Recent research has shown that collective classification in relational data often exhibit significant performance gains over conventional approaches that classify instances indi...
We consider learning models for object recognition from examples. Our method is motivated by systems that use the Hausdorff distance as a shape comparison measure. Typically an ob...
Multi-class image segmentation has made significant advances in recent years through the combination of local and global features. One important type of global feature is that of i...
Stephen Gould, Jim Rodgers, David Cohen, Gal Elida...
We present a bottom-up approach for automatic cancer cell detection in multispectral microscopic thin Pap smear images. Around 4,000 multispectral texture features are explored fo...
—We propose an approach for improving object recognition and localization using spatial kernels together with instance embedding. Our approach treats each image as a bag of insta...