Quantization is intrinsic to several data acquisition systems. This process is especially important in distributed settings, where observations must rst be compressed before they ...
Learning from streams of evolving and unbounded data is an important problem, for example in visual surveillance or internet scale data. For such large and evolving real-world data...
Chen Change Loy, Timothy M. Hospedales, Tao Xiang,...
Abstract - A robust method for symbol recognition is presented that utilizes a compact signature based on a modified Hough Transform (HT) and knowledge-based hierarchical neural ne...
In order to become an effective complement to traditional Web-scale text-based image retrieval solutions, content-based image retrieval must address scalability and efficiency iss...
The paper introduces symbolic bisimulations for a simple probabilistic π-calculus to overcome the infinite branching problem that still exists in checking ground bisimulations b...