Abstract: In this paper we present a framework for the fusion of radar and image information. In the case considered here we combine information from multiple closerange radars to ...
—Object detection is challenging when the object class exhibits large within-class variations. In this work, we show that foreground-background classification (detection) and wit...
Quan Yuan, Ashwin Thangali, Vitaly Ablavsky, Stan ...
We introduce an approach to accurately detect and segment partially occluded objects in various viewpoints and scales. Our main contribution is a novel framework for combining obj...
This work is about scene interpretation in the sense of detecting and localizing instances from multiple object classes. We concentrate on object indexing: generate an over-comple...
We compare and contrast two different models for detecting sentence-like units in continuous speech. The first approach uses hidden Markov sequence models based on N-grams and max...
Yang Liu, Andreas Stolcke, Elizabeth Shriberg, Mar...