Mohammad Nazmul Alam Khan

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We study automatic target recognition (ATR) in infrared (IR) imagery by applying two recent computer vision techniques, Histogram of Oriented Gradients (HOG) and Bag-of-Words (BoW). We propose the idea of dense HOG features which are extracted from a set of high-overlapped local patches in a small IR chip and we apply a vocabulary tree that is learned from(More)
Domain adaptation (DA) algorithms address the problem of distribution shift between training and testing data. Recent approaches transform data into a shared subspace by minimizing the shift between their marginal distributions. We propose a method to learn a common subspace that will leverage the class conditional distributions of training samples along(More)
Data replication is a key factor to achieve scalability and fault tolerance in databases as it maintains several clones of data objects. A change made in data automatically triggers carrying out similar changes in each of the replica. A number of data replication techniques have been proposed in the contemporary literature due to its large scale application(More)
This paper presents the simulation of privacy-related applications employing blind signature (BS) schemes. Two popular privacy-related applications: 'traditional BS based electronic voting system (EVS)' and 'traditional offline electronic payment protocol (EPP)' have been chosen here. A BS scheme is a cryptographic protocol that plays a(More)
Domain adaptation (DA) algorithms utilize a labelrich old dataset (domain) to build a machine learning model (classification, detection etc.) in a label-scarce new dataset with different data distribution. Recent approaches transform crossdomain data into a shared subspace by minimizing the shift between their marginal distributions. In this paper, we(More)
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