Browsing University of Waterloo by Subject "Deep learning"
Now showing items 1-11 of 11
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Computational Depth from Defocus via Active Quasi-random Pattern Projections
(University of Waterloo, 2018-08-22)Depth information is one of the most fundamental cues in interpreting the geometric relationship of objects. It enables machines and robots to perceive the world in 3D and allows them to understand the environment far ... -
Constraint-Guided Machine Learning for Solving Optimal Power Flow Problem
(University of Waterloo, 2022-08-31)Due to the nonlinear and non-convex attributes of the optimization problems in power systems such as Optimal Power Flow (OPF), traditional iterative optimization algorithms require significant amount of time to converge ... -
Deep Learning Based Place Recognition for Challenging Environments
(University of Waterloo, 2016-08-25)Visual based place recognition involves recognising familiar locations despite changes in environment or view-point of the camera(s) at the locations. There are existing methods that deal with these seasonal changes or ... -
Deep Residual Networks for Hyperspectral Image Classification
(Institute of Electrical and Electronics Engineers, 2017-07-25)Deep neural networks can learn deep feature representation for hyperspectral image (HSI) interpretation and achieve high classification accuracy in different datasets. However, counterintuitively, the classification ... -
Denoising Autoencoder for Multi-level Random Telegraph Signal Analysis
(University of Waterloo, 2023-09-21)Random Telegraph Signals (RTSs) are discrete random fluctuations between different current levels that usually appear in short-channel Metal-Oxide-Semiconductor Field Effect Transistors (MOSFETs). The statistical analysis ... -
Development of a global road safety performance function using deep neural networks
(Elsevier, 2017-08-01)This paper explores the idea of applying a machine learning approach to develop a global road safety performance function (SFP) that can be used to predict the expected crash frequencies of different highways from different ... -
Honkling: In-Browser Personalization for Ubiquitous Keyword Spotting
(University of Waterloo, 2019-12-19)Used for simple voice commands and wake-word detection, keyword spotting (KWS) is the task of detecting pre-determined keywords in a stream of utterances. A common implementation of KWS involves transmitting audio samples ... -
Hydrophobicity Classification of RTV Silicone Rubber-Coated Insulators Using Deep Learning Algorithms
(University of Waterloo, 2022-08-18)Silicone rubber-based outdoor polymeric insulators are widely employed in electric power transmission and distribution networks to replace conventional ceramic insulators, owing to their superior performance in contaminated ... -
Natural Language Processing using Deep Learning for Classifying Water Infrastructure Procurement Records and Calculating Unit Costs
(University of Waterloo, 2024-03-06)This thesis introduces a novel ontology-based deep learning classification model specifically tailored for civil engineering applications, focusing on automating the extraction and classification of water infrastructure ... -
Road Information Extraction from Mobile LiDAR Point Clouds using Deep Neural Networks
(University of Waterloo, 2020-08-17)Urban roads, as one of the essential transportation infrastructures, provide considerable motivations for rapid urban sprawl and bring notable economic and social benefits. Accurate and efficient extraction of road information ... -
Towards Learning Feasible Hierarchical Decision-Making Policies in Urban Autonomous Driving
(University of Waterloo, 2022-09-29)Modern learning-based algorithms, powered by advanced deep structured neural nets, have multifacetedly facilitated automated driving platforms, spanning from scene characterization and perception to low-level control and ...