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 19 of 19 for “"Machine perception"”.
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Machine perception of three-dimensional solids
Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering, 1963.
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Machine Perception of Objects With Curved Surfaces
Made available in DSpace on 2014-12-10T19:07:19Z (GMT). No. of bitstreams: 1 7500277.pdf: 3081045 bytes, checksum: 27b8da1bf0c51a2520f06df3f2d62cca (MD5) Previous issue date: 1974
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Towards Automated Design of Machine Perception Systems
Animal's visual perception systems have evolved to their environment over billions of years, enabling them to navigate, avoid predators, and hunt prey. In contrast, machine perception systems designed by humans require significant engineering and often use standard cameras that may not be well …
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Machine perception of natural musical conducting gestures
Thesis (M.S.)--Massachusetts Institute of Technology, Program in Media Arts & Sciences, 1996.
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Empowering vision machine perception for robust telehealth applications
… vision for telehealth and deploying robust machine learning (ML) models for telehealth applications. Under the first focus, the Digitized Neurological Examination (DNE) system is introduced for comprehensive vision-based neurological examination using smartphones, validated for clinical …
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Machine perception and learning of complex social systems
The study of complex social systems has traditionally been an arduous process, involving extensive surveys, interviews, ethnographic studies, or analysis of online behavior. Today, however, it is possible to use the unprecedented amount of information generated by pervasive mobile phones to provide …
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Attention-based machine perception for intelligent cyber-physical systems
Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2022-04-06 without embargo terms
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Categorical organization and machine perception of oscillatory motion patterns
… We develop a computational model of categorical perception of these motion patterns based on their inherent structural regularity. The model proposes the initial construction of a hierarchical ordering of the model parameters to partition them into sub-categorical specializations. This …
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Electric field imaging
… new physical channel and inference framework for machine perception of human action. Though electric field sensing is an important sensory modality for several species of fish, it has not been seriously explored as a channel for machine perception. Technological applications of field sensing, from …
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Compositional simulation in perception and cognition
Despite rapid recent progress in machine perception and models of biological perception, fundamental questions remain open. In particular, the paradigm underlying these advances, pattern recognition, requires large amounts of training data and struggles to generalize to situations outside the …
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Viewpoint Optimization for Autonomous Strawberry Harvesting with Deep Reinforcement Learning
… industry. However, due to bottlenecks in machine perception and economic viability, a profitable and commercially adopted strawberry harvesting system remains elusive. In this research, we explore the feasibility of using deep reinforcement learning to overcome these bottlenecks and …
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Discriminative, generative, and imitative learning
… that combines three different paradigms in machine learning: generative, discriminative and imitative learning. A generative probabilistic distribution is a principled way to model many machine learning and machine perception problems. Therein, one provides domain specific knowledge in terms …
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On development and perception of theomorphic robots: the uncanny valley effect to Artificial Intelligence (AI)
… Pre-training (CLIP) model to simulate perception and classification processes. Specifically, the research uses the conceptual structure of the Godspeed Questionnaire, widely used in research on the Uncanny Valley effect, to investigate how an AI system categorizes a robot relative to …
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Slimmable neural networks for edge devices
… learning have witnessed major breakthroughs in machine perception and generative modeling, the problem of how to run neural networks within latency budget for edge devices remains unsolved. This thesis presents a new approach to train a single neural network executable at arbitrary widths for …
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Towards perceptual intelligence : statistical modeling of human individual and interactive behaviors
… correctly classify human behaviors, by means of Machine Perception and Machine Learning techniques. In the thesis I develop the statistical machine learning algorithms (dynamic graphical models) necessary for detecting and recognizing individual and interactive behaviors. In the case of the …
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Towards a Fast and Accurate Face Recognition System from Deep Representations
The key components of a machine perception algorithm are feature extraction 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, …
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Holistic indoor scene understanding, modelling and reconstruction from single images.
… reconstruction. It aims at automatic 3D scene perception that enables machines to understand and predict 3D contents as human vision, which we hope could advance the boundaries of 3D vision in machine perception, robotics and Artificial Intelligence.
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Attention-Based Encoder-Decoder Models for Speech Processing
Speech processing is one of the key components of machine perception. It covers a wide range of topics and plays an important role in many real-world applications. Many speech processing problems are modelled using sequence-to-sequence models. More recently, the Attention-Based Encoder-Decoder …
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Auditory-based processing of communication sounds
… model of human auditory processing as part of a machine-hearing system. Features were generated by an auditory model, and used as input to machine learning systems to determine the content of the sound. Features were generated using the auditory image model (AIM) and were used for speech …