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 13 of 13 for “"Deep features"”.
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Sketch image recognition using deep features
… directly to sketches, a model using a new deep neural network that considers more of the unique characteristics of sketches has been developed and studied. Experiment results on the challenging sketch datasets demonstrate the superior performance of this present model in comparison to …
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Investigation of KimiaNet's and DenseNet's deep features in lung cancer subtypes
Deep neural networks (DNN) have extended applications in the _eld of digital pathology. One of which is to act as feature extractors for content-based image retrieval (CBIR) systems. Therefore, it is necessary to investigate how these deep features work and attribute these features to histologic …
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A Malware Classification Method Based on the Multi-Layer Feature Fusion of Malware Image Representations and Opcode Markov Images
… on the fusion of image representation and opcode features. By integrating the features of image-based malware representation and opcode Markov image, the classification performance is enhanced. Specifically, our model introduces two feature fusion modules: a cross-attention-based fusion module and …
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Efficient and Effective Solutions for Video Classification
… (such as hand-crafted descriptor extraction) to deep learning. Therefore, this thesis captures this transition period, however, unlike image classification, where the state-of-the-art results are dominated by deep learning approaches, for video classification the deep learning approaches are not …
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Individual Carbon Nanotube Probes And Field Emitters Fabrication And T
… with nanotube tips allows us to image relatively deep features of the sample surface at near nanometer resolution. Characterization of AFM with individual CNT tips and field emission properties of single CNT emitters will be studied and presented.
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Unmasking the imposters: towards improving the generalisation of deep learning methods for face presentation attack detection.
… applications. An in-depth analysis of current deep learning methods is used in this research to examine various aspects of detecting face presentation attacks. A number of new techniques are implemented and evaluated in this study, including pre-trained models, manual feature extraction, and …
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A Unified Theory of Representation Learning: How Hidden Relationships Power Algorithms that can Learn without Labels
… theory is the notion that relationships between deep network representations hold the key discover the structure of the world without human input. This work will begin with a few examples of this principle in action; discovering hidden connections that span cultures and millennia in the visual …
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Mapping Building Damage Caused by Earthquakes Using Satellite Imagery and Deep Learning
… assessing post-event damage. The application of deep learning is encouraged by recent technological developments, enabling the processing of increasing amounts of data in a reasonable time as well as the use of more complex models. In this thesis, deep learning is explored for identifying …
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Device-Free WiFi Sensing for Human Activity Recognition
… and intelligent monitoring. Recently, applying deep learning (DL) to WiFi-based HAR has received strong research interest. Assisted by signal processing techniques, DL-based HAR methods are able to automatically extract deep features from input signals, contributing to successful recognitions. …
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Primary/Soft Biometrics: Performance Evaluation and Novel Real-Time Classifiers
… faces and then extracts 7 types of classical and deep features. These features were fused together to train 3 different classifiers. Our proposed model yielded 91.93% on the average accuracy outperforming 7 state-of-the-art models. We also developed a real-time model for classifying the states of …
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Learning to Generate and Refine Object Proposals
… stereo images. Our method makes use of learned deep features and designed geometric features to represent a region and learns a similarity network to guide the superpixel grouping process. We also learn a ranking network to predict the objectness score for each segment proposal. To address the …
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Learning to Generate and Refine Object Proposals
… stereo images. Our method makes use of learned deep features and designed geometric features to represent a region and learns a similarity network to guide the superpixel grouping process. We also learn a ranking network to predict the objectness score for each segment proposal. To address the …
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Towards a Fast and Accurate Face Recognition System from Deep Representations
… followed by classification or regression. The features representing the input data should have the following desirable properties: 1) they should contain the discriminative information required for accurate classification, 2) they should be robust and adaptive to several variations in the input …