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Question classification plays an important role in question answering. Features are the key to obtain an accurate question classifier. In contrast to Li and Roth (2002)'s approach which makes use of very rich feature space, we propose a compact yet effective feature set. In particular, we propose head word feature and present two approaches to augment(More)
We establish a new set of features for differentiating benign from malignant breast lesions using ultrasound (US) images. Two types of features (sonographic and textural features) are considered. Among them, three sonographic features are novel. Sonograms of 321 pathologically proven breast cases are analyzed and classified into benign and malignant(More)
We present an efficient technique based on histogram evolution for summarizing video sequences to make them more amenable to browsing and retrieval. First, a ground-truth database of videos is generated in which the shot breaks are detected by human subjects and numbered in order. Three types of histogram are then used to capture the characteristics of(More)
To diagnose breast cancer (BCa), the number of mitotic cells present in tissue sections is an important parameter to examine and grade breast biopsy specimen. The differentiation of mitotic from non-mitotic cells in breast histopathological images is a crucial step for automatical mitosis detection. This work aims at improving the accuracy of mitosis(More)
In this paper we construct a hybrid moving object detection system. In this system, we first use the frame difference method to extract key frames in a given video sequence, then use the optical flow method and the HSV background subtraction method to extract the moving objects, respectively. We propose two hybrid methods: Improved Optical Flow method and(More)
Despite progress in image retrieval by using low-level features , such as colors, textures and shapes, the performance is still unsatisfied as there are existing gaps between low-level features and high-level semantic concepts (semantic gaps). In this research, we propose a novel image retrieval system based on bag-of-features (BoF) model by integrating(More)
Keywords: Bag-of-features (BoF) Image retrieval Weighted K-means SIFT-LBP HOG-LBP Histogram intersection a b s t r a c t One of the biggest challenges in content based image retrieval is to solve the problem of " semantic gaps " between low-level features and high-level semantic concepts. In this paper, we aim to investigate various combinations of(More)
Label semantics is a random set framework for modelling with words. In previous work, several machine learning algorithms based on this semantics have been proposed and studied. In this paper, we introduce a new linguistic rule induction algorithm based on Quinlan's FOIL. According to this algorithm, a set of linguistic rules are generated for(More)