洪 昌鈺

研究成果

每年研究成果 1993 2009 2010 2011 2025

• 36 Article
• 19 Conference contribution
• 1 Comment/debate
• 1 Conference article
• 1 更多
  • 1 Review article

每年研究成果

每年研究成果

搜尋結果

• 2025

  Enhancing prediction of magnetic properties in additive manufacturing products through a 3D convolutional vision transformer model

  Chang, L. K., Chen, P. C., Tsai, M. C., Lee, R. M., Huang, J. C., Chang, T. W. & Horng, M. H., 2025 4月, 於: International Journal of Advanced Manufacturing Technology. 137, 9, p. 4503-4519 17 p.

  研究成果: Article › 同行評審
• 2024

  Machine learning applied to property prediction of metal additive manufacturing products with textural features extraction

  Chang, L. K., Chen, R. S., Tsai, M. C., Lee, R. M., Lin, C. C., Huang, J. C., Chang, T. W. & Horng, M. H., 2024 5月, 於: International Journal of Advanced Manufacturing Technology. 132, 1-2, p. 83-98 16 p.

  研究成果: Article › 同行評審

  • 3D printers 100%
  • Feature extraction 78%
  • Machine learning 74%
  • Metals 64%
  • Support vector regression 59%
  5 引文 斯高帕斯（Scopus）

• The Detection and Classification of Scaphoid Fractures in Radiograph by Using a Convolutional Neural Network

  Yang, T. H., Sun, Y. N., Li, R. S. & Horng, M. H., 2024 11月, 於: Diagnostics. 14, 21, 2425.

  研究成果: Article › 同行評審

  開啟存取
• 2022

  Deep Learning Applied to Defect Detection in Powder Spreading Process of Magnetic Material Additive Manufacturing

  Chen, H. Y., Lin, C. C., Horng, M. H., Chang, L. K., Hsu, J. H., Chang, T. W., Hung, J. C., Lee, R. M. & Tsai, M. C., 2022 8月, 於: Materials. 15, 16, 5662.

  研究成果: Article › 同行評審

  開啟存取

  • Magnetic materials 100%
  • Magnetic Material 96%
  • learning 86%
  • Spreading 84%
  • magnetic materials 82%
  19 引文 斯高帕斯（Scopus）

• Scaphoid Fracture Detection by Using Convolutional Neural Network

  Yang, T. H., Horng, M. H., Li, R. S. & Sun, Y. N., 2022 4月, 於: Diagnostics. 12, 4, 895.

  研究成果: Article › 同行評審

  開啟存取

  • Scaphoid Bone 100%
  • X-Rays 93%
  • Area Under Curve 73%
  • X-Ray 72%
  • Sensitivity and Specificity 67%
  20 引文 斯高帕斯（Scopus）

• Validation of a Deep Learning-based Automatic Detection Algorithm for Measurement of Endotracheal Tube-to-Carina Distance on Chest Radiographs

  Huang, M., Chen, C. Y., Horng, M. H., Li, C. I., Hsu, I. L., Su, C. M., Sun, Y. N. & Lai, C. H., 2022 12月 1, 於: Anesthesiology. 137, 6, p. 704-715 12 p.

  研究成果: Article › 同行評審

  • Deep Learning 100%
  • Thorax 50%
  • Critical Care 21%
  • Intensive Care Units 6%
  4 引文 斯高帕斯（Scopus）
• 2021

  A Fully-Automatic Segmentation of the Carpal Tunnel from Magnetic Resonance Images Based on the Convolutional Neural Network-Based Approach

  Yang, T. H., Yang, C. W., Sun, Y. N. & Horng, M. H., 2021 10月, 於: Journal of Medical and Biological Engineering. 41, 5, p. 610-625 16 p.

  研究成果: Article › 同行評審

  開啟存取

  • Magnetic resonance 100%
  • Convolutional neural networks 87%
  • Tunnels 80%
  • Tendons 62%
  • Convolution 13%
  4 引文 斯高帕斯（Scopus）

• The steelmaking process parameter optimization with a surrogate model based on convolutional neural networks and the firefly algorithm

  Liu, Y. C., Horng, M. H., Yang, Y. Y., Hsu, J. H., Chen, Y. T., Hung, Y. C., Sun, Y. N. & Tsai, Y. H., 2021 6月 1, 於: Applied Sciences (Switzerland). 11, 11, 4857.

  研究成果: Article › 同行評審

  開啟存取

  • fireflies 100%
  • Steelmaking 73%
  • Convolutional neural networks 55%
  • Multilayer 53%
  • optimization 39%
  3 引文 斯高帕斯（Scopus）
• 2020

  DeepNerve: A New Convolutional Neural Network for the Localization and Segmentation of the Median Nerve in Ultrasound Image Sequences

  Horng, M. H., Yang, C. W., Sun, Y. N. & Yang, T. H., 2020 9月, 於: Ultrasound in Medicine and Biology. 46, 9, p. 2439-2452 14 p.

  研究成果: Article › 同行評審

  開啟存取

  • Median Nerve 100%
  • nerves 98%
  • tunnels 40%
  • physical work 23%
  • image analysis 15%
  40 引文 斯高帕斯（Scopus）

• Segmentation of finger tendon and synovial sheath in ultrasound image using deep convolutional neural network

  Kuok, C. P., Yang, T. H., Tsai, B. S., Jou, I. M., Horng, M. H., Su, F. C. & Sun, Y. N., 2020 4月 22, 於: Biomedical engineering online. 19, 1, 24.

  研究成果: Article › 同行評審

  開啟存取

  • Tendons 100%
  • Deep neural networks 84%
  • Fingers 80%
  • Convolutional neural networks 79%
  • Ultrasonics 74%
  16 引文 斯高帕斯（Scopus）
• 2019

  An effective and accurate identification system of Mycobacterium tuberculosis using convolution neural networks

  Kuok, C. P., Horng, M. H., Liao, Y. M., Chow, N. H. & Sun, Y. N., 2019 6月, 於: Microscopy Research and Technique. 82, 6, p. 709-719 11 p.

  研究成果: Article › 同行評審

  • tuberculosis 100%
  • system identification 82%
  • convolution integrals 62%
  • Convolution 59%
  • Mycobacterium tuberculosis 58%
  34 引文 斯高帕斯（Scopus）

• Cobb angle measurement of spine from x-ray images using convolutional neural network

  Horng, M. H., Kuok, C. P., Fu, M. J., Lin, C. J. & Sun, Y. N., 2019, 於: Computational and Mathematical Methods in Medicine. 2019, 6357171.

  研究成果: Article › 同行評審

  開啟存取

  • Spine 100%
  • Angle measurement 93%
  • Neural Networks 72%
  • Convolutional neural networks 70%
  • X rays 69%
  223 引文 斯高帕斯（Scopus）
• 2015

  Motion estimation using the firefly algorithm in ultrasonic image sequence of soft tissue

  Chao, C. F., Horng, M. H. & Chen, Y. C., 2015, 於: Computational and Mathematical Methods in Medicine. 2015, 343217.

  研究成果: Article › 同行評審

  開啟存取

  • Fireflies 100%
  • Motion Estimation 96%
  • Soft Tissue 90%
  • Image Sequence 89%
  • Motion Vector 75%
  6 引文 斯高帕斯（Scopus）

• The construction of support vector machine classifier using the firefly algorithm

  Chao, C. F. & Horng, M. H., 2015 2月 23, 於: Computational Intelligence and Neuroscience. 2015, 212719.

  研究成果: Article › 同行評審

  開啟存取

  • Fireflies 100%
  • Support Vector Machine 71%
  • Classifier 65%
  • Support vector machines 47%
  • Classifiers 41%
  61 引文 斯高帕斯（Scopus）
• 2013

  Multilevel image threshold selection based on the shuffled frog-leaping algorithm

  Horng, M. H., 2013, 於: Journal of Chemical and Pharmaceutical Research. 5, 9, p. 599-605 7 p.

  研究成果: Article › 同行評審

  • Anura 100%
  • Entropy 76%
  • Pattern Recognition 18%
  • Learning 6%
  • Technology 6%
  9 引文 斯高帕斯（Scopus）

• The glowworm swarm optimization for training the radial basis function network in ultrasonic supraspinatus image classification

  Horng, M. H., 2013 9月, 於: Advanced Science Letters. 19, 9, p. 2724-2727 4 p.

  研究成果: Article › 同行評審

  • Image Classification 100%
  • Radial Basis Function Network 97%
  • Swarm 87%
  • Radial basis function networks 73%
  • Rotator Cuff 70%
  5 引文 斯高帕斯（Scopus）
• 2012

  Firefly algorithm for training the radial basis function network for data classifications

  Horng, M. H., Lee, M. C. & Liou, R. J., 2012 5月, 於: Advanced Science Letters. 11, 1, p. 755-758 4 p.

  研究成果: Article › 同行評審

  • Fireflies 100%
  • Radial Basis Function Network 92%
  • Data Classification 87%
  • Radial basis function networks 69%
  • Gradient Descent 20%
  3 引文 斯高帕斯（Scopus）

• Multilevel minimum cross entropy threshold selection with shuffled frog-leaping algorithm

  Horng, M. H., 2012 6月, 於: Advances in Information Sciences and Service Sciences. 4, 11, p. 168-176 9 p.

  研究成果: Article › 同行評審

  • Cross-entropy 100%
  • Entropy 58%
  • Optimization 24%
  • Exhaustive Search 16%
  • Particle swarm optimization (PSO) 9%
  2 引文 斯高帕斯（Scopus）

• Vector quantization using the firefly algorithm for image compression

  Horng, M. H., 2012 1月, 於: Expert Systems With Applications. 39, 1, p. 1078-1091 14 p.

  研究成果: Article › 同行評審

  • Vector quantization 100%
  • Image compression 90%
  • Particle swarm optimization (PSO) 47%
  236 引文 斯高帕斯（Scopus）
• 2011

  Image vector quantization algorithm via honey bee mating optimization

  Horng, M. H. & Jiang, T. W., 2011 3月, 於: Expert Systems With Applications. 38, 3, p. 1382-1392 11 p.

  研究成果: Article › 同行評審

  • Vector quantization 100%
  • Particle swarm optimization (PSO) 74%
  • Image compression 18%
  44 引文 斯高帕斯（Scopus）

• Multilevel image thresholding selection based on the firefly algorithm

  Horng, M. H. & Jiang, T. W., 2011 2月, 於: ICIC Express Letters. 5, 2, p. 557-562 6 p.

  研究成果: Article › 同行評審

  • Particle swarm optimization (PSO) 100%
  • Entropy 75%
  • Pattern recognition 26%
  • Image processing 23%
  3 引文 斯高帕斯（Scopus）

• Multilevel minimum cross entropy threshold selection based on the firefly algorithm

  Horng, M. H. & Liou, R. J., 2011 11月, 於: Expert Systems With Applications. 38, 12, p. 14805-14811 7 p.

  研究成果: Article › 同行評審

  • Entropy 100%
  • Particle swarm optimization (PSO) 49%
  • Image segmentation 14%
  • Communication 7%
  190 引文 斯高帕斯（Scopus）

• Multilevel thresholding selection based on the artificial bee colony algorithm for image segmentation

  Horng, M. H., 2011 10月, 於: Expert Systems With Applications. 38, 11, p. 13785-13791 7 p.

  研究成果: Article › 同行評審

  • Image segmentation 100%
  • Entropy 88%
  • Particle swarm optimization (PSO) 29%
  • Pattern recognition 15%
  • Image processing 13%
  264 引文 斯高帕斯（Scopus）

• Vector quantization based on the artificial bee colony algorithm

  Horng, M. H. & Jiang, T. W., 2011 8月, 於: ICIC Express Letters. 5, 8 B, p. 2881-2887 7 p.

  研究成果: Article › 同行評審

  • Vector quantization 100%
  • Image compression 18%
• 2010

  A multilevel image thresholding using the honey bee mating optimization

  Horng, M. H., 2010 1月 1, 於: Applied Mathematics and Computation. 215, 9, p. 3302-3310 9 p.

  研究成果: Article › 同行評審

  • Entropy 69%
  • Maximum Entropy 66%
  • Optimization 62%
  • Particle swarm optimization (PSO) 19%
  • Particle Swarm Optimization Algorithm 13%
  109 引文 斯高帕斯（Scopus）

• Multilevel minimum cross entropy threshold selection based on the honey bee mating optimization

  Horng, M. H., 2010 6月, 於: Expert Systems With Applications. 37, 6, p. 4580-4592 13 p.

  研究成果: Article › 同行評審

  開啟存取

  • Entropy 100%
  • Particle swarm optimization (PSO) 33%
  • Pattern recognition 17%
  • Image processing 15%
  95 引文 斯高帕斯（Scopus）

• Parametric active contour model by using the honey bee mating optimization

  Horng, M. H., Liou, R. J. & Wu, J., 2010, 於: Expert Systems With Applications. 37, 10, p. 7015-7025 11 p.

  研究成果: Article › 同行評審

  • Beer 100%
  • Chromosomes 84%
  • Genes 70%
  16 引文 斯高帕斯（Scopus）

• Performance evaluation of multiple classification of the ultrasonic supraspinatus images by using ML, RBFNN and SVM classifiers

  Horng, M. H., 2010 6月, 於: Expert Systems With Applications. 37, 6, p. 4146-4155 10 p.

  研究成果: Article › 同行評審

  • Ultrasonics 100%
  • Classifiers 82%
  • Neural networks 47%
  • Maximum likelihood 36%
  • Support vector machines 31%
  27 引文 斯高帕斯（Scopus）
• 2009

  Multi-class classification of ultrasonic supraspinatus images based on radial basis function neural network

  Horng, M. H. & Chen, S. M., 2009, 於: Journal of Medical and Biological Engineering. 29, 5, p. 242-250 9 p.

  研究成果: Article › 同行評審

  • Ultrasonics 100%
  • Textures 93%
  • Neural networks 71%
  • Tendons 66%
  • Fractal dimension 35%
  12 引文 斯高帕斯（Scopus）

• Multi-class support vector machine for classification of the ultrasonic images of supraspinatus

  Horng, M. H., 2009 5月, 於: Expert Systems With Applications. 36, 4, p. 8124-8133 10 p.

  研究成果: Article › 同行評審

  • Ultrasonics 100%
  • Support vector machines 94%
  • Textures 75%
  • Tendons 53%
  • Classifiers 33%
  47 引文 斯高帕斯（Scopus）
• 2007

  An ultrasonic image evaluation system for assessing the severity of chronic liver disease

  Horng, M. H., 2007 10月, 於: Computerized Medical Imaging and Graphics. 31, 7, p. 485-491 7 p.

  研究成果: Article › 同行評審

  • Liver 100%
  • Ultrasonics 85%
  • Liver Diseases 70%
  • Chronic Disease 61%
  • Radial basis function networks 24%
  21 引文 斯高帕斯（Scopus）
• 2003

  Texture feature coding method for texture classification

  Horng, M. H., 2003 1月, 於: Optical Engineering. 42, 1, p. 228-238 11 p.

  研究成果: Article › 同行評審

  • coding 100%
  • textures 89%
  • Textures 86%
  • pixels 14%
  • Pixels 13%
  56 引文 斯高帕斯（Scopus）
• 2002

  Texture feature coding method for classification of liver sonography

  Horng, M. H., Sun, Y. N. & Lin, X. Z., 2002 1月 2, 於: Computerized Medical Imaging and Graphics. 26, 1, p. 33-42 10 p.

  研究成果: Article › 同行評審

  • Ultrasonography 100%
  • Liver 80%
  • Textures 53%
  • Ultrasonics 19%
  • Maximum likelihood 14%
  84 引文 斯高帕斯（Scopus）
• 1998

  Computer morphometry for quantitative measurement of liver fibrosis: Comparison with Knodell's score, colorimetry and conventional description reports

  Lin, X. Z., Horng, M. H., Sun, Y. N., Shiesh, S. C., Chow, N. H. & Guo, X. Z., 1998, 於: Journal of Gastroenterology and Hepatology (Australia). 13, 1, p. 75-80 6 p.

  研究成果: Article › 同行評審

  • Colorimetry 100%
  • Nonparametric Statistics 27%
  • trichrome stain 21%
  • Microcomputers 16%
  • Alcoholics 15%
  41 引文 斯高帕斯（Scopus）
• 1997

  Assessing liver tissue fibrosis with an automatic computer morphometry system

  Sun, Y. N. & Horng, M. H., 1997 5月, 於: IEEE Engineering in Medicine and Biology Magazine. 16, 3, p. 66-73 8 p.

  研究成果: Article › 同行評審

  • Liver 100%
  • Computer systems 73%
  • Tissue 70%
  • Image acquisition 31%
  • Microscopes 26%
  14 引文 斯高帕斯（Scopus）
• 1995

  New method for texture classification based on local surface structure and its application to ultrasonic liver images

  Horng, M. H., Sun, Y. N., Lin, X. Z. & Wang, J. Y., 1995, 於: Biomedical Engineering - Applications, Basis and Communications. 7, 5, p. 491-498 8 p.

  研究成果: Article › 同行評審

  • Surface structure 100%
  • Liver 99%
  • Ultrasonics 85%
  • Crystalline Texture 80%
  • Surface Structure 80%