This paper aims at effectively detecting the building changes in bi-temporal very high resolution satellite images. Many applications require detecting structural changes in a scene over a period of time. Change detection of man-made objects using remote sensing images has many applications such as city planning, informal building detection and disaster management. For this paper, two bi-tempor...

For a long decade clustering faced a problem of noise and outliers. Support Vector Clustering is one of the techniques in pattern recognition. Support Vector Clustering is Kernel-Based Clustering. Division of patterns, data items, and feature vectors into groups (clusters) is a complicated task since clustering does not assume any prior knowledge, which are the clusters to be searched for. Nois...

We propose a new document vector representation specifically designed for the document clustering task. Instead of the traditional termbased vectors, a document is represented as an -dimensional vector, where is the number of documents in the cluster. The value at each dimension of the vector is closely related to the generation probability based on the language model of the corresponding docum...

Local adaptation between sympatric host and parasite populations driven by vector genetics appears to be a factor that influences dynamics of disease epidemics and evolution of insect-vectored viruses. Although T. tabaci is the primary vector of Tomato spotted wilt virus (TSWV) in some areas of the world, it is not an important vector of this economically important plant virus in many areas whe...

In this paper, we have proposed a novel alignment-free method for comparing the similarity of protein sequences. We first encode a protein sequence into a 440 dimensional feature vector consisting of a 400 dimensional Pseudo-Markov transition probability vector among the 20 amino acids, a 20 dimensional content ratio vector, and a 20 dimensional position ratio vector of the amino acids in the s...

High-level speaker-specific features (HLSSFs), such as the style of pronunciation of words, their use, phonotactics and prosody, form the main subjects of state-of-the-art research on automatic speaker recognition (ASR). In this paper, we experimentally verify HLSSF extraction and support vector machine (SVM)-based modelling techniques. The HLSSF extraction produces patterns of symbols for each...

Tensor representation is helpful to reduce the small sample size problem in discriminative subspace selection. As pointed by this paper, this is mainly because the structure information of objects in computer vision research is a reasonable constraint to reduce the number of unknown parameters used to represent a learning model. Therefore, we apply this information to the vector-based learning ...

1. Introduction: In the research area of one dimensional stochastic processes, Markov chains acquire special importance due to large number of applications. One of the simplest possible continuous time Markov chains, namely birth-and-death process arises naturally in many queueing models. Such a Markov chain has an efficient recursive solution for the equilibrium probabilities. Specifically the...