, Eui-ik Jeon, Impyeong Lee, Luca Zedda, Andrea Loddo, Cecilia Di Ruberto, Sagar Verma, Siddharth Gupta, Shishir Muralidhara, Niharika Hegde, Daitao Xing, Nikolaos Evangeliou, Anthony Tzes, Vojtech Bartl, Jakub Spanhel, Adam Herout, Neelanjan Bhowmik, Toby P. Breckon, Shivanand Kundargi, Tejas Anvekar, Ramesh Ashok Tabib, Uma Mudengudi, Arpita Vats, Yang Song, Delong Liu, Yonglin Li, Shuman Li, Chenhao Tan, Long Lan, Vladimir Somers, Christophe De Vleeschouwer, Alexandre Alahi, Hsiang-Wei Huang, Cheng-Yen Yang, Jenq-Neng Hwang, Pyong-Kun Kim, Kwangju Kim, Kyoungoh Lee, Shuai Jiang, Haiwen Li, Zheng Ziqiang, Tuan-Anh Vu, Hai Nguyen-Truong, Sai-Kit Yeung, Zhuang Jia, Sophia Yang, Chih-Chung Hsu, Xiu-Yu Hou, Yu-An Jhang, Simon Yang, Mau-Tsuen Yang:
1st Workshop on Maritime Computer Vision (MaCVi) 2023: Challenge Results. WACV (Workshops) 2023: 265-302 - [i13]Chih-Chung Hsu, Chih-Yu Jian, Chia-Ming Lee, Chi-Han Tsai, Sheng-Chieh Dai:
Strong Baseline and Bag of Tricks for COVID-19 Detection of CT Scans. CoRR abs/2303.08490 (2023) - 2022
- [j8]Chih-Chung Hsu, Chia-Yen Lee, Cheng-Jhong Lin, Hung Yeh:
A comprehensive study of age-related macular degeneration detection. Multim. Tools Appl. 81(9): 11897-11916 (2022) - [j7]Huihui Fang, Fei Li, Huazhu Fu, Xu Sun, Xingxing Cao, Fengbin Lin, Jaemin Son, Sunho Kim, Gwenolé Quellec, Sarah Matta, Sharath M. Shankaranarayana, Yi-Ting Chen, Chuen-heng Wang, Nisarg A. Shah, Chia-Yen Lee, Chih-Chung Hsu, Hai Xie, Baiying Lei, Ujjwal Baid, Shubham Innani, Kang Dang, Wenxiu Shi, Ravi Kamble, Nitin Singhal, Ching-Wei Wang, Shih-Chang Lo, José Ignacio Orlando, Hrvoje Bogunovic, Xiulan Zhang, Yanwu Xu:
ADAM Challenge: Detecting Age-Related Macular Degeneration From Fundus Images. IEEE Trans. Medical Imaging 41(10): 2828-2847 (2022) - [c36]Chih-Chung Hsu, Chi-Han Tsai, Guan-Lin Chen, Sin-Di Ma, Shen-Chieh Tai:
Spatial-Slice Feature Learning Using Visual Transformer and Essential Slices Selection Module for COVID-19 Detection of CT Scans in the Wild. ECCV Workshops (7) 2022: 621-634 - [c35]Bor-Sheng Huang, Chih-Chung Hsu, Wo-Ting Liao, Han-Yi Kao, Xian-Yun Wang:
DCSN: Deformable Convolutional Semantic Segmentation Neural Network for Non-Rigid Scenes. ICASSP 2022: 4668-4672 - [c34]Chih-Chung Hsu, Sin-Di Ma:
Few-Shot Semantic Segmentation based on Detail-Preserving-Aware Loss. ICCE-TW 2022: 581-582 - [c33]Chih-Chung Hsu, Sheng-Jay Dai, Shao-Ning Chen:
COVID-19 Infection Percentage Prediction via Boosted Hierarchical Vision Transformer. ICIAP Workshops 2022: 529-535 - [c32]Chih-Chung Hsu, Chieh Lee, Shen-Chieh Tai, Yun-Zhong Jiang:
Augmented-Training-Aware Bisenet for Real-Time Semantic Segmentation. ICME Workshops 2022: 1-6 - [c31]Sophia Yang, Jun-Teng Zhang, Chia-Wen Lin, Chih-Chung Hsu:
GAN-Based Criminal Suspect Face Generator. ICS 2022: 329-340 - [c30]Chih-Chung Hsu, Pi-Ju Tsai, Ting-Chun Yeh, Xiu-Yu Hou:
A Comprehensive Study of Spatiotemporal Feature Learning for Social Medial Popularity Prediction. ACM Multimedia 2022: 7130-7134 - [i12]Huihui Fang, Fei Li, Huazhu Fu, Xu Sun, Xingxing Cao, Fengbin Lin, Jaemin Son, Sunho Kim, Gwenolé Quellec, Sarah Matta, Sharath M. Shankaranarayana, Yi-Ting Chen, Chuen-heng Wang, Nisarg A. Shah, Chia-Yen Lee, Chih-Chung Hsu, Hai Xie, Baiying Lei, Ujjwal Baid, Shubham Innani, Kang Dang, Wenxiu Shi, Ravi Kamble, Nitin Singhal, José Ignacio Orlando, Hrvoje Bogunovic, Xiulan Zhang, Yanwu Xu:
ADAM Challenge: Detecting Age-related Macular Degeneration from Fundus Images. CoRR abs/2202.07983 (2022) - [i11]Chih-Chung Hsu, Chi-Han Tsai, Guan-Lin Chen, Sin-Di Ma, Shen-Chieh Tai:
Spatiotemporal Feature Learning Based on Two-Step LSTM and Transformer for CT Scans. CoRR abs/2207.01579 (2022) - [i10]Benjamin Kiefer, Matej Kristan, Janez Pers, Lojze Zust, Fabio Poiesi, Fabio Augusto de Alcantara Andrade, Alexandre Bernardino, Matthew Dawkins, Jenni Raitoharju, Yitong Quan, Adem Atmaca, Timon Höfer, Qiming Zhang, Yufei Xu, Jing Zhang, Dacheng Tao, Lars Sommer, Raphael Spraul, Hangyue Zhao, Hongpu Zhang, Yanyun Zhao, Jan Lukas Augustin, Eui-ik Jeon, Impyeong Lee, Luca Zedda, Andrea Loddo, Cecilia Di Ruberto, Sagar Verma, Siddharth Gupta, Shishir Muralidhara, Niharika Hegde, Daitao Xing, Nikolaos Evangeliou, Anthony Tzes, Vojtech Bartl, Jakub Spanhel, Adam Herout, Neelanjan Bhowmik, Toby P. Breckon, Shivanand Kundargi, Tejas Anvekar, Chaitra Desai, Ramesh Ashok Tabib, Uma Mudengudi, Arpita Vats, Yang Song, Delong Liu, Yonglin Li, Shuman Li, Chenhao Tan, Long Lan, Vladimir Somers, Christophe De Vleeschouwer, Alexandre Alahi, Hsiang-Wei Huang, Cheng-Yen Yang, Jenq-Neng Hwang, Pyong-Kun Kim, Kwangju Kim, Kyoungoh Lee, Shuai Jiang, Haiwen Li, Zheng Ziqiang, Tuan-Anh Vu, Hai Nguyen-Truong, Sai-Kit Yeung, Zhuang Jia, Sophia Yang, Chih-Chung Hsu, Xiu-Yu Hou, Yu-An Jhang, Simon Yang, Mau-Tsuen Yang:
1st Workshop on Maritime Computer Vision (MaCVi) 2023: Challenge Results. CoRR abs/2211.13508 (2022) - 2021
- [j6]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) - [c29]Chia-Hung Yeh, Daniel Chiu, Li-Wei Kang, Chih-Chung Hsu, Chen Lo:
Generative Adversarial Networks-based Face Hallucination with Identity-Preserving. ICCE-TW 2021: 1-2 - [c28]Guan-Lin Chen, Chih-Chung Hsu, Mei-Hsuan Wu:
Adaptive Distribution Learning with Statistical Hypothesis Testing for COVID-19 CT Scan Classification. ICCVW 2021: 471-479 - [c27]Chih-Chung Hsu, Chieh Lee, Lin Chen, Min-Kai Hung, Andy Yu-Lun Lin, Xian-Yu Wang:
Efficient-ROD: Efficient Radar Object Detection based on Densely Connected Residual Network. ICMR 2021: 526-532 - [i9]Andrey Ignatov, Cheng-Ming Chiang, Hsien-Kai Kuo, Anastasia Sycheva, Radu Timofte, Min-Hung Chen, Man-Yu Lee, Yu-Syuan Xu, Yu Tseng, Shusong Xu, Jin Guo, Chao-Hung Chen, Ming-Chun Hsyu, Wen-Chia Tsai, Chao-Wei Chen, Grigory Malivenko, Minsu Kwon, Myungje Lee, Jaeyoon Yoo, Changbeom Kang, Shinjo Wang, Zheng Shaolong, Hao Dejun, Xie Fen, Feng Zhuang, Yipeng Ma, Jingyang Peng, Tao Wang, Fenglong Song, Chih-Chung Hsu, Kwan-Lin Chen, Mei-Hsuang Wu, Vishal M. Chudasama, Kalpesh Prajapati, Heena Patel, Anjali Sarvaiya, Kishor P. Upla, Kiran B. Raja, Raghavendra Ramachandra, Christoph Busch, Etienne de Stoutz:
Learned Smartphone ISP on Mobile NPUs with Deep Learning, Mobile AI 2021 Challenge: Report. CoRR abs/2105.07809 (2021) - [i8]Chih-Chung Hsu, Guan-Lin Chen, Mei-Hsuan Wu:
Visual Transformer with Statistical Test for COVID-19 Classification. CoRR abs/2107.05334 (2021) - 2020
- [c26]Chih-Chung Hsu, Wen-Hai Tseng, Hao-Ting Yang:
Learning to Predict Risky Driving Behaviors for Autonomous Driving. ICCE-TW 2020: 1-2 - [c25]Chih-Chung Hsu, Kuan-Yu Huang:
Coupled Adversarial Learning for Single Image Super-Resolution. SAM 2020: 1-5 - [c24]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 - [i7]Chih-Chung Hsu, Hsin-Ti Ma:
Edge-Preserving Guided Semantic Segmentation for VIPriors Challenge. CoRR abs/2007.08919 (2020)
2010 – 2019
- 2019
- [j5]Chih-Chung Hsu, Chia-Wen Lin, Weng-Tai Su, Gene Cheung:
SiGAN: Siamese Generative Adversarial Network for Identity-Preserving Face Hallucination. IEEE Trans. Image Process. 28(12): 6225-6236 (2019) - [c23]Chih-Chung Hsu, Hsin-Ti Ma, Jun-Yi Lee:
SSSNet: Small-Scale-Aware Siamese Network for Gastric Cancer Detection. AVSS 2019: 1-5 - [c22]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 - [c21]Chih-Chung Hsu, Chia-Hsiang Lin:
Dual Reconstruction with Densely Connected Residual Network for Single Image Super-Resolution. ICCV Workshops 2019: 3643-3650 - [c20]Yi-Xiu Zhuang, Chih-Chung Hsu:
Detecting Generated Image Based on a Coupled Network with Two-Step Pairwise Learning. ICIP 2019: 3212-3216 - [c19]Chih-Chung Hsu, Li-Wei Kang, Chia-Yen Lee, Jun-Yi Lee, Zhong-Xuan Zhang, Shao-Min Wu:
Popularity Prediction of Social Media based on Multi-Modal Feature Mining. ACM Multimedia 2019: 2687-2691 - [c18]Chih-Chung Hsu, Cing-Hao Hung, Chih-Yu Jian, Yi-Xiu Zhuang:
Stronger Baseline for Vehicle Re-Identification in the Wild. VCIP 2019: 1-4 - [i6]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) - [i5]Chih-Chung Hsu, Chia-Hsiang Lin:
Dual Reconstruction with Densely Connected Residual Network for Single Image Super-Resolution. CoRR abs/1911.08711 (2019) - 2018
- [j4]Chih-Chung Hsu, Chia-Wen Lin:
CNN-Based Joint Clustering and Representation Learning with Feature Drift Compensation for Large-Scale Image Data. IEEE Trans. Multim. 20(2): 421-429 (2018) - [c17]Weng-Tai Su, Chih-Chung Hsu, Ziling Huang, Chia-Wen Lin, Gene Cheung:
Joint Pairwise Learning and Image Clustering Based on a Siamese CNN. ICIP 2018: 1992-1996 - [c16]Chih-Chung Hsu, Chia-Yen Lee, Ting-Xuan Liao, Jun-Yi Lee, Tsai-Yne Hou, Ying-Chu Kuo, Jing-Wen Lin, Ching-Yi Hsueh, Zhong-Xuan Zhang, Hsiang-Chin Chien:
An Iterative Refinement Approach for Social Media Headline Prediction. ACM Multimedia 2018: 2008-2012 - [i4]Chih-Chung Hsu, Chia-Wen Lin, Weng-Tai Su, Gene Cheung:
SiGAN: Siamese Generative Adversarial Network for Identity-Preserving Face Hallucination. CoRR abs/1807.08370 (2018) - [i3]Chih-Chung Hsu, Chia-Yen Lee, Ting-Xuan Liao, Jun-Yi Lee, Tsai-Yne Hou, Ying-Chu Kuo, Jing-Wen Lin, Ching-Yi Hsueh, Zhong-Xuan Zhan, Hsiang-Chin Chien:
An Iterative Refinement Approach for Social Media Headline Prediction. CoRR abs/1809.08753 (2018) - [i2]Chih-Chung Hsu, Chia-Yen Lee, Yi-Xiu Zhuang:
Learning to Detect Fake Face Images in the Wild. CoRR abs/1809.08754 (2018) - 2017
- [c15]Chih-Chung Hsu, Chia-Wen Lin:
Unsupervised convolutional neural networks for large-scale image clustering. ICIP 2017: 390-394 - [c14]Chih-Chung Hsu, Ying-Chin Lee, Ping-En Lu, Shian-Shin Lu, Hsiao-Ting Lai, Ching-Chu Huang, Chun Wang, Yang-Jiun Lin, Weng-Tai Su:
Social Media Prediction Based on Residual Learning and Random Forest. ACM Multimedia 2017: 1865-1870 - [c13]Chih-Chung Hsu, Chia-Wen Lin:
Objective quality assessment for video retargeting based on spatio-temporal distortion analysis. VCIP 2017: 1-4 - [i1]Chih-Chung Hsu, Chia-Wen Lin:
CNN-Based Joint Clustering and Representation Learning with Feature Drift Compensation for Large-Scale Image Data. CoRR abs/1705.07091 (2017) - 2016
- [c12]Weng-Tai Su, Chih-Chung Hsu, Chia-Wen Lin, Weiyao Lin:
Supervised-learning based face hallucination for enhancing face recognition. ICASSP 2016: 1751-1755 - 2015
- [j3]Chih-Chung Hsu, Li-Wei Kang, Chia-Wen Lin:
Temporally Coherent Superresolution of Textured Video via Dynamic Texture Synthesis. IEEE Trans. Image Process. 24(3): 919-931 (2015) - [j2]Li-Wei Kang, Chih-Chung Hsu, Boqi Zhuang, Chia-Wen Lin, Chia-Hung Yeh:
Learning-Based Joint Super-Resolution and Deblocking for a Highly Compressed Image. IEEE Trans. Multim. 17(7): 921-934 (2015) - 2014
- [j1]Chih-Chung Hsu, Chia-Wen Lin, Yuming Fang, Weisi Lin:
Objective Quality Assessment for Image Retargeting Based on Perceptual Geometric Distortion and Information Loss. IEEE J. Sel. Top. Signal Process. 8(3): 377-389 (2014) - [c11]Chih-Chung Hsu, Li-Wei Kang, Chia-Wen Lin:
Video super-resolution via dynamic texture synthesis. MMSP 2014: 1-6 - 2013
- [c10]Li-Wei Kang, Bo-Chi Chuang, Chih-Chung Hsu, Chia-Wen Lin, Chia-Hung Yeh:
Self-learning-based single image super-resolution of a highly compressed image. MMSP 2013: 224-229 - [c9]Chih-Chung Hsu, Chia-Wen Lin, Yuming Fang, Weisi Lin:
Objective quality assessment for image retargeting based on perceptual distortion and information loss. VCIP 2013: 1-6 - 2011
- [c8]Chih-Chung Hsu, Chia-Wen Lin:
Image super-resolution via feature-based affine transform. MMSP 2011: 1-5 - [c7]Chun-Yu Lin, Chih-Chung Hsu, Chia-Wen Lin, Li-Wei Kang:
Fast deconvolution-based image super-resolution using gradient prior. VCIP 2011: 1-4 - 2010
- [c6]Chih-Chung Hsu, Chia-Wen Lin, Chiou-Ting Hsu, Hong-Yuan Mark Liao, Jen-Yu Yu:
Face hallucination using Bayesian global estimation and local basis selection. MMSP 2010: 449-453
2000 – 2009
- 2009
- [c5]Chih-Chung Hsu, Chia-Wen Lin, Chiou-Ting Hsu, Hong-Yuan Mark Liao:
Cooperative face hallucination using multiple references. ICME 2009: 818-821 - 2008
- [c4]Chih-Chung Hsu, Hsuan-Ting Chang:
Accelerating vector quantization of images using modified run length coding for adaptive block representation and difference measurement. ISCAS 2008: 3494-3497 - [c3]Chih-Chung Hsu, Tzu-Yi Hung, Chia-Wen Lin, Chiou-Ting Hsu:
Video forgery detection using correlation of noise residue. MMSP 2008: 170-174 - 2007
- [c2]Chih-Chung Hsu, Hsuan-Ting Chang, Ting Cheng Chang:
An Improved Face Detection Method in Low-resolution Video. IIH-MSP 2007: 419-422 - 2006
- [c1]Chih-Chung Hsu, Hsuan-Ting Chang, Ting Cheng Chang:
Efficient Moving Object Extraction in Compressed Low-Bit-Rate Video. IIH-MSP 2006: 411-414
Coauthor Index
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