By formulating the problem of ordering the outputs observed from a device over time, we pose a new problem in forensics and propose a framework for addressing this problem of devi...
Junwen Mao, Orhan Bulan, Gaurav Sharma, Suprakash ...
To become robust, a tracking algorithm must be able to support uncertainty and ambiguity often inherently present in the data in form of occlusion and clutter. This comes usually ...
Abstract. Interactively learning from a small sample of unlabeled examples is an enormously challenging task. Relevance feedback and more recently active learning are two standard ...
Charlie K. Dagli, ShyamSundar Rajaram, Thomas S. H...
We treat the problem of edge detection as one of statistical inference. Local edge cues, implemented by filters, provide information about the likely positions of edges which can ...
Scott Konishi, Alan L. Yuille, James M. Coughlan, ...
Most approaches to learn classifiers for structured objects (e.g., images) use generative models in a classical Bayesian framework. However, state-of-the-art classifiers for vecto...