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Full-Text Articles in Physical Sciences and Mathematics
Morphological Network: Network With Morphological Neurons., Ranjan Mondal Dr.
Morphological Network: Network With Morphological Neurons., Ranjan Mondal Dr.
Doctoral Theses
Image processing with traditional approaches mainly use the tools of linear systems. However, linear approaches are not well suited and may even fail to solve problems involving geometrical aspects of the image. Thus, nonlinear geometric approaches like morphological operations are very popular in those cases. Morphological operations are nonlinear operations based on a set and lattice-theoretic methodology for image analysis that are capable of describing the geometrical structure of image objects quantitatively. It is suitable for various problems in image processing, computer vision, and pattern recognition. While solving problems with morphology, a particular structuring element is defined. Structuring elements have …
Many-Objective Evolutionary Algorithms: Objective Reduction, Decomposition And Multi-Modality., Monalisa Pal Dr.
Many-Objective Evolutionary Algorithms: Objective Reduction, Decomposition And Multi-Modality., Monalisa Pal Dr.
Doctoral Theses
Evolutionary Algorithms (EAs) for Many-Objective Optimization (MaOO) problems are challenging in nature due to the requirement of large population size, difficulty in maintaining the selection pressure towards global optima and inability of accurate visualization of high-dimensional Pareto-optimal Set (in decision space) and Pareto-Front (in objective space). The quality of the estimated set of Pareto-optimal solutions, resulting from the EAs for MaOO problems, is assessed in terms of proximity to the true surface (convergence) and uniformity and coverage of the estimated set over the true surface (diversity). With more number of objectives, the challenges become more profound. Thus, better strategies have …
Dealing With Classification Irregularities In Real-World Scenarios., Payel Sadhukhan Dr.
Dealing With Classification Irregularities In Real-World Scenarios., Payel Sadhukhan Dr.
Doctoral Theses
Data processing by the human sensory system comes naturally. This processing, commonly denoted as pattern recognition and analysis are carried out spontaneously by humans. In day to day life, in most cases, decision making by humans come without any conscious effort. From the middle of the past century, humans have shown interest to render their abstraction capabilities (pattern recognition and analysis) to the machine. The abstraction capability of the machine is ’machine intelligence’ or ’machine learning’ [87].The primary goal of machine learning methods is to extract some meaningful information from the ’data’. Data refers to the information or attributes that …
Studies On Diagnostic Coverage And X-Sensitivity In Logic Circuits., Manjari Pradhan Dr.
Studies On Diagnostic Coverage And X-Sensitivity In Logic Circuits., Manjari Pradhan Dr.
Doctoral Theses
Today’s integrated circuits comprise billions of interconnected transistors assembled on a tiny silicon chip, and testing them to ensure functional and timing correctness continues to be a major challenge to designers and test engineers with further downscaling of transistors. Although substantial progress has been witnessed during the last five decades in the area of algorithmic test generation and fault diagnosis, applications of combinatorial and machinelearning (ML) techniques to solve these problems remain largely unexplored till date. In this thesis, we study three problems in the context of digital logic test and diagnosis. The first problem is that of fault diagnosis …
On Supervised And Unsupervised Methodologies For Mining Of Text Data., Tanmay Basu Dr.
On Supervised And Unsupervised Methodologies For Mining Of Text Data., Tanmay Basu Dr.
Doctoral Theses
The supervised and unsupervised methodologies of text mining using the plain text data of English language have been discussed. Some new supervised and unsupervised methodologies have been developed for effective mining of the text data after successfully overcoming some limitations of the existing techniques.The problems of unsupervised techniques of text mining, i.e., document clustering methods are addressed. A new similarity measure between documents has been designed to improve the accuracy of measuring the content similarity between documents. Further, a hierarchical document clustering technique is designed using this similarity measure. The main significance of the clustering algorithm is that the number …
Single And Multiobjective Approaches To Clustering With Point Symmetry., Sriparna Saha Dr.
Single And Multiobjective Approaches To Clustering With Point Symmetry., Sriparna Saha Dr.
Doctoral Theses
In our every day life, we make decisions consciously or unconsciously. This decision can be very simple such as selecting the color of dress or deciding the menu for lunch, or may be as difficult as those involved in designing a missile or in selecting a career. The former decision is easy to take, while the latter one might take several years due to the level of complexity involved in it. The main goal of most kinds of decision-making is to optimize one or more criteria in order to achieve the desired result. In other words, problems related to optimization …
Empirical Determination And Forecastability Of Foreign Exchange Rate Of India., Rituparna Kar Dr.
Empirical Determination And Forecastability Of Foreign Exchange Rate Of India., Rituparna Kar Dr.
Doctoral Theses
The first chapter of this thesis begins with a brief review of the existing literature on foreign exchange rate models and their forecasting performance. Thereafter it presents the motivation as well as the main aspects of this study. The format of this chapter is as follows. A brief review of the relevant literature is presented in the first section. This review includes the important theoretical / structural as well as time series models of exchange rate. The motivation of the thesis is discussed in Section 1.2. Section 1.3 presents a brief account of the Indian economic reforms since 1993 with …
Certain Pattern Recognition Tasks Using Genetic Programming., Durga Muni Dr.
Certain Pattern Recognition Tasks Using Genetic Programming., Durga Muni Dr.
Doctoral Theses
No abstract provided.
Morphological Tower: A Tool For Multi-Scale Image Processing., Susanta Mukhopadhyay Dr.
Morphological Tower: A Tool For Multi-Scale Image Processing., Susanta Mukhopadhyay Dr.
Doctoral Theses
An image is a recorded replication of natural scene or objects using suitable sensor and recording media. The visual quality of the recorded image may be enhanced using various types of low-level processing namely noise smoothing, contrast enhancement. The images of the same scene recorded by several sensors reveal more inforination but in their own respective ways. This advantage of multi-sensor imaging system is real- ized through the fusion of the multimodal images. One more important higher-level processing is segmentation where the image is decomposed into a set of meaningful regions ( e.g. objects and background). An image, in general, …
On Some Generalized Transforms For Signal Decomposition And Reconstruction., Yumnam Singh Dr.
On Some Generalized Transforms For Signal Decomposition And Reconstruction., Yumnam Singh Dr.
Doctoral Theses
In this thesis, we propose two new subband transforms entitled ISITRA and YKSK transforms and their possible applications in image compression and encryption. Both these transforms are developed based on a common model of multiplication known as Bino’s model of multiplication. ISITRA is a convolution based transforms i.e., that both forward and inverse transform of ISITRA is based on convolution as in DWT or 2-channel filter bank. However, it is much more general than the existing DWT or 2-channel filter bank scheme in the sense that it we can get different kinds of filters in addition to the filters specified …
On Textured Image Analysis Using Wavelets., Mausumi Acharyya Dr.
On Textured Image Analysis Using Wavelets., Mausumi Acharyya Dr.
Doctoral Theses
In image processing and computer vision research, we aim to derive better tools that give us different perspectives on the same image, allowing us to understand not only its content, but also its meaning and significance. Image processing can not compete with the human eye in terms of accuracy but it can outperform the latter easily on observational consistency, and ability to carry out detailed mathematical estimations. With time, image processing research has broadened from the basic pixel-based low- level operations to high-level analysis, that now includes the use of artificially intelligent techniques for image interpretation and understanding. These new …
Certain Pattern Recognition Tasks For Data Mining Problems., Pabitra Mitra Dr.
Certain Pattern Recognition Tasks For Data Mining Problems., Pabitra Mitra Dr.
Doctoral Theses
Pattern recognition (PR) is an activity that we humans normally excel in. We do it almost all the time, and without conscious effort. We receive information via our various sensory organs, which is processed instantaneously by our brain so that, almost immediately, we are able to identify the source of the information, without having made any perceptible effort. What is even more impressive is the accuracy with which we can perform recognition tasks even under non-ideal conditions, for instance, when the information that needs to be processed is vague, imprecise or even incomplete. In fact, most of our day-to-day activities …
On Some Self-Organizing Models And Their Applications., Amitava Dutta Dr.
On Some Self-Organizing Models And Their Applications., Amitava Dutta Dr.
Doctoral Theses
Abstract: Self-organizing neural network models constitute the main theme of this thesis. Some well-known self-organizing models are surveyed and their properties are discussed. The application areas on which the thesis focuses are briefly described.This thesis deals with Artificial Neural Network models, in particular, Self- organizing (unsupervisnd) models. We develop here a few self-organizing neural net- work models to solve certain problems which are well studied in the areas of Image Processing and Computationel Geometry and have wide applications in shape eztrac- tion and optimization.1.1 Artificial neural networkThe study of Biological Neural Networks originally comes under biological sciences. They deal with …
Feature Evaluation, Classification And Rule Generation Using Fuzzy Sets And Neural Networks., Rajat Kumar De Dr.
Feature Evaluation, Classification And Rule Generation Using Fuzzy Sets And Neural Networks., Rajat Kumar De Dr.
Doctoral Theses
Pattern recognition and machine learning form a major area of research and develop- ment activity that encompasses the processing of pictorial and other non-numerical information obtained from the interaction between science, technology and society. A motivation for the spurt of activity in this field is the need for people to com- municate with the computing machines in their natural mode of communication. Another important motivation is that the scientists are also concerned with the idea of designing and making intelligent machines that can carry out certain tasks that we human beings do. The most salient outcome of these is the …
Pattern Classification Using Genetic Algorithms., Sanghamitra Bandyopadhyay Dr.
Pattern Classification Using Genetic Algorithms., Sanghamitra Bandyopadhyay Dr.
Doctoral Theses
Pattern recognition and machine learning form a major area of research and develop- ment activity that encompasses the processing of pictorial and other non-numerical information obtained from the interaction between science, technology and society. A motivation for the spurt of activity in this field is the need for people to com- municate with the computing machines in their natural mode of communication. Another important motivation is that the scientists are also concerned with the idea of designing and making intelligent machines that can carry out certain tasks that we human beings do. The most salient outcome of these is the …
On The Developement Of An Optical Character Recognition(Ocr) System For Printed Bangla Script., Umapada Pal Dr.
On The Developement Of An Optical Character Recognition(Ocr) System For Printed Bangla Script., Umapada Pal Dr.
Doctoral Theses
This thesis concerns OCR development of machine printed text in an Indian lan- guage, Bangla (Bengali) which is the fourthmost popular language in the world and the secondmost popular language in India.1.1 Optical Character Recognition Optical Character Recognition (OCR) is a process of automatic computer recog- nition of characters in optically scanned and digitized pages of text. OCR is ene of the most fascinating and challenging areas of pattern recognition with various practical applications. It can contribute tremendously to the advancement of an automation process and can improve the interface between man and machine in many applications, including office automation …
Neuro Fuzzy Reasoning For Pattern Classification And Object Recognition., Jayati Ghosh Dr.
Neuro Fuzzy Reasoning For Pattern Classification And Object Recognition., Jayati Ghosh Dr.
Doctoral Theses
In real world, pattern classification and object recognition problems are faced with fuzzi- ness that is connected with diverse facets of cognitive activity of the human being. An origin of sources of fuzziness is related to labels expressed in feature space as well as to labels of classes taken into account in classification and /or recognition procedures. Though a lot of scientific efforts have already been dedicated to pattern recognition problems, especially to classification procedures, still pattern recognition is confronted with a continuous challenge coming from a human being who can perform lot of ex- tremely complex classification tasks by …
Neuro-Fuzzy Models For Classification And Rule Generation., Sushmita Mitra Dr.
Neuro-Fuzzy Models For Classification And Rule Generation., Sushmita Mitra Dr.
Doctoral Theses
Machine recognition [1, 2] of patterns can be viewed as a two-fold task, consisting of learning the invariant and common properties of a set of samples characterizing a class, and of deciding a new sample as a possible member of the class by noting that it has properties common to those of the set of samples. In other words, pattern recognition by computers can be described as a transformation from the measurenment space M to the feature space F and finally to the decision space D (1), i.e., M ⟶F⟶D.Here, the mapping 6 : F⟶D is the decision function and …
Connectionist Models For Certain Tasks Related To Object Recognition., Jayanta Basak Dr.
Connectionist Models For Certain Tasks Related To Object Recognition., Jayanta Basak Dr.
Doctoral Theses
Recognition of objects in an image, according to Suetens et al. [1), relers to the task of finding and labeling parts of a two-dimensional image of a scene that correspond to the real objects in the scene. Object recognition is necessary in a variety of domains like robot navigation, aerial imagery analysis, industrial inspection and so on. Normally, different strategies for object recognition (1-(5] involve establishing some model for each object, i.e., some general description of each object, and then labeling different parts of the scene according to the knowledge about the models.Object models can have two-dimensional (2D) or three-climensional …
On Lexical And Syntactic Processing Of Bangla Language By Computer., Probal Sengupta Dr.
On Lexical And Syntactic Processing Of Bangla Language By Computer., Probal Sengupta Dr.
Doctoral Theses
A distinctive intelligent trait of human beings is the ability to carry out meaningful communication through language. The communication may be direct as in spoken conversation or indirect as in written form, through the audio-visual media, etc. Linguistic ability in humans have fascinated scholars ever since man first learnt to use language. Linguistics, the branch of study involved in studying the nature of human linguistic communication, is perhaps as old as language itself. The invention of the computer added a new dimension to linguistics. Making the computer emu- late human linguistic behaviour was taken up as a challenge by computer …
Multivalued Approach For Uncertainty Management., Deba Prasad Mandal Dr.
Multivalued Approach For Uncertainty Management., Deba Prasad Mandal Dr.
Doctoral Theses
Real life problems are rarely free from uncertainty which usually emerges from the deficiencies of information available from a situation. The defi- ciencies may result from incomplete, imprecise, not fully reliable, vague or contradictory information depending on the problem. Management of uncer- tainty in a decision making system has been an important research problem for many years.Until the inception of the concept of fuzzy set theory in 1965 (1), the theory of probability and statistics was the primary mathematical tool for modeling uncertainty in a system/situation. Fuzzy set theory has shown enormous proinise in handling uncertaintics to a reasonable extent …
On Image Segmentation Using Neural Networks And Fuzzy Sets., Ashish Ghosh Dr.
On Image Segmentation Using Neural Networks And Fuzzy Sets., Ashish Ghosh Dr.
Doctoral Theses
During the last five decades or even more a large number of researchers are trying to design intelligent systems to perform tasks at which human beings are more efficient at present. One of the most important behavioral tasks in which human beings show their expertise is image analysis or recognition; where a large amount of pictorial data is processed in a very small amount of time (called real time). Widespread attempts have been made to develop intelligent systems (under different names, like pattern recognition system, image under- standing system, computer vision system etc.) for pictorial pattern analysis and recognition. The …
On A Class Of Stochastic Approximation -Type Parameter-Learning Algorithms For Pattern Recognition., Amita Pal Dr.
On A Class Of Stochastic Approximation -Type Parameter-Learning Algorithms For Pattern Recognition., Amita Pal Dr.
Doctoral Theses
The first tank can involve one or more subtasks. For instance, it may require the design of a classifier on the basis of whatever prior knowledge there is of the feature space, or given the design, to estimate efficiently the parameters of the classifier. The latter might involve the estimation of the density function itself if very little is known about the class-conditional fenture distribution, or it may necessitate the entimation of the parameters of the fenture distribution, if one can assume it to have some known form. It may also involve estimating the boundaries of the classes, if even …