Global ETD Search
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 551 for “"Feature extraction"”.
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Sparse Kernel feature extraction
The presence of irrelevant features in training data is a significant obstacle for many machine learning tasks, since it can decrease accuracy, make it harder to understand the learned model and increase computational and memory requirements. One approach to this problem is to extract appropriate …
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Feature extraction via heat flow analogy
Feature extraction is an important field of image processing and computer vision. Features can be classified as low-level and high-level. Low-level features do not give shape information of the objects, where the popular low-level feature extraction<br/>techniques are edge detection, corner …
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Automated feature extraction in oceanographic visualization
… but combining biological, chemical and physical features is able to help us understand the complex coupled physics, biology and acoustics of the ocean. Applications of the prediction of the ocean environment include exploitation and management of marine resources, pollution control such as …
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Feature extraction from millimetre wave radar images
… into the segmentation and classification of features on images of wound terrain generated from an airborne millimetre wave radar. The principles of operation of the radar are established and it is shown how an image is produced from this particular radar. The parameters such as wavelength, …
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Multiscale geometric feature extraction and object recognition
Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1997.
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Inspection and feature extraction of marine propellers
Thesis (M.S.)--Massachusetts Institute of Technology, Dept. of Ocean Engineering, 1997.
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Segmentation and Feature Extraction Methods for Ocular Modalities
… vascular pattern enhancement techniques, feature extraction methodologies and feature enhancement methods for CV recognition. We introduce a new sclera segmentation algorithm using morphological properties of human eye in visible spectrum. This study demonstrates the effective use of the …
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Feature extraction in image processing and deep learning
… networks, and algorithms to extract useful features of images in fields of deep learning, quantum energy regression and cancer image analysis. The separate applications are connected by using representation systems in harmonic analysis; we focus on deriving proper representations of data …
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Feature Extraction for Automatic Recognition of Telephone Speech
… system can be considered as containing a feature extractor and a word classifier. The research described in this thesis concerns a feature extraction system for transforming telephone speech into strings of symbols, suitable for use by a word classifier. The hypothesis upon which the …
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Optimization of acoustic feature extraction from dysarthric speech
… speech recognition, Stevens' Lexical Access from Features (LAFF) framework, for ten individual speakers with dysarthria (SWDs). The LAFF model is rooted in distinctive feature theory, with acoustic landmarks indicating changes in the manner of articulation. The acoustic correlates manifested …
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Compressive image feature extraction by means of folding
… we term folding for the purposes of image feature extraction. We seek to discover whether image features are preserved under this process and how to efficiently extract them. The application is in size weight and power constrained imaging scenarios where an efficient implementation of this …
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Feature Extraction Workflows for Urban Mobile-Terrestrial LiDAR Data
… (GEOBIA) for the development of automated feature extraction. A LiDAR sensor-centric perspective during the data acquisition phase is used to organize data for the user and to transform the data into a 2D reference frame for object-oriented image analysis of MTL data. Organizing the display …
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Feature extraction and knowledge discovery in process operation analysis
… study which consists of three components: (1) feature extraction from dynamic transient signals using multiscale wavelet transform; (2) operational state identification using unsupervised and recursive learning methods; and (3) automatic extraction of knowledge rules from process operational …
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Learning Efficient Deep Feature Extraction For Mobile Ocular Biometrics
… using Convolutional Neural Networks(CNN) for feature extraction and person recognition. Most of the early works proposed using large CNNs for ocular recognition in subject-dependent evaluation, where the subjects overlap between the training and testing set. This is difficult to scale for the …
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Feature Extraction and Object Recognition using Conditional Morphological Operators
… work undertaken on morphological operators for feature extraction from, and segmentation and recognition of, objects within single 2-D images under loosely controlled conditions.<br/><br/>The novel aspects of the work include the development of a conditional morphological operator, the RJ …
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Unsupervised Feature Extraction Techniques for Plasma Semiconductor Etch Processes
As feature sizes on semiconductor chips continue to shrink plasma etching is becoming a more and more critical process in achieving low cost high-volume manufacturing. Due to the highly complex physics of plasma and chemical reactions between plasma species, control of plasma etch processes is one …
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AI Approaches for Feature Extraction in Multimodal Biomedical Data
… AI approaches can fail to learn due to "feature dilution", where a model is overloaded with data points, and spurious or noisy features prevent it from successfully aligning to and converging on semantic or predictive features in the dataset. Traditional methods of feature extraction …
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