One-class kernel subspace ensemble for medical image classification
نویسندگان
چکیده
منابع مشابه
One-class kernel subspace ensemble for medical image classification
Classification of medical images is an important issue in computer-assisted diagnosis. In this paper, a classification scheme based on a one-class kernel principle component analysis (KPCA) model ensemble has been proposed for the classification of medical images. The ensemble consists of one-class KPCA models trained using different image features from each image class, and a proposed product ...
متن کاملApproximate polytope ensemble for one-class classification
In this work, a new one-class classification ensemble strategy called approximate polytope ensemble is presented. The main contribution of the paper is threefold. First, the geometrical concept of convex hull is used to define the boundary of the target class defining the problem. Expansions and contractions of this geometrical structure are introduced in order to avoid over-fitting. Second, th...
متن کاملKernel Whitening for One-Class Classification
In one-class classification one tries to describe a class of target data and to distinguish it from all other possible outlier objects. Obvious applications are areas where outliers are very diverse or very difficult or expensive to measure, such as in machine diagnostics or in medical applications. In order to have a good distinction between the target objects and the outliers, good representa...
متن کاملMultiple Similarities Based Kernel Subspace Learning for Image Classification
In this paper, we propose a new method for image classification, in which matrix based kernel features are designed to capture the multiple similarities between images in different low-level visual cues. Based on the property that dot product kernel can be regarded as a similarity measure, we apply kernel functions to different low-level visual features respectively to measure the similarities ...
متن کاملOnline Learning with Regularized Kernel for One-class Classification
This paper presents an online learning with regularized kernel based one-class extreme learning machine (ELM) classifier and is referred as “online RK-OC-ELM”. The baseline kernel hyperplane model considers whole data in a single chunk with regularized ELM approach for offline learning in case of one-class classification (OCC). Further, the basic hyper plane model is adapted in an online fashio...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: EURASIP Journal on Advances in Signal Processing
سال: 2014
ISSN: 1687-6180
DOI: 10.1186/1687-6180-2014-17