Browsing University of Waterloo by Subject "artificial intelligence"
Now showing items 21-40 of 53
-
Fundamental Limitations of Semi-Supervised Learning
(University of Waterloo, 2009-05-05)The emergence of a new paradigm in machine learning known as semi-supervised learning (SSL) has seen benefits to many applications where labeled data is expensive to obtain. However, unlike supervised learning (SL), which ... -
GRS: Combining Generation and Revision in Unsupervised Sentence Simplification
(University of Waterloo, 2022-08-30)Text simplification is a task in the natural language processing field that alters a given text to reduce the structural and lexical complexity of the text while preserving the underlying meaning. We can classify existing ... -
Highly Efficient Deep Intelligence via Multi-Parent Evolutionary Synthesis of Deep Neural Networks
(University of Waterloo, 2020-02-11)Machine learning methods, and particularly deep neural networks, are a rapidly growing field and are currently being employed in domains such as science, business, and government. However, the significant success of neural ... -
Human-AI Interaction in the Presence of Ambiguity: From Deliberation-based Labeling to Ambiguity-aware AI
(University of Waterloo, 2020-09-11)Ambiguity, the quality of being open to more than one interpretation, permeates our lives. It comes in different forms including linguistic and visual ambiguity, arises for various reasons and gives rise to disagreements ... -
The Impact of Teams in Multiagent Systems
(University of Waterloo, 2023-07-31)Across many domains, the ability to work in teams can magnify a group's abilities beyond the capabilities of any individual. While the science of teamwork is typically studied in organizational psychology (OP) and areas ... -
Intelligent Robotic Recycling of Flat Panel Displays
(University of Waterloo, 2019-05-29)As the population and prosperity continue to rise the demand for high-tech products is rapidly increasing. Displays are a huge part of this market with millions being created each year. We have a finite amount of resources ... -
An Intelligent System for Induction Motor Health Condition Monitoring
(University of Waterloo, 2015-04-08)Induction motors (IMs) are commonly used in both industrial applications and household appliances. An IM online condition monitoring system is very useful to identify the IM fault at its initial stage, in order to prevent ... -
Learning From Almost No Data
(University of Waterloo, 2021-06-15)The tremendous recent growth in the fields of artificial intelligence and machine learning has largely been tied to the availability of big data and massive amounts of compute. The increasingly popular approach of training ... -
Learning-Free Methods for Goal Conditioned Reinforcement Learning from Images
(University of Waterloo, 2021-04-27)We are interested in training goal-conditioned reinforcement learning agents to reach arbitrary goals specified as images. In order to make our agent fully general, we provide the agent with only images of the environment ... -
Leveraging Atmospheric-Pressure Spatial Atomic Layer Deposition and Machine Learning for Nanomaterial and Device Design
(University of Waterloo, 2023-07-27)The deposition and design of nanometre-scale oxide films is an integral component of the ongoing nanomaterial revolution, from cell phones, to batteries, to photovoltaics. Atmospheric-pressure spatial atomic layer deposition ... -
Machine Learning in the Nuclear Medicine: Part 1-Introduction
(Society of Nuclear Medicine and Molecular Imaging, 2019-04)This article, the first in a 2-part series, provides an introduction to machine learning (ML) in a nuclear medicine context. This part addresses the history of ML and describes common algorithms, with illustrations of when ... -
Mitigating Fiber Nonlinearity with Machine Learning
(University of Waterloo, 2021-12-20)Nowadays, optical communication transmission is based mainly on optical fiber networks. Increasing demands for higher-capacity systems are hampered by signal distortions due to nonlinear effects of the commercial optic ... -
A Mixed Signal 65nm CMOS Implementation of a Spiking Neural Network
(University of Waterloo, 2022-08-26)Spiking neural networks (SNNs) are an emerging class of biologically inspired Artificial Neural Networks implemented in machine learning and artificial intelligence. Current state-of-the-art small- and large-scale SNNs ... -
Model-Based Bayesian Sparse Sampling for Data Efficient Control
(University of Waterloo, 2019-06-24)In this work, we propose a novel Bayesian-inspired model-based policy search algorithm for data efficient control. In contrast to other model-based approaches, our algorithm makes use of approximate Gaussian processes in ... -
Modeling Trust in Multiagent Mobile Vehicular Ad-Hoc Networks through Enhanced Knowledge Exchange for Effective Travel Decision Making
(University of Waterloo, 2012-04-24)This thesis explores how to effectively model trust in the environment of mobile vehicular ad-hoc networks. We consider each vehicle’s travel path planning to be guided by an intelligent agent that receives traffic reports ... -
Modern Object and Visual Relationship Detection in Images from a Critical, Cognitive and Data Perspective
(University of Waterloo, 2023-04-27)Deep learning has dominated the landscape of computer vision for the past decade. Deep learning networks are the top performers on a slew of computer vision challenges (e.g., object detection or image segmentation) and on ... -
Non-Invasive Blood Glucose Monitoring Using Electromagnetic Sensors
(University of Waterloo, 2022-05-16)Monitoring glycemia levels in people with diabetes has developed rapidly over the last decade. A broad range of easy-to-use systems of reliable accuracies are now deployed in the market following the introduction of the ... -
Novel Directions for Multiagent Trust Modeling in Online Social Networks
(University of Waterloo, 2020-05-13)This thesis presents two works with the shared goal of improving the capacity of multiagent trust modeling to be applied to social networks. The first demonstrates how analyzing the responses to content on a discussion ... -
On the Design of 2D Human Pose Estimation Networks using Accelerated Neuroevolution and Novel Keypoint Representations
(University of Waterloo, 2022-05-02)Motion capture is a very useful technology that is employed across many industries. Biomechanical analysis, film production, video game development, and virtual reality are among its diverse applications. However, traditional ... -
Popular Content Distribution in Public Transportation Using Artificial Intelligence Techniques
(University of Waterloo, 2019-08-20)Outdoor wireless networks suffer nowadays from an increasing data traffic demand which comes at the time where almost no vacant frequency spectrum has been left. A vast majority of this demand comes from popular content ...