Equipment
Support to Experimenting Novel Computation Models
Equipment
Support to Experimenting Novel Computation Models
Sponsor: Air Force Office of Scientific Research
This project addresses the equipment support to the existing research effort and the related education need for experimenting novel computation models at the computer science department of State University of New York at Binghamton. This is part of the DoD DURIP Program managed by US Air Force Office of Scientific Research (AFOSR).
Project Personnel:
PIs:
Prof. Zhongfei (Mark) Zhang(SUNY Binghamton)
Prof. Nael Abu-Ghazaleh(SUNY Binghamton)
AFOSR Program Managers:
Maj. Amy Magnus, PhD
Dr. David Luginbuhl
Publications:
Duane Gilmour and Zhongfei (Mark) Zhang, Determining Course of Action Alignment with Operational Objectives, Proc. the 11th International Command and Control Research and Technology Symposium, Cambridge, UK, September, 2006, (accepted)
Ruofei Zhang and Zhongfei (Mark) Zhang, Effective Image Retrieval Based on Hidden Concept Discovery in Image Database, IEEE Transaction on Image Processing, Volume 16, Number 2, February, 2006, pp 562 -- 572
Arif Ghafoor, Zhongfei (Mark) Zhang, Michael S. Lew, and Zhi-Hua Zhou, Guest Editors' Introduction to Machine Learning Approaches to Multimedia Information Retrieval, ACM Multimedia Systems Journal, Springer, 2006
Zhongfei (Mark) Zhang, Querying Non-Uniform Image Databases for Biometrics-Related Identification Applications, Sensor Review, Emerald Publishers, Volume 26, Number 2, April, 2006, pp 122-126
Ruofei Zhang and Zhongfei (Mark) Zhang, Empirical Bayesian Learning in the Relevance Feedback of Image Retrieval, Image and Vision Computing, Elsevier Science, Volume 24, Issue 3, March, 2006, pp 211-2233
Ruofei Zhang, Zhongfei (Mark) Zhang, Mingjing Li, Wei-Ying Ma, and Hong-Jiang Zhang, A Probabilistic Semantic Model for Image Annotation and Multi-Modal Image Retrieval, ACM Multimedia Systems Journal, the special issue of Using Machine Learning Approaches to Multimedia Information Retrieval, Springer, 2006
Jian Yao and Zhongfei (Mark) Zhang, Hierarchical Shadow Detection for Color Aerial Images, Computer Vision and Image Understanding, Elsevier Science, Volume 102, Issue 1, April, 2006, pp 60-69
Bo Long, Xiaoyun Wu,
Zhongfei (Mark) Zhang, and Philip S. Yu, Unsupervised Learning on K-partite
Graphs, Proc. ACM International Conference on Knowledge Discovery and Data
Mining, ACM Press, Philadelphia, PA, USA, August, 2006
[pdf]
Bo Long, Zhongfei (Mark) Zhang, Xiaoyun Wu, and Philip S. Yu, Spectral Clustering for Multi-Type Relational Data, Proc. International Conference on Machine Learning, ACM Press, Pittsburgh, PA, USA, June, 2006[pdf]
Xiao-Bing Xue, Zhi-Hua Zhou, and Zhongfei (Mark) Zhang, Improve Web Search Using Image Snippets, Proc. the 21st National Conference on Artificial Intelligence, AAAI Press, Boston, MA, USA, July, 2006
Jian Yao, Zhongfei (Mark) Zhang, Sameer Antani, Rodney Long, and George Thoma, Automatic Medical Image Annotation and Retrieval Using SEMI-SECC, Proc. IEEE International Conference on Multimedia and Expo, IEEE Computer Society Press, Toronto, Canada, July, 2006
Jian Yao, Sameer
Antani, Rodney Long, and George Thoma, and Zhongfei (Mark) Zhang, Automatic
Medical Image Annotation and Retrieval Using SECC, Proc. IEEE International
Symposium on Computer Based Medical Systems, IEEE Computer Society Press,
Salt Lake City, Utah, USA, June, 2006[pdf]
This material is based upon the work supported by the Air Force Office of Scientific Research under project No. FA9550-06-1-0327.
Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the Air Force Office of Scientific Researc.