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  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
181

Efficient co-location pattern discovery /

Xiao, Xiangye. January 2009 (has links)
Includes bibliographical references (p. 114-126).
182

Fuzzy Clustering Analysis

Karim, Ehsanul, Madani, Sri Phani Venkata Siva Krishna, Yun, Feng January 2010 (has links)
The Objective of this thesis is to talk about the usage of Fuzzy Logic in pattern recognition. There are different fuzzy approaches to recognize the pattern and the structure in data. The fuzzy approach that we choose to process the data is completely depends on the type of data. Pattern reorganization as we know involves various mathematical transforms so as to render the pattern or structure with the desired properties such as the identification of a probabilistic model which provides the explaination of the process generating the data clarity seen and so on and so forth. With this basic school of thought we plunge into the world of Fuzzy Logic for the process of pattern recognition. Fuzzy Logic like any other mathematical field has its own set of principles, types, representations, usage so on and so forth. Hence our job primarily would focus to venture the ways in which Fuzzy Logic is applied to pattern recognition and knowledge of the results. That is what will be said in topics to follow. Pattern recognition is the collection of all approaches that understand, represent and process the data as segments and features by using fuzzy sets. The representation and processing depend on the selected fuzzy technique and on the problem to be solved. In the broadest sense, pattern recognition is any form of information processing for which both the input and output are different kind of data, medical records, aerial photos, market trends, library catalogs, galactic positions, fingerprints, psychological profiles, cash flows, chemical constituents, demographic features, stock options, military decisions.. Most pattern recognition techniques involve treating the data as a variable and applying standard processing techniques to it.
183

Occupying spaces of belonging : indigeneity in diasporic Guyana

Cordis, Shanya Dennen 10 December 2013 (has links)
This report focuses on the intersections between diaspora and indigeneity in the nation-state of Guyana. To illustrate this conflicting, yet overlapping relationship, I examine the nature of state indigenous governing policies by tracing the colonial genealogy of the current 2006 Amerindian Act. I draw on the analytics of settler-colonialism, specifically the “logic of elimination,” to analyze dominant representations of indigeneity in the legislation, which grants recognition of collective rights and ancestral lands while constructing a narrative of national unity and belonging. Ultimately, this report seeks to sheds new light on an indigenous identification as a rights-bearing subject and ultimately rethinks indigenous/non-indigenous social and political relations. / text
184

Task-dependent target-distractor discriminability effect on repetitionblindness

Chan, Wing-lui., 陳穎蕾. January 2011 (has links)
published_or_final_version / Psychology / Master / Master of Philosophy
185

Artificial training samples for the improvement of pattern recognitionsystems

Ni, Zhibo., 倪志博. January 2012 (has links)
Pattern recognition is the assignment of some sort of label to a given input value or instance, according to some specific learning algorithm. The recognition performance is directly linked with the quality and size of the training data. However, in many real pattern recognition implementations, it is difficult or not so convenient to collect as many samples as possible for training up the classifier, such as face recognition or Chinese character recognition. In view of the shortage of training samples, the main object of our research is to investigate the generation and use of artificial samples for improving the recognition performance. Besides enhancing the learning, artificial samples are also used in a novel way such that a conventional Chinese character recognizer can read half or combined Chinese character segments. It greatly simplifies the segmentation procedure as well as reduces the error introduced by segmentation. Two novel generation models have been developed to evaluate the effectiveness of supplementing artificial samples in the training. One model generates artificial faces with various facial expressions or lighting conditions by morphing and warping two given sample faces. We tested our face generation model in three popular 2D face databases, which contain both gray scale and color images. Experiments show the generated faces look quite natural and they improve the recognition rates by a large margin. The other model uses stroke and radical information to build new Chinese characters. Artificial Chinese characters are produced by Bezier curves passing through some specified points. This model is more flexible in generating artificial handwritten characters than merely distorting the genuine real samples, with both stroke level and radical level variations. Another feature of this character generation model is that it does not require any real handwritten character sample at hand. In other words, we can train the conventional character classifier and perform character recognition tasks without collecting handwritten samples. Experiment results have validated its possibility and the recognition rate is still acceptable. Besides tackling the small sample size problem in face recognition and isolated character recognition, we improve the performance of bank check legal amount recognizer by proposing character segments recognition and applying Hidden Markov Model (HMM). It is hoped that this thesis can provide some insights for future researches in artificial sample generation, face morphing, Chinese character segmentation and text recognition or some other related issues. / published_or_final_version / Electrical and Electronic Engineering / Doctoral / Doctor of Philosophy
186

Investigating consistency and orthographic neighbourhood density effects in Chinese character processing

Wong, Leung-wai, 王良慧 January 2012 (has links)
With about 90% of all characters in a Chinese dictionary belonging to the semantic-phonetic compound category, Chinese orthography is really more phonetic than logographic. Previous studies have shown that regularity and consistency in the phonetic radical facilitate lexical access of phonetic compound characters. These findings are in line with the literature on lexical access of alphabetic languages, suggesting that phonology plays a common role in the process of visual word recognition across orthographies. The contradictory orthographic neighbourhood density effects found in Chinese and English studies, however, challenge the universal applicability of current models of lexical access. This paper reports an empirical study which investigates regularity, consistency and orthographic neighbourhood density effects on the reading and naming of traditional Chinese phonetic compound characters based on Cantonese phonology. Results showed that by manipulating regularity and consistency at the body rime level, a facilitatory orthographic neighbourhood density effect could be found in lexical decision but not naming. The implication is that regularity and consistency at the level of rime (in addition to the syllable level) is functional in Chinese reading. It also suggests that the body rime might have a general role in lexical access across languages. These findings are interpreted within the connectionist and dual-route models of lexical access. / published_or_final_version / Linguistics / Master / Master of Philosophy
187

Computer extraction of human faces

Low, Boon Kee January 1999 (has links)
Due to the recent advances in visual communication and face recognition technologies, automatic face detection has attracted a great deal of research interest. Being a diverse problem, the development of face detection research has comprised contributions from researchers in various fields of sciences. This thesis examines the fundamentals of various face detection techniques implemented since the early 70's. Two groups of techniques are identified based on their approach in applying face knowledge as a priori: feature-based and image-based. One of the problems faced by the current feature-based techniques, is the lack of costeffective segmentation algorithms that are able to deal with issues such as background and illumination variations. As a result a novel facial feature segmentation algorithm is proposed in this thesis. The algorithm aims to combine spatial and temporal information using low cost techniques. In order to achieve this, an existing motion detection technique is analysed and implemented with a novel spatial filter, which itself is proved robust for segmentation of features in varying illumination conditions. Through spatio-temporal information fusion, the algorithm effectively addresses the background and illumination problems among several head and shoulder sequences. Comparisons of the algorithm with existing motion and spatial techniques establishes the efficacy of the combined approach.
188

Optical signaling strategies for use in a multi-component sensor array

McCleskey, Shawn Catherine, 1976- 11 July 2011 (has links)
Not available / text
189

Intelligent lexical access based on Chinese/English text queries

Lam, Yat-kin., 林日堅. January 2005 (has links)
published_or_final_version / abstract / toc / Computer Science / Master / Master of Philosophy
190

Assimilation in form memory after verbal label association training

Sears, Melody Kay January 1980 (has links)
No description available.

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