- Presentation schedule -final; 6 May 2008 Time w10 -12 May w11-19 May w12 -26 May w13 -2 June
- Biographies. Charles L. Wilson has worked in various areas of computer modeling ranging from semi
- Fingerprint Classification \Lambda Kalle Karu and Anil K. Jain
- Learning to Classify Biomedical Signals
- Signal Processing: Image Communication, v.16 (2001), pp. 477500 TEMPORAL VIDEO SEGMENTATION: A SURVEY
- Abstract--In this paper we propose a new graph-based feature splitting algorithm maxInd, which creates a balanced
- Multimedia Tools and Applications, 2002, vol. 8, pp. 187-212, Springer HYBRID RULE-BASED/NEURAL APPROACH FOR SEGMENTATION OF MPEG
- VideoGCS -A Clustering-Based System for Video Summarization and Browsing
- T. Theeramunkong et al. (Eds.): PAKDD Workshops 2009, LNAI 5669, pp. 100111, 2010. Springer-Verlag Berlin Heidelberg 2010
- A Hill-climbing Landmarker Generation Algorithm Based on Efficiency and Correlativity Criteria
- A Landmarker Selection Algorithm Based on Correlation and Efficiency Criteria
- Phrases and Feature Selection in E-Mail Classification Elisabeth Crawford
- Proceedings of the 8th Australasian Document Computing Symposium,
- DNA MICROARRAY DATA CLUSTERING USING GROWING SELF ORGANIZING NETWORKS
- SCHOOL OF INFORMATION TECHNOLOGIES WiiPAINT++: PAINTING WITH THE Wii REMOTE
- Accurate and Efficient Selection of Voting Ensembles Technical Report Number 564
- INFO4990 Research Methods, s1 2008 Presentation -marking sheet
- INFO 4990: Information Technology Research Methods
- Comparing Feature-based and Clique-based User Models for Movie Selection
- Neural Network Fingerprint Classification C. L. Wilson
- Fingerprint Classification and Matching Anil Jain Sharath Pankanti
- A Hill-climbing Landmarker Generation Algorithm Based on Efficiency and Correlativity Criteria
- Automatic Fingerprint Verification Using Neural Anna Ceguerra and Irena Koprinska
- Learning to Classify E-mail Irena Koprinska, Josiah Poon, James Clark, Jason Chan
- Code of practice for supervision of postgraduate research Approved by: Academic Board on 19 October 1992
- SEGMENTATION OF COMPRESSED VIDEO BY LEARNING VECTOR Irena Koprinska * and Sergio Carrato
- Monday, April 21, 2008 INFO4990 1 Statistics in Research
- Appears in Proceedings of the Fifth ACM Conference on Digital Libraries, pp.195240, June 2000 ContentBased Book Recommending
- Abstract--We present new approaches for 5-minute ahead electricity load forecasting. They were evaluated on data from
- IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING, MANUSCRIPT ID 1 Clustering and Sequential Pattern Mining of
- Almost junk: classifying public announcements for user communities
- Honours projects 2010 supervised by Irena Koprinska irena@it.usyd.edu.au
- INFO4990: Empirical Evaluation A case study in IR and NLP
- IMAGE CLASSIFICATION USING LABELLED AND UNLABELLED DATA Irena Koprinska1
- Comparisons between Heuristics Based on Correlativity and Efficiency for Landmarker Generation
- A Proposed Meta-learning Framework for Algorithm Selection Utilising
- A New Landmarker Generation Algorithm Based on Correlativity Daren Ler, Irena Koprinska and Sanjay Chawla
- Studies in Higher Education Volume 27, No. 4, 2002 `It's a PhD, not a Nobel Prize'
- Learning Collaborative Information Filters Daniel Billsus and Michael J. Pazzani
- Introduction Why Good Writing is Important
- INFO5993 Research Methods Presentation -marking sheet
- Finding someone you will like and who won't reject you
