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The mismatch between the training data and the test data distributions is a challenging issue while designing many practical computer vision systems. In this paper, we propose a domain adaptation technique to tackle this issue. We are interested in a domain adaptation scenario where source domain has large amount of labeled examples and the target domain has large amount of unlabeled examples. We...
The recognition of legal amount present on a bank cheque is a big challenge because of the structural complexity of characters and variability of writing styles in automatic bank cheque processing. This paper proposes a technique of text word recognition based on template matching technique using Correlation coefficient. We have developed a database of 61 words, combination of which can represent...
Automated classification of music signal is an active area of research. It can act as the fundamental step for various applications like archival, indexing and retrieval of music data. In this work, a simple methodology is presented to categorize the music signals based on their genre. In order to capture the characteristics of the music signal of different genres, signal is first decomposed to extract...
Image fusion is the method of gathering information from images obtained from sensors of different modalities in order to create an image that is more detailed than the input images. This paper presents a novel method for fusion of low-resolution multispectral (MS) images with a high-resolution panchromatic (PAN) image using Stationary Wavelet Transform (SWT) and Independent Component Analysis (ICA)...
Normally, statistical methods are used to generate rankings for genes in terms of their ability to distinguish between normal and malignant tumors from a gene expression dataset. However, different statistical methods yield different ranks for same gene and there is no universally accepted method for ranking. Therefore rank aggregation is required to find the overall ranking of the set of genes. There...
The standard fuzzy C-means (FCM) algorithm does not fully utilize the spatial information for image segmentation and is sensitive to noise especially in the presence of intensity inhomogeneity in magnetic resonance imaging (MRI) images. The underlying reason is that a single fuzzy membership function in FCM algorithm cannot properly represent pattern associations to all clusters. In this paper, we...
In this paper, a parametric texture based video coding scheme is proposed for multi-view videos. The proposed scheme exploits the perceptual redundancy of the textured region in a statistical manner which is ignored in the multi-view video coding scheme of H.264/MVC. This statistical nature of texture is independent of the 3D scene structure. The set of most similar texture macroblocks over different...
Taking motivation from Twin Support Vector Machine (TWSVM), Peng (2009) attempted to propose Twin Support Vector Regression (TSVR) where regressor was obtained via solving pair of Quadratic Programming Problems(QPPs). However the discussed formulation was not on the lines of TWSVM and had some restrictions. In this paper we propose formulation termed as Twin Support Vector Machine based Regression(TWSVR)...
This work proposes techniques for demosaicing multi-spectral images obtained from a single sensor architecture. This is a new problem. Compressed Sensing (CS) based formulations can recover images by exploiting the sparsity of the images in the wavelet domain. In this work, we improve upon existing techniques by accounting for the hierarchical (tree-structured) correlation that exists among the wavelet...
The performance of any machine based recognition system heavily depends on the types of features used. More accurate the features extracted are, better is the chance of getting enhance performance in the recognition system. With this aim in mind a feature extraction method is proposed for numerals of Indian languages. It has been observed that structural feature are having an edge over the statistical...
In this paper, we introduce a new scalable platform for knowledge sharing based group learning in an adaptive boosting(AdaBoost) environment for supervised learning Though knowledge sharing has been an active area of research in semi supervised learning, the concept has not been explored thoroughly in supervised learning framework. In our proposed algorithm, several learner members are trained simultaneously...
We welcome all the participants and speakers of the Eighth International Conference on Advances in Pattern Recognition (ICAPR 2015) to the campus of India Statistical Institute in Kolkata. Electronics and Communication Sciences Unit (ECSU) of the Institute is organizing the current edition of the well-known ICAPR during the period 5th to 7th January 2015 after a long gap of five years. A pre-conference...
It is indeed a great honor for me to serve as a Chair of the Program Committee of The Eighth International Conference on Advances in Pattern Recognition (ICAPR 2015) being held at Indian Statistical Institute (ISI), Kolkata, India during January 4–7, 2015. This conference is organized as a part of the series started in 1981. ICAPR 2015 is technically co-sponsored by IEEE Computational Intelligence...
Respiration rate (RR) is one of the important vital signs used for clinical monitoring of neonates in intensive care units. Due to the fragile skin of the neonates, it is preferable to have monitoring systems with minimal contact with the neonate. Recently, several methods have been proposed for contact-free monitoring of vital signs using a video camera. Detection of the chest-and-abdomen region...
Facial expression recognition has many potential applications which has attracted the attention of researchers in the last decade. Feature extraction is one important step in expression analysis which contributes toward fast and accurate expression recognition. This paper represents an approach of combining the shape and appearance features to form a hybrid feature vector. We have extracted Pyramid...
Image registration is a method that resolves the discrepancy between spatial alignments of two or more images having an identical view, taken at different times, from different viewpoints and by different image sensors. It is extensively used in many image processing tasks such as medical imaging, remote sensing, military applications and so on. In this work, we propose a new automated image registration...
Feature selection is an essential technique used in high dimensional data. Basically, feature selection is focused on removing irrelevant features. But, removing redundant features is also equally important. We propose a novel feature subset selection algorithm based on the idea of consensus clustering. Our algorithm constructs a complete graph on feature space and partitions the graph using various...
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