Category: IEEE 2017

Active Contour Model with Entropy based Constraint for Image Segmentation

Active Contour Model with Entropy-based Constraint for Image Segmentation Abstract: For most existing image segmentation methods based on Active Contours, the contour evolutions tend to get trapped in local optima and thus cause the segmentation methods sensitive to contour initialization and deficient in dealing with noisy and inhomogeneous regions. Aiming at this problem, we propose […]


Modeling and Learning Distributed Word Representation with Metadata for Question Retrieval

Weakly Supervised Fine-Grained Categorization with Part-Based Image Representation Abstract In this paper, we propose a fine-grained image categorization system with easy deployment. We do not use any object/part annotation (weakly supervised) in the training or in the testing stage, but only class labels for training images. Fine-grained image categorization aims to classify objects with only subtle distinctions (e.g., two breeds of dogs that look alike). Most […]