Jung-Hua Wang, Ph. D.

Title:

Director, Artificial Intelligence Research Center (AIRC), National Taiwan Ocean University (2020~present).

Professor, Department of Electrical Engineering, National Taiwan Ocean University (1999~present)

Education:

Ph.D., Department of Electrical Engineering, Texas Tech University, USA

M.S.E.E., Department of Electrical Engineering, Texas Tech University, USA.

B.S.E.E., Department of Electrical Engineering, National Cheng Kung University, Taiwan.

Jung-Hua Wang was born in Keelung City, Taiwan, in 1959. He received B.S. degree in electrical engineering from National Chen Kung University (NCKU), Taiwan, in 1983, and M.S. and Ph.D. degrees in electrical engineering from Texas Tech University, USA. After graduation from NCKU, he joined Texas Instrument as a Process Engineer. Before going to the U.S. for academic degrees, he worked as a Test Engineer with the National Chung-Shan Institute of Science and Technology (CSIST) for two years. After receiving the Ph.D. degree, he went back to Taiwan and joined ITRI (Industrial Technology Research Institute), one of the foremost consortia in the world for applied R&D, there his major job function is developing novel neural network paradigms for industrial applications. Since 1991, he has been serving as a faculty member of the Department of Electrical Engineering, National Taiwan Ocean University (NTOU). From 2019 to 2021, he served as the Chairman of the Department of Electrical Engineering, NTOU. He currently serves as the Director of AI Research Center, NTOU. In 2018, he visited the IBM Watson Center in New York and went on to SIO/UCSD for initiating an international collaboration project between NTOU and SIO. His research interests include: Image Processing, Artificial Intelligence, and Computer Vision. He is academically active and works closely with researchers and experts of aquaculture and genetic breeding. In particular. As the director of AIRC, he has successfully organized research teams targeting on applying AI techniques to underwater fish behavior analysis, marine environment ecology monitoring, human infertility, and so on. He is inventors or co-inventors of 15 patents and has presented and published over 121 technical articles in international journals and international conferences.

Publication

Books 

¡P Alasdair McAndrew, Jung-Hua Wang and Chun-Shun Tseng, Introduction to DigitalImage Processing with MATLAB, THOMSON, 2010.

 Referred Papers

1. C. C. Chang, J. H. Wang, et al., ¡§ Applying Artificial Intelligence (AI) Techniques to Implement a Practical Smart Cage Aquaculture Management System,¡¨ Journal of Medical and Biological Engineering, p.p. 1-7, 2021.(SCIE, IF:1.553 5-year, IF:1.733).

2. L. Chang, Y. T. Chen, J. H. Wang, Y. L. Chang, ¡§ Rice-Field Mapping with Sentinel-1A SAR Time-Series Data,¡¨ Remote sensing, vol. 13, no. 1, 021. (SCI,IF:4.509, 5-year, IF:5.00).

3. J. H. Wang, S. K. Lee, Y. C. Lai, C. C. Lin, T. Y. Wang, Y. R. Lin, T. H. Hsu, C. W. Huang, and C. P. Chiang, ¡§ Anomalous Behaviors Detection for Underwater Fish Using AI Techniques,¡¨ IEEE Access, 2020. (SCI, IF:3.745 5-year, IF:4.076)

4. R. J. Huang, J. H. Wang, C. S. Tseng, Z. W. Tu, and K. C. Chiang, ¡§ Bayesian edge detector using deformable directivity-aware sampling window,¡¨ Entropy 2020, ol. 22, no. 10, 2020. (SCI, IF:2.494, 5-year, IF:2.53).

5. R. J. Huang, C. Y. Tsao, Y. P. Kuo, Y. C. Lai, C. C. Liu, Z. W. Tu, J. H. Wang, and C. C. Chang, ¡§ Fast Visual Tracking based on Convolutional Networks,¡¨ Sensors 2018, Vol. 18, no. 2, 2405, 2018. Financially supported by MOST 107-2634-F-019-001.(SCIE, IF:3.275, 5-year, IF:3.427).

6. R. J. Huang, J. H. Wang, and C. S. Tseng, ¡§ Bayesian Approach to Perceptual Edge Preservation in Computer Vision,¡¨ Computer Science and Information Technology, vol. 5, no. 3, pp. 113-119, 2017. Financially supported by MOST 105-2221-E-019-068.

7. C. S. Tseng, and J. H. Wang, ¡§ Perceptual edge detection via entropy-driven gradient evaluation,¡¨ IET Computer Vision, vol. 6, no. 2, pp. 163-171, 2016 (SCI, IF:1.516, 5-year, IF:1.524).

8. C. S. Tseng, J. H. Wang, and R. J. Huang, ¡§ Maximum-Likelihood Directivity for Depicting Perceptual Contours,¡¨ Journal of Marine Science and Technology, vol. 24, no.2, pp. 152-162, 2016(SCI, IF:1.446, 5-year, IF:1.84), Financially supported by NSC 101-2221-E-019-068.

9. J. D. Zhu, C. F. Lin, S. H. Chang, J. H. Wang, T. I. Peng, Y. Y. Chien, ¡§ Analysis of spike waves in epilepsy using Hilbert-Huang transform,¡¨ Journal of medical systems, 39(1), 1-13, 2015. (SCI, IF:3.058, 5-year, IF:3.072)

10. ¤ýºaµØ¡B²ø©ú©_¡B¾G¶®ªå¡A ¡§¶}©Ý¦Û°Ê¤Æ¨t²Îªºµø¬É¢w¾÷¾¹µøı¡¨¡A¹q¤l¤ë¥Z¡Avol.151¡App. 189-205, 2008¡C

11. J. H. Wang, C. S. Tseng, S. Y. Shen, and Y.Y. Jheng, ¡§Self-organizing Fusion Neural Networks,¡¨ Journal of Advanced Computational Intelligence and Intelligent Informatics, vol.11, no.6, pp. 610-619, 2007.

12. J. H. Wang, F. C. Chang, and F. W. Su ,¡§Image Segmentation via Self-organizing Fusion,¡¨ IEE Proc.-Vision, Image and Signal Processing, vol.153, Issue 5 , pp. 657-665 Oct. 2006. (SCI, IF:0.461).

13. ±i©¾¸Û¡BªLÂí¬w¡B¤ýºaµØ¡B¾G¼}¼w, ¡§»·ºÝ¾Þ±±¤ô¤U¾÷±ñÁu¨t²ÎÀ³¥Î©ó¤ô¤U¬I¤u§@·~¤§§Þ³N¬ãµo¡¨¡A¤uµ{¬ì§Þ³q°T¡A vol.75¡App.114-120¡C

14. J. H. Wang, J. D. Rau, and W. J. Liu, ¡§Two-stage clustering via neural networks,¡¨ IEEE Trans. on Neural Networks, vol. 14, no. 3, pp. 606-615, May 2003. (SCI, IF:2.952, 5-year, IF:3.37)

15. J. H. Wang, H. Huang, and J. L. Chen, ¡§PCT¢wA technique to probe cluster terrain,¡¨ Pattern Recognition Letters, vol. 23, no. 10, pp. 1153-1168, Aug. 2002. (SCI, IF:3.255, 5-year, IF:3.077)

16. J. H. Wang, W. J. Liu, and L. D. Lin, ¡§Histogram-based fuzzy filter for image restoration,¡¨ IEEE Trans. on Systems, Man, and Cybernetics, Part B: Cybernetics, vol. 32, no. 2, pp. 230-238, Apr. 2002. (SCI, IF:6.22, 5-year, IF:6.18)

17. J. H. Wang and M. C. Tsai, and W. S. Su, ¡§Learning temporal sequences using dual-weight neurons,¡¨ Journal of Chinese Institute of Engineers, vol. 24, no. 3, pp. 329-344, Mar. 2001. (SCI, IF:0.667, 5-year, IF:0.64)

18. J. H. Wang, and J. D. Rau, ¡§VQ-Agglomeration¢wA novel approach to clustering,¡¨ IEE Proc.-Vision, Image and Signal Processing, vol. 148, no. 1, pp. 36-44, Feb. 2001. (SCI, IF:0.461)

19. ±i©¾¸Û¡B¾G¼}¼w¡B¤ýºaµØ¡BªLÂí¬w¡B´¿¥@©M, ¡§´¼¼z«¬¤ô¤U¾÷±ñÁu¨t²Î§Þ³N¬ã²ß»P¹ê§@¡¨¡A¤uµ{¬ì§Þ³q°T¡Avol. 56, pp. 45-50, 2001¡C

20. J. H. Wang, Y. W. Yu, and J. H. Tsai, ¡§On the internal representations of product unit,¡¨ Neural Processing Letters, vol.12, no. 3, pp. 247-252, Dec. 2000. (SCI, IF:2.891, 5-year, IF:2.711)

21. J. H. Wang, C. Y. Peng, and J. D. Rau, ¡§Harmonic neural networks for on-line learning vector quantisation,¡¨ IEE Proc.-Vision, Image and Signal Processing, vol. 147, no. 5, pp. 485-492, Oct. 2000. (SCI, IF:0.461)

22. J. H. Wang, J. D. Rau, and C. Y. Peng, ¡§Toward optimizing a self-creating neural network,¡¨ IEEE Trans. on Systems, Man, and Cybernetics, Part B: Cybernetics, vol. 30, no. 4, pp. 586-593, Aug. 2000. (SCI, IF:6.22, 5-year, IF:6.184)

23. C. C. Chang, J. H. Wang, M. D. Jeng, C. C. Lin, and K. H. Chen, ¡§The fabrication and characterization of PZT thin film Acoustic Devices for application in underwater robotic systems,¡¨ Proceedings of the National Science Council. Part A, vol. 24, no. 4, pp. 287-292, July 2000. (EI)

24. J. H. Wang, and C. Y. Peng, ¡§A novel self-creating neural network for learning vector quantization,¡¨ Neural Processing Letters, vol. 11, no. 2, pp. 139-151, Apr. 2000. (SCI, IF:2.891, 5-year, IF:2.711)

25. J. H. Wang, and W. D. Sun, ¡§On the characteristics of growing cell structures (GCS) neural network,¡¨ Neural Processing Letters, vol. 10, no. 2, pp. 139-149, Oct. 1999. (SCI, IF:2.891, 5-year, IF:2.711)

26. J. H. Wang, R. F. Hsieh, and H. C. Chiu, ¡§A progressive constraint search approach for disparity matching in stereo vision,¡¨ Proceedings of the National Science Council. Part A, vol. 23, no. 6, pp. 789-798, June 1999. (EI)

27. J. H. Wang, and C. P. Hsiao, ¡§On disparity matching in stereo vision via a neural network framework,¡¨ Proceedings of the National Science Council. Part A, vol. 23, no. 5, pp. 665-678, Mar. 1999. (EI)

28. J. H. Wang, and H. C. Chiu, ¡§HAF: An adaptive fuzzy filter for restoring highly corrupted images by histogram estimation,¡¨ Proceedings of the National Science Council. Part A, vol. 23, no. 5, pp. 630-643, Mar. 1999. (EI)

29. J. H. Wang, and C. Y. Peng, ¡§Competitive neural network scheme for learning vector quantization,¡¨ IEE Electronics Letters, vol. 35, no. 9, pp. 725-726, Apr. 1999. (SCI, IF:1.316, 5-year, IF:1.279)

30. J. H. Wang, and W. D. Sun, ¡§Online learning vector quantization: a harmonic competition approach based on conservation network,¡¨ IEEE Trans. on Systems, Man, and Cybernetics. Part B, vol. 29, no. 5, pp. 642-653, Oct. 1999.(SCI, IF:6.22, 5-year, IF:6.184)

31. J. H. Wang, ¡§Prescanned minmax center-weighted filters for image restoration,¡¨ IEE Proceedings-Vision, Image and Signal Processing, vol. 146, no. 2, pp. 101-107, Apr. 1999. (SCI, IF:0.461)(Àò89¦~«×°ê¬ì·|¥Òµ¥¼úÀy)

32. J. H. Wang, and W. D. Sun, ¡§Improved representation-burden conservation network for learning nonstationary VQ,¡¨ Neural Processing Letters, vol. 8, no. 1, pp. 41-53, Aug. 1998. (SCI, IF:2.891, 5-year, IF:2.711)

33. J. H. Wang, ¡§Principal interconnections in higher order Hebbian-type associative memories,¡¨ IEEE Trans. on Knowledge and Data Engineering, vol. 10, no. 2, pp. 342-344, Mar./Apr. 1998. (SCI, IF:4.935, 5-year, IF:5.201)(Àò88¦~«×°ê¬ì·|¥Òµ¥¼úÀy)

34. J. H. Wang, and L. D. Lin, ¡§Improved median filter using minmax algorithm for image processing,¡¨ IEE Electronic Letter, vol. 33, no. 16, pp. 1362-1363, July 1997. (SCI, IF:1.316, 5-year, IF:1.279)

35. J. H. Wang, L. D. Lin, and M. D. Yu, ¡§Histogram-based adaptive neuro-fuzzy filter for image restoration,¡¨ Proceedings of the National Science Council. Part A, vol. 21, no. 6, pp. 556-572, 1997. (EI)

36. J. H. Wang, and C. P. Hsiao, ¡§Representation-burden conservation network applied to learning VQ,¡¨ Neural Processing Letters, vol. 5, no. 3, pp. 209-217, 1997. (SCI, IF:2.891, 5-year, IF:2.711)

37. J. H. Wang, ¡§On the characteristics of the quadratic order associative memory that uses synchronous update and direct convergence,¡¨ International Journal of Neural Systems, vol. 7, no. 1, pp. 69-81, Mar. 1996. (SCI, IF: 5.604, 5-year, IF:4.834) (Àò86¦~«×°ê¬ì·|¥Òµ¥¼úÀy)

38. M. D. Jeng, and J. H. Wang, ¡§Live reversible and bounded petri nets for modeling automated manufacturing systems,¡¨ Advances in manufacturing systems: design, modeling and analysis, Edited by R. S. Sodhi, M Zhou and S. Das, Elsevier, New York, USA, vol. 22, pp. 63-68, 1994.

39. J. H. Wang, T. L. Jong, T. F. Krile, and J. F. Walkup, ¡§On the characteristics of the auto-associative memory with nonzero-diagonal terms in the memory matrix,¡¨ Neural Computation, vol. 3, no. 3, pp. 428-439, 1991. (SCI, IF:2.505, 5-year, IF:2.284)(Àò83¦~«×°ê¬ì·|¥Òµ¥¼ú§U)

40. J. H. Wang, T. F. Krile, and J. F. Walkup, ¡§Determination of hopfield associative memory characteristics using a single parameter,¡¨ Neural Networks, vol. 3, no. 3, pp. 319-331, 1990. (SCI, IF:5.535, 5-year, IF:7.309)(Àò82¦~«×°ê¬ì·|¥Òµ¥¼ú§U)

Conference Papers

1. Lena Chang, Yi-Ting Chen, Ming-Hung Hung, Jung-Hua Wang, Yang-Lang Chang, ¡§YOLOV3 BASED SHIP DETECTION IN VISIBLE AND INFRARED IMAGES,¡¨in Proc. of IEEE International Geoscience and Remote Sensing Symposium IGARSS2021, July 11 ¡V 16, Brussels, Belgium, 2021.

2. S. K. Lee, Y. C. Lai, J. H. Wang, T. H. Hsu, C. W. Huang, and C. P. Chiang, ¡§Fish Abnormal Behavior Detection Based on Object Detection, Tracking and DTW,¡¨IEEE Intl. Comp. Symposium (ICS), Tainan, Taiwan, 2020.

3. T. D. Wum, Y. Yen, J. H. Wang; R. J. Huang, H. W. Lee, and H. F. Wang, ¡§Automatic Target Recognition in SAR Images Based on a Combination of CNN and SVM,¡¨2020 International Workshop on Electromagnetics: Applications and Student Innovation Competition (iWEM), pp. 1-2, Makung, Taiwan, 2020.

4. R. J. Huang, Y. C. Lai, C. Y. Tsao, Y. P. Kuo, J. H. Wang, and C. C. Chang, ¡§Applying convolutional networks to underwater tracking without training,¡¨2018 IEEE International Conference on Applied System Invention (ICASI), pp. 342-345, Chiba(Tokyo), Japan, 2018.

5. K. C. Liang, C. S. Tseng, J. H. Wang, and H. W. Huang, ¡§Complete Contours Formation via Alignment Interpretation of Illusory Edges,¡¨IEEE 7th International Workshop on Computational Intelligence and Applications (IWCIA 2014), Hiroshima, Japan, Nov. 7-8, 2014.

6. C. S. Tseng, S. C. Tsai, C. W. Lin, C. T. Lin, Y. H. Wang, B. Y. Huang, and J. H. Wang, ¡§Novel Boundary Determination Algorithm for Lane Detection,¡¨ International Conference on Connected Vehicles and Expo (ICCVE 2013), pp. 598-603, Las Vegas, Nevada, U.S., Dec. 2-6, 2013.

7. C. S. Tseng, C. T. Lin, C. W. Lin, and J. H. Wang, ¡§Perceptual Edges Preservation Conformal to Human Vision Perception,¡¨ IEEE 13th International Conference on Information Reuse and Integration (IRI 2012), pp. 173-178, Las Vegas, Nevada, U.S., Aug. 8-10, 2012.

8. C. S. Tseng, C. W. Lin, C. D. Lin, S. C. Tsai, and J. H. Wang, ¡§Entropy-weighted Bayesian Approach to Edge Finding for Object Perception,¡¨ IEEE/SICE Int. Symp. on System Integration (Sll 2011), pp. 1293-1298, Kyoto, Japan, Dec. 20-22, 2011.

9. C. S. Tseng, K. L. Kuo, Y. T. Tsai, H. E. Lan, and J. H. Wang, ¡§Significant Edge Finding in View of Human Perception,¡¨ IEEE/SICE Int. Symp. on System Integration (Sll 2011), pp. 84-89, Kyoto, Japan, Dec. 20-22, 2011.

10. C. S. Tseng, K. T. Wang, M. C. Wu, N. Y. Cheng, and J. H. Wang, ¡§Retrospective tracking for barcode reading,¡¨ The 8th IEEE International Conference on Industrial Informatics (INDIN 2010), pp. 114-119, Osaka, Japan, July 13-16, 2010.

11. C. P. Tseng, K. T. Wang, M. C. Wu, C. S. Tseng, and J. H. Wang, ¡§Combining Signature Method and Linear Filtering for Convex Polygon Detection in Slanted Images,¡¨ The 23th IPPR Conference on Computer Vision, Graphics and Image Processing (CVGIP 2010), PP. 0546, Kaohsiung, Aug. 15-17, 2010.

12. C. Y. Cheng, C. S. Tseng, K. T. Wang, T. I. Peng, C. F. Lin, and J. H. Wang, ¡§HHT-Based Scalp Map For Capturing Transient EEG Event, ¡¨ The 22th IPPR Conference on Computer Vision, Graphics and Image Processing (CVGIP 2009), pp.798-803, Chi-Tou, Taiwan, August 23-25, 2009.

13. Y. C. Chen, H. J. Shih, Y. S. Jheng, S. Y. Shen, M. D. Guo, and J. H. Wang, ¡§Clustering based on Generalized Inverse Transformation,¡¨ IEEE International Conference on Systems, Man, and Cybernetics (SMC 2008), pp. 3045-3050, Singapore, Oct. 12-15, 2008.

14. J. S. Yu, M. C. Jhuang, K. C. Yang, and J. H. Wang, ¡§Multi-object Segmentation Using Probabilistic Labeling,¡¨ IEEE International Conference on Systems, Mad Cybernetics (SMC 2008), Suntec Singapore International Convention Exhibition Centre, pp. 1026-1030, Singapore, Oct. 12-15, 2008.

15. K. C. Chieh, M. C. Jhuang, C. S. Tseng, J. S. Yu, and J. H. Wang, ¡§Improved Segmentation Based on Probabilistic Labeling,¡¨ The 2008 International Conference on Bioinformatics and Computational Biology (BIOCOMP'08), pp. 563-567, Las Vegas, USA, July 14-17, 2008.

16. Y. C. Chen, Y. S. Jheng, H. J. Shih, and J. H. Wang, ¡§Clustering via Dimension Extension and Pseudo-inverse Transformation,¡¨ 2008 National Symposium on System Science and Engineering (NSSSE' 08), Ilan, Taiwan, June 6-7, 2008.

17. C. S. Tseng, Y. Y. Jheng, S. Y. Shen, and J. H. Wang, ¡§Fast Symmetric Keys Generation via Mutual Mirroring Process,¡¨ 2008 IEEE World Congress on Computational Intelligence (WCCI 2008), pp. 3162-3166, Hong Kongm, June 1-6, 2008.

18. M. D. Guo, J. T. Lai, C. S. Tseng, and J. H. Wang, ¡§Information Security for Products Record in Wireless Sensory System,¡¨ 2008 RFID¬ì§Þ½×¤å¬ã°Q·|, Taipei, Feb. 1, 2008.

19. Y. C. Chen, K. H. Wu, J. T. Lai, and J. H. Wang, ¡§Scale Shrinking Transformation and Applications,¡¨ 3rd International Conference on Soft Computing and Intelligent Systems and 7th International Symposium on advanced Intelligent Systems (SCIS & ISIS 2006), pp.698-703, Tokyo, Japan, September 20-24, 2006.

20. S. Y. Shen, Y. Y. Jheng, C. S. Tseng, and J. H. Wang, ¡§Image Segmentation via Fusion Neural Networks ,¡¨ 2006 3rd International Conference on Soft Computing and Intelligent Systems and 7th International Symposium on advanced Intelligent Systems, pp.1135-1140, Tokyo Institute of Technology, September 20-24, 2006.

21. C. C. Ting, J. S. Yu, C. S. Tseng, and J. H. Wang, ¡§Improved Snake Model for Fast Image Segmentation,¡¨ International Joint Conference on Neural Networks (IJCNN '06), pp. 3936-3941, Vancouver, BC, Canada, July 16-21, 2006.

22. K. H. Wu, and J. H. Wang, ¡§Validation-Driven Algorithm for SVC,¡¨12th International Conference on Neural Information Processing, pp.782-787, Taipei, Taiwan, Octorber 30~Novermber 2, 2005.

23. C. M. Lin, K. H. Wu, and J. H. Wang, ¡§Scale Equalized Higher-order Neural Networks,¡¨ IEEE International Conference on Systems, Man and Cybernetics, vol. 1, pp.816-821, Waikoloa, Hawaii, Oct. 10-12, 2005.

24. C. Y. Chong, F.C. Chang, and J. H. Wang, ¡§Fast Image Segmentation via Double-layer Infiltration,¡¨ IEEE International Conference on Systems, Man and Cybernetics, vol. 3, pp. 2944-2949, Waikoloa, Hawaii, October 10-12, 2005.

25. S. H. Chen, M. J. Kuo, and J. H. Wang, ¡§Image Segmentation Based on Consensus Voting,¡¨ The 9th International Workshop on Cellular Neural Networks and Their Applications, pp. 1-4, Hsinchu, Taiwan, May 28-30, 2005.

26. C. C. Wu, and J. H. Wang, ¡§Higher-order Neural Networks using Scale Equalization,¡¨ The Twelfth National Conference on Fuzzy Theory and Its Applications, Yilan, Taiwan, Nov. 2004.

27. C. M. Lin, K. H. Wu, and J. h. Wang, ¡§Scale Equalization Higher-Order Neural Networks,¡¨ IRI 2004. Proceedings of the 2004 IEEE International Conference on Information Reuse and Integration, pp. 612-617, Las Vegas, NV, USA, Nov. 8-10, 2004.

28. M. J. Kuo, C. C. Ting, and J. H. Wang, ¡§Selective Block Matching Algorithm for Video System,¡¨ IRI 2004. Proceedings of the 2004 IEEE International Conference on Information Reuse and Integration, pp. 163-167,Las Vegas, USA, Nov. 8-10, 2004.

29. F. C. Chang, F. W. Su, and J. H. Wang, ¡§A New Region-Based Approach for Image Segmentation,¡¨ IPPR Conference on Computer Vision, Graphics and Image Processing (CVGIP¡¦0)¡AHualien, Taiwan, Aug. 2004.

30. C. C. Wu, C. J. Huang, and J. H. Wang, ¡§Image Processing for Remotely Teleoperated Robotic Manipulator System for Underwater Operations,¡¨ UT '04. 2004 International Symposium on Underwater Technology, pp. 411-415, Apr. 20-23, 2004.

31. S. H. Chen, H. N. Chi, and J. H. Wang, ¡§Image segmentation via double pulse coupled neural network,¡¨ IEEE International Conference on Systems, Man and Cybernetics, vol. 3, pp. 2599-2604, Oct. 5-8, 2003.

32. C. Y. Chang, F. W. Su, and J. H. Wang, ¡§Clustering via codeword-agglomerating neural networks,¡¨ IEEE International Conference on Systems, Man, and Cybernetics, vol. 2, pp. 1618-1623, Oct. 5-8, 2003.

33. C. C. Wu, C. J. Huang, and J. H. Wang, ¡§Speckle noise Reduction for ultrasonic images,¡¨ IEEE International Conference on Systems, Man, and Cybernetics, vol. 5, pp. 4165-4170, Oct. 2003.

34. C. Y. Chang, W. S. Shie, and J. H. Wang, ¡§Color image segmentation via fuzzy feature tuning and feature adjustment,¡¨ Tenth National Conference on Fuzzy Theory and Its Applications, E5-pp. 11-15, 2002.

35. C. Y. Chang, W. S. Shie, and J. H. Wang, ¡§Color image segmentation via fuzzy Feature tuning and feature adjustment,¡¨ IEEE International Conference on Systems, Man and Cybernetics, vol. 4, pp. 1062-922X, Oct. 6-9, 2002.

36. C. J. Huang, H. S. Wong, and J. H. Wang, ¡§Selective block matching for error concealment in video system,¡¨ IEEE International Conference on Systems, Man, and Cybernetics, vol. 3, pp. 1062-922X, Oct. 6-9, 2002.

37. C. C. Lin, C. C. Chang, M. D. Jeng, and J. H. Wang, ¡§Development of an intelligent underwater robotic manipulator system,¡¨ MTS/IEEE Conference and Exhibition OCEANS, vol. 2, pp. 1036-1040, Honolulu, HI, USA, 2001.

38. C. W. Wu, J. L. Chen, and J. H. Wang, ¡§Self-organizing mountain method for clustering,¡¨ IEEE International Conference on Systems, Man, and Cybernetics, vol. 4, pp. 2434-2438, Tucson, AZ, USA, Oct. 2001.

39. K. C. Tsai, R. D. Rau, and J. H. Wang, ¡§Clustering via C-spheres agglomeration,¡¨ IEEE International Conference on Systems, Man, and Cybernetics, vol. 4, pp. 2428-2433, Tucson, AZ, USA, Oct. 2001.

40. C. H. Huang, Y. W. Yu, and J. H. Wang, ¡§A fuzzy-based feature tuning algorithm applied to image segmentation,¡¨ IEEE International Conference on Systems, Man, and Cybernetics, vol. 4, pp. 2140-2144, Tucson, AZ, USA, Oct. 2001.

41. K. C. Tsai, and J. H. Wang, ¡§Fast Motion Estimation in Video Coding,¡¨ NCS'2001, vol. D, pp.D168-D171 , Dec. 2001.

42. H. J, H. S. Wong, and J. H. Wang, ¡§A novel cellular search algorithm for block-matching motion estimation,¡¨ Proceedings. International Conference on Information Technology: Coding and Computing, pp. 629-633, Las Vegas, NV, USA, Apr. 2001.

43. H. Huang, and J. H. Wang, ¡§Anisotropic diffusion for object segmentation,¡¨ IEEE International Conference on Systems, Man, and Cybernetics, vol. 3, pp. 1563-1567, Nashville, TN, USA, 2000.

44. C. H. Huang, and J. H. Wang, ¡§Stereo correspondence using Hopfield network with multiple constraints,¡¨ IEEE International Conference on Systems, Man, and Cybernetics, vol.2, pp. 1518-1523, Nashville, TN, USA, 2000.

45. J. Hung, and J. H. Wang, ¡§Topology preserving using harmonic competitive neural networks,¡¨ IEEE International Conference on Systems, Man, and Cybernetics, vol.4, pp. 2597-2599, Nashville, TN, USA, 2000.

46. H. S. Wong, and J. H. Wang, ¡§Contrast enhancement based on divided histogram manipulation,¡¨ IEEE International Conference on Systems, Man, and Cybernetics, vol.2, pp. 1551-1555, Nashville, TN, USA, 2000.

47. J. H. Tsai, and J. H. Wang, ¡§Using self-creating neural network for Surface reconstruction,¡¨ IEEE SMC '99 Conference Proceedings. 1999 IEEE International Conference on Systems, Man, and Cybernetics, vol. 4, pp. 886-890, Tokyo, Japan, 1999.

48. J. D. Rau, and J. H. Wang, ¡§A voting principle of multiple features for Chinese character recognition system using neural network classifiers,¡¨ IEEE SMC '99 Conference Proceedings. 1999 IEEE International Conference on Systems, Man, and Cybernetics, vol. 6, pp. 874-878, Tokyo, Japan, 1999.

49. J. L. Chen, and J. H. Wang, ¡§A new robust clustering algorithm-density-weighted fuzzy C-means,¡¨ IEEE SMC '99 Conference Proceedings. 1999 IEEE International Conference on Systems, Man, and Cybernetic, vol. 3, pp. 90-94, Tokyo, Japan, 1999.

50. Y. W. Yu, and J. H. Wang, ¡§Image segmentation based on region growing and edge detection,¡¨ IEEE SMC '99 Conference Proceedings. 1999 IEEE International Conference on Systems, Man, and Cybernetic, vol. 6, pp. 798-803, Tokyo, Japan, 1999.

51. ¤ýºaµØ¡B¾G¼}¼w¡BªLÂí¬w¡B±i«í¼Ý¡B±i©¾¸Û¡A¡§´¼¼z«¬¤ô¤U¾÷±ñÁu¤§¬ã¨s¡¨¡A ²Ä¤@©¡¤ô¤U§Þ³N¬ã°Q·|¡A¥x¥_¡App. 33-40, 1998.

52. J. H. Wang, and K. J. Gou, ¡§Image compression using wavelet transform and self-development neural network,¡¨ IEEE International Conference on Systems, Man, and Cybernetics, vol. 4, pp. 4104-4108, San Diego, CA, USA, 1998.

53. J. H. Wang, and C. Y. Chung, ¡§Optimal clustering using neural network,¡¨ IEEE International Conference on Systems, Man, and Cybernetics, vol. 2, pp. 1625-1630, San Diego, CA, USA, 1998.

54. J. H. Wang, and L. D. Lin, ¡§Image restoration using parametric adaptive fuzzy filter,¡¨ Conference of the North American Fuzzy Information Processing Society - NAFIPS, pp. 198-202, Pensacola Beach, FL, USA, 1998.

55. J. H. Wang, and M. C. Tsai, ¡§Learning recognition of temporal sequences by coding temporal distance in neural networks,¡¨ IEEE World Congress on Computational Intelligence. The 1998 IEEE International Joint Conference on Neural Networks Proceedings, vol.2, pp. 1422-1427, Anchorage, AK, USA, 1998.

56. J. H. Wang, and W. D. Sun, ¡§Self-development competitive learning VQ based on vitality conservation networks,¡¨ IEEE World Congress on Computational Intelligence. The 1998 IEEE International Joint Conference on Neural Networks Proceedings, vol.2, pp. 885-890, Anchorage, AK, USA, 1998.

57. J. H. Wang, and S. M. Chen, ¡§Evolutionary stock trading decision support system using sliding window,¡¨ IEEE World Congress on Computational Intelligence., The 1998 IEEE International Conference on Evolutionary Computation Proceedings, 1998., pp. 253-258, Anchorage, AK, USA, 1998.

58. M. C. Tsai, and J. H. Wang, ¡§Learning recognition and reproduction of complex sequences using dynamic-weight neural network,¡¨ ISMIP¡¦97 Proceeding, International Symposium on Multimedia Information Processing, pp. 250-255, Academia Sinica, Taipei, Taiwan, 1997.

59. J. H. Wang, and W. D. Sun, ¡§Self-development competitive learning VQ,¡¨Proc. 1997 Workshop on Consumer Electronics: Digital Video and Multimedia, A1-2, pp. 7-12, Taipei, Taiwan, 1997.

60. J. H. Wang, and C. P. Hsiao, ¡§Image segmentation using self-development neural network, applied to active stereo vision,¡¨ ETFA '97., 1997 6th International Conference on Emerging Technologies and Factory Automation Proceedings, pp. 359-364, Los Angeles, CA, USA, Sep. 1997.

61. J. H. Wang, and T. H. Chien, ¡§Optimizing the resolution level in wavelet transform -- applied to image restoration,¡¨ Computational Cybernetics and Simulation., 1997 IEEE International Conference on Systems, Man, and Cybernetics, vol.3, pp. 2666-2671, Orlando, FL, USA, Oct. 1997.

62. J. H. Wang, and M. C. Tsai, ¡§Learning complex temporal sequence using bi-directional spatiotemporal neural network,¡¨ Computational Cybernetics and Simulation., 1997 IEEE International Conference on Systems, Man, and Cybernetics, vol.5, pp.4121-4126, Orlando, FL, USA, 1997.

63. J. H. Wang, and J. Y. Leu, ¡§Stock market trend prediction using ARIMA-based neural networks,¡¨ IEEE International Conference on Neural Networks, vol. 4, pp. 2160-2165, Washington, D.C., USA, 1996.

64. J. H. Wang, and C. P. Hsiao, ¡§Stereo matching by neural networks that uses Sobel feature data,¡¨ IEEE International Conference on Neural Networks, vol. 3, pp. 1801-1806, Washington, D.C., USA, 1996.

65. J. H. Wang, and J. Y. Leu, ¡§Dynamic trading decision support system using rule selector based on genetic algorithms,¡¨ Proceedings of the 1996 IEEE Signal Processing Society Workshop Neural Networks for Signal Processing [1996] VI., pp. 119-128, Kyoto, Japan, 1996.

66. J. H. Wang, and M. D. Yu, ¡§Image restoration by adaptive fuzzy optimal filter,¡¨ Intelligent Systems for the 21st Century., IEEE International Conference on Systems, Man and Cybernetics, vol.1, pp. 845-848, Vancouver, BC, Canada, 1995.

67. J. H. Wang, and M. D. Yu, ¡§Image restoration by adaptive fuzzy backpropagation hybrid network,¡¨ Proceedings. IEEE International Conference on Neural Networks, vol. 3, pp. 1438-1443, Perth, WA, Australia, 1995.

68. J. H. Wang, and R. F. Hsieh, ¡§Harmonic control of a planar complex using limited-path-guidance learning,¡¨ Proceedings. IEEE International Conference on Neural Networks, vol.5, pp. 2530-2535, Perth, WA, Australia, 1995.

69. J. H. Wang, and J. H. Lin, ¡§Adaptive spatiotemporal neural network for speech recognition,¡¨ Proceedings., IEEE International Conference on Neural Networks, vol. 5, pp. 2876-2881, Perth, WA, Australia, 1995.

70. J. H. Wang, and R. F. Hsieh, ¡§On the neural learning and harmonic control of a planar complex,¡¨ Intelligent Systems for the 21st Century., IEEE International Conference on Systems, Man and Cybernetics, vol. 4, pp. 3255-3258, Vancouver, BC, Canada, 1995.

71. J. H. Wang, and J. H. Lin, ¡§Qualitative analysis of a BP network composed of product units,¡¨ Intelligent Systems for the 21st Century., IEEE International Conference on Systems, Man and Cybernetics, vol. 1, pp. 35-39, Vancouver, BC, Canada, 1995.

72. H. Y. Shyr, and J. H. Wang, ¡§Speaker-dependent continuous speech recognition using a spatio-temporal neural network,¡¨ 1994 International Symposium on Artificial Neural Networks (ISANN'94), pp. 541-546, Tainan, Taiwan, 1994.

73. J. H. Wang, and G. Lin, ¡§On the learning dynamic of spatiotemporal neural networks,¡¨ IEEE World Congress on Computational Intelligence., 1994 IEEE International Conference on Neural Networks, vol. 5, pp. 3201-3206, Orlando, Fl, USA, 1994.

74. J. H. Wang, and M. D. Jeng, ¡§Performance characterization of product unit neural network associative memories,¡¨ The 9th International Conference on CAD/CAM, Robotics and Factories of the Future, Newark, NJ, USA, Aug. 1993.

75. J. H. Wang, ¡§Characterization of a Higher-order associative memory that uses product units,¡¨ 'Systems Engineering in the Service of Humans', Conference Proceedings., International Conference on Systems, Man and Cybernetics, vol. 2, pp. 636-639, Le Touquet, France, 1993.

76. J. H. Wang, ¡§Indirect convergence neural network associative memory,¡¨ Proceedings of the 35th Midwest Symposium on Circuits and Systems, 1992., vol.2, pp. 1377-1380, Washington, DC, 1992.

77. J. H. Wang, ¡§On a neural network associative memory that uses indirect convergence,¡¨ IEEE International Conference on Systems, Man and Cybernetics, 1992., vol. 2, pp. 1033-1037, Chicago, IL, USA, 1992.

78. J. H. Wang, T. F. Krile, and J. F. Walkup, ¡§Reduction of interconnection weights in higher order associative memory networks,¡¨ IJCNN-91-Seattle International Joint Conference on Neural Networks, 1991., vol. 2, pp. 177-182, Seattle, WA, USA, 1991.

79. J. H. Wang, T. F. Krile, and J. F. Walkup, ¡§Figures of merit for the Performance of Hebbian-type associative memories,¡¨ 1990 IJCNN International Joint Conference on Neural Networks, 1990., vol. 1, pp. 833-838, San Diego, CA, USA, 1990.