Search Results for Visual perception.

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Learning Conditional Models for Visual Perception

Veit, Andreas, author.

http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqm&rft_dat=xri:pqdiss:10815847

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Learning Conditional Models for Visual Perception / Veit, Andreas, author.

The Effects on User Perception of Uniqueness of Three Factors as Applied to 3-Dimensional Tree Models

Gao, Ge, author.

http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqm&rft_dat=xri:pqdiss:10811239

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wild-lands scenes which demands for a large number of tree models. From the visual perception

Cover image for An Analysis of the Computational Performance of a Massively Parallel Perceptual Image Quality Assesment Algorithm Implemented on Multiple Graphics Processing Units

An Analysis of the Computational Performance of a Massively Parallel Perceptual Image Quality Assesment Algorithm Implemented on Multiple Graphics Processing Units

Holloway, Joshua Keegan, author.

http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqm&rft_dat=xri:pqdiss:10187934

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simplistic models of visual perception, however such an approach has serious drawbacks in terms of poor

Learning, Moving, and Predicting with Global Motion Representations

Jaegle, Andrew, author.

http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqm&rft_dat=xri:pqdiss:10808343

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and camera motion under projective geometry; (ii) learn representations of visual motion directly from

A Study of Interpretability Mechanisms for Deep Networks

Kokate, Apurva, author. (orcid)0000-0003-2353-4171

http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqm&rft_dat=xri:pqdiss:10793172

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-critical decisions such as perception for self-driving cars, the machine learning community has been extremely

Learning Hierarchical Speech Representations Using Deep Convolutional Neural Networks

Hau, Darren, author.

http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqm&rft_dat=xri:pqdiss:10820103

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for visual perception tasks. Key to the success of deep learning is its ability to learn hierarchical

Visual Selection in Data Visualizations

Nothelfer, Christine Estelle, author.

http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqm&rft_dat=xri:pqdiss:10817381

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defined by only one visual feature, and all despite the additional visual complexity. In Section 2, we

From Motor Control to Scene Perception: Using Machine Learning to Model Human Behavior and Cognition

Bayat, Akram, author.

http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqm&rft_dat=xri:pqdiss:10788957

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networks resemble the human visual system for scene perception and object recognition in three problems: (1

Visual Analysis of Dynamics of Urban Regions Based on Human Mobility Data

Wu, Wenchao, author.

http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqm&rft_dat=xri:pqdiss:10903410

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visual analytics, we can include human perception in the data exploration process efficiently and combine

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