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Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 20 of 21 for “"Texture Classification"”.
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Transform texture classification
… thesis addresses the three major components of a texture classification system: texture image transform, feature extraction/selection, and classification. A unique theoretical investigation of texture analysis, drawing on an extensive survey of existing approaches, defines the interrelations among …
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Transform texture classification
Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Ocean Engineering, 1996.
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An Intelligent Soft-Computing Texture Classification System
… work was to obtain a system that classifies texture. This so called Texture Classification System is not a system for one special task or group of tasks. It is a general approach that shows a way towards real artificial vision.<br/><br/>Finding ways to enable computerised systems to visually …
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Support vector machine and parametric wavelet-based texture classification of stem cell images
… studies and therapeutic treatments. Since colony texture is a major discriminating feature in determining quality. we introduce a non-invasive, semi-automated texture-based stem cell colony classification methodology to aid researchers in colony quality control. We first consider the general …
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Target Detection Using a Wavelet-Based Fractal Scheme
… was compared with the EF feature for a general texture classification problem. The wavelet-based technique yielded a lower classification error than EF, which motivated the comparison between the two techniques presented in this paper. Experimental results show that the proposed techniques …
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SARLBP and STMO-GA : two novel description and selection approaches for challenging feature classification problems
Texture analysis and classification is a much-researched area due to its significance within computer vision and pattern recognition applications. Broadly speaking, two approaches for texture classification are found in the literature today: Classical and Deep Learning (DL) based. Typical Deep …
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Classification of Fallow and Perennial Fields in High-Resolution Multispectral Aerial Images
… of perennial acreage motivated the use of a texture-based classification approach. Two different texture classification methods are developed, namely a pixel-based image analysis texture segmentation framework (TSF) approach and a statistical vocabulary learning-based approach referred to as …
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Image Quality Analysis Using GLCM
… has proven to be a powerful basis for use in texture classification. Various textural parameters calculated from the gray level co-occurrence matrix help understand the details about the overall image content. The aim of this research is to investigate the use of the gray level co-occurrence …
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Malware Image Classification using Machine Learning with Local Binary Pattern
<p>Malware classification is a critical part in the cybersecurity.</p> <p>Traditional methodologies for the malware classification</p> <p>typically use static analysis and dynamic analysis to identify malware.</p> <p>In this paper, a malware classification methodology based</p> <p>on its binary …
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Investigation on advanced image search techniques
… in their visual contents, such as color, texture, and shape, to a query image is an active research area due to its broad applications. Color, for example, provides powerful information for image search and classification. This dissertation investigates advanced image search techniques and …
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Improving Identification of Area Targets by Integrated Analysis of Hyperspectral Data and Extracted Texture Features
… of integrating spectral data and extracted texture features on classification accuracy. Four separate spectral ranges (hundreds of spectral bands total) were used from the VNIR-SWIR portion of the electromagnetic spectrum. Haralick texture features (contrast, entropy, and correlation) were …
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Touching is believing : sensing and analyzing touch information with GelSight
… for material recognition, in terms of 3D surface texture classification. With image processing and machine learning techniques applied on the tactile images obtained, the fingertip GelSight sensor opens many possibilities for robotic manipulation that would otherwise be difficult to perform.
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Classification of soil surface texture using high-resolution RGB images captured under uncontrolled field conditions
… practices requires accurately classifying its texture. Accurate soil texture classification can optimize soil nutrient levels and improve land management. This study proposes a framework that uses images captured under Uncontrolled Field Conditions (UFC) to classify soil texture for farmlands …
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Progressively communicating rich telemetry from autonomous underwater vehicles via relays
… and a novel image compression scheme based on texture classification and synthesis. The specific characteristics of underwater communication channels, including high latency, intermittent communication, the lack of instantaneous end-to-end connectivity, and a broadcast medium, inform these …
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An approach to map soil texture class on the Iowan Erosion Surface
… dataset combination to produce surface soil texture class maps on the Iowan Erosion Surface physiographic region (MLRA 104) using standard and novel predictor variables (covariates) for modeling. Hand-textured and laboratory-analyzed legacy particle size fraction (PSF) data were obtained from …
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Progressively communicating rich telemetry from autonomous underwater vehicles via relays
… and a novel image compression scheme based on texture classification and synthesis. The specific characteristics of underwater communication channels, including high latency, intermittent communication, the lack of instantaneous end-to-end connectivity, and a broadcast medium, inform these …
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Development of computer-based algorithms for unsupervised assessment of radiotherapy contouring
… were explored. k-nearest neighbour (k-NN) classification of tumour from normal tissues based on texture features was also investigated. RESULTS: 63 cases were used for development and training. Segmentation and classification performance were evaluated on an independent test set of 16 …
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Machine learning methods for discriminating natural targets in seabed imagery
… discriminating sidescan sonar image textures characteristic of Sabellaria spinulosa colonisation. Results from a comparison of several textural feature creation methods on sonar waterfall imagery show that Gabor filter banks yield some of the best results. A further empirical …
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Methoden zur Konstruktion invarianter Merkmale für die Texturanalyse
… inhomogene Objektregionen werden gemeinhin als Texturen bezeichnet und repräsentieren eine intrinsische Eigenschaft des Objekts resp. der Objektoberfläche. Für viele Bereiche des maschinellen Sehens ist es wesentlich, Objekttexturen, die sich i.a. formal nicht beschreiben lassen, analysieren zu …
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The Detection of Vegetation Species in Remote Sensing Imaging
Remote sensing classification is a complicated process and requires the perception of many factors. The main image classification factors that can be taken into consideration to improve classification accuracy may include placement of a sufficient classification system, chosen of training samples, …
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