Ali Zarghami

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While recent supervised dictionary learning methods have attained promising results on the classification tasks, their performance depends on the availability of the large labeled datasets. However, in many real world applications, accessing to sufficient labeled data may be expensive and/or time consuming, but its relatively easy to acquire a large amount(More)
A Bayesian framework for 3-D human pose estimation from monocular images based on sparse representation (SR) is introduced. Our probabilistic approach aims at simultaneously learning two overcomplete dictionaries (one for the visual input space and the other for the pose space) with a shared sparse representation. Existing SR-based pose estimation(More)
Distance metric learning is a powerful approach to deal with the clustering problem with side information. For semi-supervised clustering, usually a set of pairwise similarity and dissimilarity constraints is provided as supervisory information. Although some of the existing methods can use both equivalence (similarity) and inequivalence (dissimilarity)(More)
In many real-world applications (e.g. social media application), data usually consists of diverse input modalities that originates from various heterogeneous sources. Learning a similarity measure for such data is of great importance for vast number of applications such as classification, clustering, retrieval, etc. Defining an appropriate distance metric(More)
This paper proposes a novel Dictionary Learning (DL) algorithm for pattern classification tasks. Based on the Distance Dependent Indian Buffet Process (DDIBP) model, a shared dictionary for signals belonging to different classes is learned so that the learned sparse codes are highly discriminative which can improve the pattern classification performance.(More)
Computer-Aided Diagnosis (CAD) systems are widely used for detection of various kinds of abnormalities in mammography images. Masses are one type of these abnormalities which are mostly characterized by their margin and shape. For classification of masses proper features are needed to be extracted. However, the number of well-known features for describing(More)
The objective of this study to investigate the clinical signs of Newcastle Disease (ND) in infected broiler farms of Iran Northwest and to determine serological status of this flocks and healthy flocks. Also the mortality was compared in healthy and infected flocks. From 22 broiler flocks blood samples were collected and examined with HI test. Mortality(More)
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