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ECCV
2008
Springer
16 years 3 months ago
Compressive Sensing for Background Subtraction
Abstract. Compressive sensing (CS) is an emerging field that provides a framework for image recovery using sub-Nyquist sampling rates. The CS theory shows that a signal can be reco...
Volkan Cevher, Aswin C. Sankaranarayanan, Marco F....
SIGCSE
2005
ACM
146views Education» more  SIGCSE 2005»
15 years 7 months ago
Using image processing projects to teach CS1 topics
As Computer Science educators, we know that students learn more from projects that are fun and challenging, that seem “real” to them, and that allow them to be creative in des...
Richard Wicentowski, Tia Newhall
ECAI
2006
Springer
15 years 5 months ago
Efficient Knowledge Acquisition for Extracting Temporal Relations
Abstract. Machine learning approaches in natural language processing often require a large annotated corpus. We present a complementary approach that utilizes expert knowledge to o...
Son Bao Pham, Achim G. Hoffmann
COLING
2002
15 years 1 months ago
Unsupervised Named Entity Classification Models and their Ensembles
This paper proposes an unsupervised learning model for classifying named entities. This model uses a training set, built automatically by means of a small-scale named entity dicti...
Jae-Ho Kim, In-Ho Kang, Key-Sun Choi
ICONIP
2004
15 years 3 months ago
Variational Information Maximization for Neural Coding
Abstract. Mutual Information (MI) is a long studied measure of coding efficiency, and many attempts to apply it to population coding have been made. However, this is a computationa...
Felix V. Agakov, David Barber