We use unsupervised probabilistic machine learning ideas to try to explain the kinds of learning observed in real neurons, the goal being to connect abstract principles of self-or...
Probabilistic language models are critical to applications in natural language processing that include speech recognition, optical character recognition, and interfaces for text e...
Rule bases are common in many business rule applications, clinical decision support programs, and other types of intelligent systems. As the size of the rule bases grows and the in...
First IEEE International Workshop on Biologically Motivated Computer Vision, Seoul, Korea (May 2000). There is considerable evidence that object recognition in primates is based o...
Abstract. Objective image and video quality measures play important roles in numerous image and video processing applications. In this work, we propose a new content-weighted metho...