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Cervical cancer is one of the most common types of cancer in women worldwide. Most deaths due to the disease occur in less developed areas of the world. In this work, we introduce a new image dataset along with expert annotated diagnoses for evaluating image-based cervical disease classification algorithms. A large number of Cervigram® images are selected from a database provided by the US National...
Cervical cancer is the third most common type of cancer in women worldwide. Most death cases of cervical cancer occur in less developed areas of the world. In this work, we develop an automated and low-cost method that is applicable in those low-resource regions. First, we propose a more distinctive multi-feature descriptor for encoding the cervical image information by enhancing an existing descriptor...
Object-based image analysis (OBIA) in combination with domain knowledge is an important methodology for remote sensing image interpretation. It can deal with semantic gap effectively. In this paper, a knowledge-based procedure for remote sensing image classification is presented. Domain knowledge is represented with semantic network, which guides the initial classification of the image. A quantitative...
We compare the scene classification performance of 13 features, including structure, texture and color features. First, image classification are performed using a single feature and the performance of different features are compared. Both the k-nearest-neighbor (KNN) classifier and the support vector machine classifier (SVM) are employed. And for the KNN classifier, we use four different distance...
In this paper, we propose a novel and simple method for people and vehicles classification in far distance video surveillance. In this approach, moving objects are firstly segmented from background using a background subtraction technique. Secondly, edges of moving objects are extracted using canny operator. Then straight lines of edges of moving objects are extracted by Hough transform and feature...
3D data registration and classifier are two important components in face recognition system. Aiming at the handicaps in current methods such as slow convergence or easiness of getting into local optimization, this paper works out a novel face recognition method combining filled function method, which can find a lower local minimizer by leaving the local minimizer previously found. By repeating these...
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