{"id":514,"date":"1900-12-01T08:06:00","date_gmt":"1900-12-01T00:06:00","guid":{"rendered":"https:\/\/cchsu.info\/?p=514"},"modified":"2024-03-04T09:06:55","modified_gmt":"2024-03-04T01:06:55","slug":"full-publications","status":"publish","type":"post","link":"https:\/\/cchsu.info\/wordpress\/1900\/12\/01\/full-publications\/","title":{"rendered":"Full Publications"},"content":{"rendered":"<p><strong><u>Journal Papers<\/u><\/strong><\/p>\n<ul>\n<li>G.L. Chen and <strong>C.C. Hsu<\/strong>*, &#8220;Jointly Defending DeepFake Manipulation and Adversarial Attack using Decoy Mechanism,&#8221; <em>IEEE Transactions on Pattern Analysis and Machine Intelligence (<\/em><span style=\"color: #ff0000;\">IF: 24.31, 2\/276=1%<\/span>), to appear.<\/li>\n<li>C.H. Lin, Y. Liu, C.Y. Chi, <strong>C.C. Hsu<\/strong>, H. Ren, &amp; T.Q. Quek, &#8220;Hyperspectral Tensor Completion Using Low-Rank Modeling and Convex Functional Analysis,&#8221; <i>IEEE Transactions on Neural Networks and Learning Systems (<\/i><span style=\"color: #ff0000;\">IF:14.225, 5\/276=2%<\/span><i>), to appear.<\/i><\/li>\n<li>J.Y. Yang, T.C. Lee, W.T. Liao, <strong>C.C. Hsu*<\/strong>, &#8220;Multi-Head Self-Attention Mechanism Enabled Individualized Hemoglobin Prediction and Treatment Recommendation Systems in Anemia Management for Hemodialysis Patients,&#8221; in <em>Heliyon <\/em>(<span style=\"color: #ff0000;\">IF: 2.85, Rank: 27\/138=19% Q1<\/span>), (accepted)<\/li>\n<li><strong>C.C. Hsu<\/strong>, et al., &#8220;Deep Learning-based Vehicle Trajectory Prediction based on Generative Adversarial Network for Autonomous Driving Applications,&#8221; <span lang=\"EN-US\"><i>Multimedia Tools and Applications<\/i> (IF: 2.77, Rank 32\/137=23% Q1), to appear.\u00a0<\/span><\/li>\n<li>C.Y. Wei, W.Y. Huang, C.Y. Jian, C.C.H. Hsu, <strong>C.C. Hsu<\/strong>, et al., &#8220;Semantic segmentation guided detector for segmentation, classification, and lesion mapping of acute ischemic stroke in MRI images,&#8221; in <em><span class=\"il\">NeuroImage<\/span>:\u00a0<span class=\"il\">Clinical <\/span><\/em><span class=\"il\">(<span style=\"color: #ff0000;\">IF: 4.88, Rank 29\/288=10%<\/span>)<\/span><em><span class=\"il\">, (accepted)<\/span><\/em><\/li>\n<li>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,<strong> C.-C. Hsu<\/strong> et al., &#8220;ADAM Challenge: Detecting Age-related Macular Degeneration from Fundus Images,&#8221; in <em>IEEE Transactions on Medical Imaging <\/em>(<span style=\"color: #ff0000;\">IF: 10.05, Rank=21\/693=3%<\/span>), doi: 10.1109\/TMI.2022.3172773, May 2022.<\/li>\n<li><b><span lang=\"EN-US\">C.C. Hsu,<\/span><\/b><span lang=\"EN-US\">\u00a0et al., \u201cA Comprehensive Study of Age-related Macular Degeneration Detection,\u201d\u00a0<i>Multimedia Tools and Applications<\/i> (IF: 2.75, Rank 32\/137=23% Q1), 81.9, 11897-11916, 2022.<\/span><\/li>\n<li><strong>C.C. Hsu<\/strong>, C. -H. Lin, C. -H. Kao and Y. -C. Lin, &#8220;DCSN: Deep Compressed Sensing Network for Efficient Hyperspectral Data Transmission of Miniaturized Satellite,&#8221; in <em>IEEE Transactions on Geoscience and Remote Sensing<\/em>, vol. 59, no. 9, pp. 7773-7789, Sept. 2021. (<span style=\"color: #ff0000;\">IF: 5.85, Rank 29\/1409=2%<\/span> in Electrical and Electronic Engineering)<\/li>\n<li><strong>C.C. Hsu<\/strong>, Y. X. Zhuang, and C. Y. Lee, &#8220;Deep Fake Image Detection Based on Pairwise Learning,&#8221; <em>Appl Sci-Basel, <\/em>vol. 10, no. 1, p. 370, Jan 2020. (IF: 2.47, Rank 41\/275 in General Engineering)<\/li>\n<li><strong>C.C. Hsu<\/strong>, C. W. Lin, W. T. Su, and G. Cheung, &#8220;SiGAN: Siamese Generative Adversarial Network for Identity-Preserving Face Hallucination,&#8221; <em>IEEE Trans Image Process, <\/em>vol. 28, no. 12, pp. 6225-6236, Dec 2019. (IF:9.34, Rank: 5\/334=1% in Computer Graphics and Computer-Aided Design Software).<\/li>\n<li>C.Y. Lee, G.-L. Chen, Z.-X. Zhang, Y.-H. Chou, and <strong>C.C. Hsu<\/strong>*, &#8220;Is intensity inhomogeneity correction useful for classification of breast cancer in sonograms using deep neural network?,&#8221; <em>Journal of healthcare engineering, <\/em>vol. 2018, 2018. (*corresponding author) (IF:1.295, Rank:51\/150)<\/li>\n<li><strong>C. Hsu<\/strong> and C.-W. Lin, &#8220;Cnn-based joint clustering and representation learning with feature drift compensation for large-scale image data,&#8221; <em>IEEE Transactions on Multimedia, <\/em>vol. 20, no. 2, pp. 421-429, 2017. (IF:6.051, Rank: 2\/195=1% in Media Technology).<\/li>\n<li><strong>C. Hsu<\/strong>, L. Kang, and C. Lin, &#8220;Temporally Coherent Super-Resolution of Textured Video via Dynamic Texture Synthesis,&#8221; <em>IEEE Transactions on Image Processing, <\/em>vol. 24, no. 3, pp. 919 &#8211; 931, 2015. (IF:9.34, Rank: 5\/334=1% in Computer Graphics and Computer-Aided Design Software).<\/li>\n<li>L.W. Kang, <strong>C.C. Hsu<\/strong>, B. Q. Zhuang, C. W. Lin, and C. H. Yeh, &#8220;Learning-Based Joint Super-Resolution and Deblocking for a Highly Compressed Image,&#8221; <em>Ieee Transactions on Multimedia, <\/em>vol. 17, no. 7, pp. 921-934, Jul 2015. (IF:6.051, Rank: 2\/195=1% in Media Technology).<\/li>\n<li><strong>C.C. Hsu<\/strong>, C. W. Lin, Y. M. Fang, and W. S. Lin, &#8220;Objective Quality Assessment for Image Retargeting Based on Perceptual Geometric Distortion and Information Loss,&#8221; <em>Ieee Journal of Selected Topics in Signal Processing, <\/em>vol. 8, no. 3, pp. 377-389, Jun 2014. (IF:6.688, Rank: 7\/543=1% in Signal Processing).<\/li>\n<li>H.T. Chang, <strong>C.C. Hsu<\/strong>, C. H. Yeh, and D. F. Shen, &#8220;Image authentication with tampering localization based on watermark embedding in wavelet domain,&#8221; <em>Optical Engineering, <\/em>vol. 48, no. 5, p. 057002, May 2009. (IF:1.21, Rank:93\/264)<\/li>\n<\/ul>\n<p><strong><u>Book Chapters<\/u><\/strong><\/p>\n<ul>\n<li>T. Chang\u00a0and\u00a0<strong>C.C. Hsu<\/strong>, &#8220;Fractal-based Secured multiple-image distribution and compression,&#8221;\u00a0<em>in Handbook of Research on Secure Multimedia Distribution<\/em>, Chapter 27, Edited by Dr. Shiguo Lian and Dr. Yan Zhang, ISBN: 978-1-60566-262-6, 2008.<\/li>\n<\/ul>\n<p><strong><u>Conference Papers<\/u><\/strong><\/p>\n<ul>\n<li><strong>C. C. Hsu<\/strong>, Y. Z. Jiang, and W. H. Huang, &#8220;Swift Concurrent Semantic Segmentation and Object Detection on Edge Devices,&#8221; <em>IEEE International Conference on Multimedia and Expo (ICME) Workshop<\/em>, Brisbane, Australia, 10-14 July 2023.<\/li>\n<li><strong>C. C. Hsu<\/strong>, C.Y. Jian, C.M. Lee, C.H. Tsai, and S.C. Tai, &#8220;Bag of Tricks of Hybrid Network for COVID-19 Detection of CT Scans,&#8221;<em> IEEE International Conference on Acoustics, Speech, &amp; Signal Processing (ICASSP)<\/em>, June 2023.<\/li>\n<li><strong>C. C. Hsu<\/strong> and M.Z. Ke, &#8220;Seeing is NOT Believing: Toward Forgery Detection for Hyperspectral Image,&#8221;<em> IEEE International Geoscience and Remote Sensing Symposium (IGARSS)<\/em>, July 2023.<\/li>\n<li><strong>C.C. Hsu<\/strong>, C.H. Tsai, G.L. Chen, S.D. Ma, and S.C. Dai, &#8220;Spatial-Slice Feature Learning using Visual Transformer and Essential Slices Selection Module for COVID-19 Detection of CT Scans in the Wild,&#8221; <em>European Conference on Computer Vision (ECCV) Workshop<\/em>, 23-27 Oct. 2022.<\/li>\n<li><strong>C.C. Hsu<\/strong>, P.J. Tsai, T.C. Yeh, and X.U. Hou, &#8220;A Comprehensive Study of Spatiotemporal Feature Learning for Social Medial Popularity Prediction,&#8221; 30th <em>ACM international conference on Multimedia, <\/em>10-14 Oct. 2022.<\/li>\n<li><strong>C.C. Hsu<\/strong> and S.D. Ma, &#8220;Few-Shot Semantic Segmentation based on Detail-Preserving-Aware Loss,&#8221; in Prof. of<em> IEEE International Conference on Consumer Electronics \u2013 Taiwan<\/em>, Taiwan, July 6-8 2022.<\/li>\n<li><strong>C.C. Hsu<\/strong>, C. Lee, S. Tai, and Y. Jiang, &#8220;Augmented-Training-Aware Bisenet for Real-Time Semantic Segmentation,&#8221; <em>in 2022 IEEE International Conference on Multimedia and Expo Workshops (ICMEW)<\/em>, Taipei City, Taiwan, 2022 pp. 1-6.<\/li>\n<li><strong>C.C. Hsu<\/strong>, S.J. Dai, and S.N. Chen, &#8220;COVID-19 Infection Percentage Estimation via Boosted Hierarchical Vision Transformer,&#8221; in Proc. of <em>21st International Conference on Image Analysis and Processing<\/em>, LECCE, ITALY, May 23-27 2022.<\/li>\n<li>B.S. Huang, <strong>C.C. Hsu<\/strong>, W.T. Liao, H.Y. Kao, and X.Y. Wang, &#8220;DCSN: Deformable Convolutional Semantic Segmentation Neural Network for Non-Rigid Scenes,&#8221; <em>IEEE International Conference on Acoustics, Speech and Signal Processing<\/em> <em>(ICASSP)<\/em>, 22-27 May 2022.<\/li>\n<li>G.L. Chen, <strong>C.C. Hsu<\/strong>, and M.H. Wu, \u201cAdaptive Distribution Learning with Statistical Hypothesis Testing for COVID-19 CT Scan Classification,\u201d in Proc. of <em>IEEE\/CVF International Conference on Computer Vision Workshop (ICCVW), Oct. 2021.<\/em><\/li>\n<li>\n<div class=\"gs_gray\">CH Yeh, D Chiu, LW Kang, <strong>CC Hsu<\/strong>, C Lo, &#8221; Generative Adversarial Networks-based Face Hallucination with Identity-Preserving,&#8221; in Proc. of <em>IEEE International Conference on Consumer Electronics-Taiwan (ICCE-TW)<\/em>, 2021.<\/div>\n<\/li>\n<li><strong>C.C. Hsu, <\/strong>C, Lee, C. Lin, K.M. Hung, Y.L. Lin, X.Y. Wang, \u201cEfficient-ROD: Efficient Radar Object Detection based on Densely Connected Residual Network,\u201d in Proc. of <em>ACM International Conference on Multimedia Retrieval (ICMR)<\/em>, 21-24 Aug., 2021.<\/li>\n<li>Ignatov, C.-M. Chiang, H.-K. Kuo, A. Sycheva, and R. Timofte, &#8220;Learned smartphone isp on mobile npus with deep learning, mobile ai 2021 challenge: Report,&#8221; in <em>Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition<\/em>, 2021, pp. 2503-2514.<\/li>\n<li><strong>-C. Hsu<\/strong>, W.-H. Tseng, H.-T. Yang, C.-H. Lin, and C.-H. Kao, &#8220;Rethinking Relation between Model Stacking and Recurrent Neural Networks for Social Media Prediction,&#8221; in <em>Proceedings of the 28th ACM International Conference on Multimedia<\/em>, 2020, pp. 4585-4589.<\/li>\n<li><strong>-C. Hsu<\/strong>, W.-H. Tseng, and H.-T. Yang, &#8220;Learning to Predict Risky Driving Behaviors for Autonomous Driving,&#8221; in <em>2020 IEEE International Conference on Consumer Electronics-Taiwan (ICCE-Taiwan)<\/em>, 2020: IEEE, pp. 1-2.<\/li>\n<li>-W. Kang, <strong>C.-C. Hsu<\/strong>, I.-S. Wang, T.-L. Liu, S.-Y. Chen, and C.-Y. Chang, &#8220;Vehicle Trajectory Prediction based on Social Generative Adversarial Network for Self-Driving Car Applications,&#8221; in <em>2020 International Symposium on Computer, Consumer and Control (IS3C)<\/em>, 2020: IEEE, pp. 489-492.<\/li>\n<li>-X. Zhuang and <strong>C.-C. Hsu<\/strong>, &#8220;Detecting Generated Image Based on a Coupled Network with Two-Step Pairwise Learning,&#8221; in <em>2019 IEEE International Conference on Image Processing (ICIP)<\/em>, 2019: IEEE, pp. 3212-3216. (Best Student Papwe Award)<\/li>\n<li><strong>-C. Hsu<\/strong>, L.-W. Kang, C.-Y. Lee, J.-Y. Lee, Z.-X. Zhang, and S.-M. Wu, &#8220;Popularity prediction of social media based on multi-modal feature mining,&#8221; in <em>Proceedings of the 27th ACM International Conference on Multimedia<\/em>, 2019, pp. 2687-2691.<\/li>\n<li>Lugmayr<em> et al.<\/em>, &#8220;Aim 2019 challenge on real-world image super-resolution: Methods and results,&#8221; in <em>2019 IEEE\/CVF International Conference on Computer Vision Workshop (ICCVW)<\/em>, 2019: IEEE, pp. 3575-3583.<\/li>\n<li><strong>-C. Hsu<\/strong>, H.-T. Ma, and J.-Y. Lee, &#8220;SSSNet: Small-Scale-Aware Siamese Network for Gastric Cancer Detection,&#8221; in <em>2019 16th IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS)<\/em>, 2019: IEEE, pp. 1-5.<\/li>\n<li><strong>-C. Hsu<\/strong>, C.-H. Hung, C.-Y. Jian, and Y.-X. Zhuang, &#8220;Stronger Baseline for Vehicle Re-Identification in the Wild,&#8221; in <em>2019 IEEE Visual Communications and Image Processing (VCIP)<\/em>, 2019: IEEE, pp. 1-4.<\/li>\n<li><strong>-C. Hsu<\/strong> and C.-H. Lin, &#8220;Dual Reconstruction with Densely Connected Residual Network for Single Image Super-Resolution,&#8221; in <em>IEEE International Conference on Computer Vision Workshop (ICCVW)<\/em>, 2019.<\/li>\n<li>-T. Su, <strong>C.-C. Hsu<\/strong>, Z. Huang, C.-W. Lin, and G. Cheung, &#8220;Joint pairwise learning and image clustering based on a siamese cnn,&#8221; in <em>2018 25th IEEE International Conference on Image Processing (ICIP)<\/em>, 2018: IEEE, pp. 1992-1996.<\/li>\n<li><strong>-C. Hsu<\/strong><em> et al.<\/em>, &#8220;An iterative refinement approach for social media headline prediction,&#8221; in <em>Proceedings of the 26th ACM international conference on Multimedia<\/em>, 2018, pp. 2008-2012.<\/li>\n<li><strong>-C. Hsu<\/strong>, &#8220;Iteration-Free Fractal Mating Coding for Mutual Image Compression,&#8221; in <em>2018 International Symposium on Computer, Consumer and Control (IS3C)<\/em>, 2018: IEEE, pp. 396-399.<\/li>\n<li><strong>-C. Hsu<\/strong>, C.-Y. Lee, and Y.-X. Zhuang, &#8220;Learning to detect fake face images in the wild,&#8221; in <em>2018 International Symposium on Computer, Consumer and Control (IS3C)<\/em>, 2018: IEEE, pp. 388-391.<\/li>\n<li><strong>-C. Hsu<\/strong><em> et al.<\/em>, &#8220;Social media prediction based on residual learning and random forest,&#8221; in <em>Proceedings of the 25th ACM international conference on Multimedia<\/em>, 2017, pp. 1865-1870. (Oral &amp; Best Grand Challenge Paper Award)<\/li>\n<li><strong>-C. Hsu<\/strong> and C.-W. Lin, &#8220;Objective quality assessment for video retargeting based on spatio-temporal distortion analysis,&#8221; in <em>2017 IEEE Visual Communications and Image Processing (VCIP)<\/em>, 2017: IEEE, pp. 1-4.<\/li>\n<li><strong>-C. Hsu<\/strong> and C.-W. Lin, &#8220;Unsupervised convolutional neural networks for large-scale image clustering,&#8221; in <em>2017 IEEE International Conference on Image Processing (ICIP)<\/em>, 2017: IEEE, pp. 390-394.<\/li>\n<li>-T. Su, <strong>C.-C. Hsu<\/strong>, C.-W. Lin, and W. Lin, &#8220;Supervised-learning based face hallucination for enhancing face recognition,&#8221; in <em>2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)<\/em>, 2016: IEEE, pp. 1751-1755.<\/li>\n<li><strong>-C. Hsu<\/strong>, L.-W. Kang, and C.-W. Lin, &#8220;Video super-resolution via dynamic texture synthesis,&#8221; in <em>2014 IEEE 16th International Workshop on Multimedia Signal Processing (MMSP)<\/em>, 2014: IEEE, pp. 1-6.<\/li>\n<li>-W. Kang, B. Zhuang, <strong>C.-C. Hsu,<\/strong> C.-W. Lin, and C.-H. Yeh, &#8220;Self-learning-based low-quality single image super-resolution,&#8221; in <em>IEEE Workshop Multimedia Signal Processing\u00a0<\/em>(<em>MMSP<\/em>), Sardinia, Italy, Sept. 2013, 2013. (Top 10% Paper Award)<\/li>\n<li>-W. Kang, B.-C. Chuang, <strong>C.-C. Hsu<\/strong>, C.-W. Lin, and C.-H. Yeh, &#8220;Self-learning-based single image super-resolution of a highly compressed image,&#8221; in <em>2013 IEEE 15th International Workshop on Multimedia Signal Processing (MMSP)<\/em>, 2013: IEEE, pp. 224-229.<\/li>\n<li><strong>-C. Hsu<\/strong>, C.-W. Lin, Y. Fang, and W. Lin, &#8220;Objective quality assessment for image retargeting based on perceptual distortion and information loss,&#8221; in <em>2013 Visual Communications and Image Processing (VCIP)<\/em>, 2013: IEEE, pp. 1-6.<\/li>\n<li><strong>-C. Hsu<\/strong> and C.-W. Lin, &#8220;Image super-resolution via feature-based affine transform,&#8221; in <em>2011 IEEE 13th International Workshop on Multimedia Signal Processing<\/em>, 2011: IEEE, pp. 1-5.<\/li>\n<li>-Y. Lin,<strong> C.-C. Hsu<\/strong>, C.-W. Lin, and L.-W. Kang, &#8220;Fast deconvolution-based image super-resolution using gradient prior,&#8221; in <em>2011 Visual Communications and Image Processing (VCIP)<\/em>, 2011: IEEE, pp. 1-4.<\/li>\n<li><strong>-C. Hsu<\/strong>, C.-W. Lin, C.-T. Hsu, H.-Y. M. Liao, and J.-Y. Yu, &#8220;Face hallucination using Bayesian global estimation and local basis selection,&#8221; in <em>2010 IEEE International Workshop on Multimedia Signal Processing<\/em>, 2010: IEEE, pp. 449-453.<\/li>\n<li><strong>-C. Hsu,<\/strong> C.-W. Lin, C.-T. Hsu, and H.-Y. M. Liao, &#8220;Cooperative face hallucination using multiple references,&#8221; in <em>2009 IEEE International Conference on Multimedia and Expo<\/em>, 2009: IEEE, pp. 818-821.<\/li>\n<li><strong>-C. Hsu<\/strong> and H. T. Chang, &#8220;Accelerating vector quantization of images using modified run length coding for adaptive block representation and difference measurement,&#8221; in <em>2008 IEEE International Symposium on Circuits and Systems<\/em>, 2008: IEEE, pp. 3494-3497.<\/li>\n<li><strong>-C. Hsu<\/strong>, T.-Y. Hung, C.-W. Lin, and C.-T. Hsu, &#8220;Video forgery detection using correlation of noise residue,&#8221; in <em>2008 IEEE 10th workshop on multimedia signal processing<\/em>, 2008: IEEE, pp. 170-174.<\/li>\n<li><strong>-C. Hsu<\/strong>, H. T. Chang, and T.-C. Chang, &#8220;An improved face detection method in low-resolution video,&#8221; in <em>Third International Conference on Intelligent Information Hiding and Multimedia Signal Processing (IIH-MSP 2007)<\/em>, 2007, vol. 2: IEEE, pp. 419-422.<\/li>\n<li><strong>-C. Hsu<\/strong>, H. T. Chang, and T.-c. Chang, &#8220;Efficient moving object extraction in compressed low-bit-rate video,&#8221; in <em>2006 International Conference on Intelligent Information Hiding and Multimedia<\/em>, 2006: IEEE, pp. 411-414.<\/li>\n<\/ul>\n<p><strong><u>Patents<\/u><\/strong><\/p>\n<ul>\n<li><strong> Hsu\u00a0<\/strong>and T.C. Lee, \u201cSystem and method for diagnosing gastrointestinal neoplasm,\u201d US Patent, US11011275B2, 5\/18\/2021.<\/li>\n<li>\u7ae5\u66c9\u5112, \u8a31\u5fd7\u4ef2, \u5f35\u6587\u8aa0, \u201c\u5f71\u50cf\u8fa8\u8b58\u65b9\u6cd5\u201d, Taiwan Patent, #I689872, 4\/1 \/2020.<\/li>\n<li><strong>C. Hsu<\/strong> and C.W. Lin, \u201cMethod and system for example-based face hallucination,\u201d USA patent # 8,488,913, 2013.<\/li>\n<li><strong>C. Hsu<\/strong> and H.S. Chang, \u201c\u5f71\u50cf\u8fa8\u8b58\u7cfb\u7d71\u53ca\u5176\u64cd\u4f5c\u65b9\u6cd5,\u201d Taiwan Patent #201329874, 2013.<\/li>\n<li><strong>C. Hsu<\/strong>, and C.W. Lin, &#8220;Super-resolution method and system for human face based on sample,&#8221; China patent #CN102298775 B, 2013.<\/li>\n<li>\u5f35\u5ef7\u653f, \u5f35\u8ed2\u5ead, \u8207<strong>\u8a31\u5fd7\u4ef2<\/strong>, &#8220;The application of parallel-connected distributed encryption system in internet,&#8221; Taiwan Patent #094122766, 2005.<\/li>\n<li><strong>\u8a31\u5fd7\u4ef2<\/strong>, \u738b\u711c\u6f54, \u8207\u5f35\u5ef7\u653f, &#8220;\u61c9\u7528\u65bc\u7db2\u969b\u7db2\u8def\u4e0a\u4e4b\u5206\u6563\u5f0f\u52a0\u5bc6\u65b9\u6cd5,&#8221; Taiwan Patent #093135605, 2004.<\/li>\n<\/ul>\n","protected":false},"excerpt":{"rendered":"<p>Journal Papers G.L. Chen and C.C. Hsu*, &#8220;Jointly  [&hellip;]<\/p>\n","protected":false},"author":2,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[1],"tags":[],"class_list":["post-514","post","type-post","status-publish","format-standard","hentry","category-uncategorized"],"_links":{"self":[{"href":"https:\/\/cchsu.info\/wordpress\/wp-json\/wp\/v2\/posts\/514","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/cchsu.info\/wordpress\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/cchsu.info\/wordpress\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/cchsu.info\/wordpress\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/cchsu.info\/wordpress\/wp-json\/wp\/v2\/comments?post=514"}],"version-history":[{"count":21,"href":"https:\/\/cchsu.info\/wordpress\/wp-json\/wp\/v2\/posts\/514\/revisions"}],"predecessor-version":[{"id":1112,"href":"https:\/\/cchsu.info\/wordpress\/wp-json\/wp\/v2\/posts\/514\/revisions\/1112"}],"wp:attachment":[{"href":"https:\/\/cchsu.info\/wordpress\/wp-json\/wp\/v2\/media?parent=514"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/cchsu.info\/wordpress\/wp-json\/wp\/v2\/categories?post=514"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/cchsu.info\/wordpress\/wp-json\/wp\/v2\/tags?post=514"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}