Exploding amounts of multimedia data increasingly require automatic indexing and classification, e.g. training classifiers to produce high-level features, or semantic concepts, ch...
Wei Jiang, Eric Zavesky, Shih-Fu Chang, Alexander ...
This paper presents a procedure aimed at recognizing environmental sounds for surveillance and security applications. We propose to apply One-Class Support Vector Machines (1-SVMs...
kernel canonical correlation analysis (KCCA) is a recently addressed supervised machine learning methods, which shows to be a powerful approach of extracting nonlinear features for...
We propose an algorithm for extracting fields from HTML search results. The output of the algorithm is a database table– a data structure that better lends itself to high-level...
We propose a novel method for identifying road vehicles between two non-overlapping cameras. The problem is formulated as a same-different classification problem: probability of t...