Browsing Engineering (Faculty of) by Subject "Machine Learning"
Now showing items 1-20 of 34
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3D Ground Truth Generation Using Pre-Trained Deep Neural Networks
(University of Waterloo, 2019-05-24)Training 3D object detectors on publicly available data has been limited to small datasets due to the large amount of effort required to generate annotations. The difficulty of labeling in 3D using 2.5D sensors, such as ... -
Adaptive Learning Algorithms for Non-stationary Data
(University of Waterloo, 2015-04-22)With the wide availability of large amounts of data and acute need for extracting useful information from such data, intelligent data analysis has attracted great attention and contributed to solving many practical tasks, ... -
Anti-Patterns for Automatic Program Repairs
(University of Waterloo, 2016-09-23)Automated program repair has been a heated topic in software engineering. In recent years, we have witnessed many successful applications such as Genprog, SPR, RSRepair, etc. Given a bug and its test suite, which includes ... -
An Application of Secure Data Aggregation for Privacy-Preserving Machine Learning on Mobile Devices
(University of Waterloo, 2018-09-21)Machine learning algorithms over big data have been widely used to make low-priced services better over the years, but they come with privacy as a major public concern. The European Union has made the General Data Protection ... -
Automated Resolution Selection for Image Segmentation
(University of Waterloo, 2014-02-25)It is well known in image processing in general, and hence in image segmentation in particular, that computational cost increases rapidly with the number and dimensions of the images to be processed. Several fields, such ... -
Automatic Recognition and Generation of Affective Movements
(University of Waterloo, 2014-12-17)Body movements are an important non-verbal communication medium through which affective states of the demonstrator can be discerned. For machines, the capability to recognize affective expressions of their users and generate ... -
Automating and Optimizing a Transportation Mode Classification Model for use on Smartphone Data
(University of Waterloo, 2015-04-01)As transportation engineering and planning evolve from “data poor” to “data rich” practices, methods to automate the collection and translation of data to information become increasingly important. Advances in wireless ... -
Channel-based Physical Layer Authentication
(University of Waterloo, 2014-08-01)The characteristics of the wireless physical layer can be exploited to complement and enhance traditional security. In this thesis, we study the channel-based physical layer authentication. The authentication problem is ... -
A Class of Augmented Convolutional Networks Architectures for Efficient Visual Anomaly Detection
(University of Waterloo, 2021-07-23)Visual anomaly detection, the task of isolating visual data that do not conform to the defined notion of normality, is very crucial for the autonomous functioning of entities with exceptional potential in a spectrum of ... -
Cooperative Based Software Clustering on Dependency Graphs
(University of Waterloo, 2014-06-20)The organization of software systems into subsystems is usually based on the constructs of packages or modules and has a major impact on the maintainability of the software. However, during software evolution, the ... -
Data Balancing and Hyper-parameter Optimization for Machine Learning Algorithms for Secure IoT Networks
(University of Waterloo, 2022-12-19)Nowadays, many industries rely on Machine Learning (ML) algorithms and their ability to learn from existing data to make inferences about new unlabeled data. Applying ML algorithms to the network security domain is not ... -
Dataset Creation and Imbalance Mitigation in Big Data: Enhancing Machine Learning Models for Forest Fire Prediction
(University of Waterloo, 2023-10-19)Historically, forest fire prediction methods have leaned on heuristics, local insights, and basic statistical models, often neglecting the complex interplay of variables such as temperature, humidity, wind speed, and ... -
Deep Learning and Spatial Statistics for Determining Road Surface Condition
(University of Waterloo, 2019-08-28)Machine Learning (ML), and especially Deep Learning (DL) methods, have evolved rapidly over the last years and showed remarkable advances in research areas such as computer vision and natural language processing; however, ... -
Deep Multi Agent Reinforcement Learning for Autonomous Driving
(University of Waterloo, 2020-04-29)Deep Learning and back-propagation have been successfully used to perform centralized training with communication protocols among multiple agents in a cooperative Multi-Agent Deep Reinforcement Learning (MARL) environment. In ... -
Detecting Freezing of Gait Using Wearable Sensors and Machine Learning: Exploring Ternary Freezing of Gait Classification
(University of Waterloo, 2023-09-20)This work focuses on Parkinson's disease (PD), a neurodegenerative disease characterized by the production of Lewy bodies in the brain, resulting in the degeneration of dopaminergic nigrostriatal neurons. A common and ... -
Discretize and Conquer: Scalable Agglomerative Clustering in Hamming Space
(University of Waterloo, 2019-01-11)Clustering is one of the most fundamental tasks in many machine learning and information retrieval applications. Roughly speaking, the goal is to partition data instances such that similar instances end up in the same group ... -
Fast Intra-frame Coding Algorithm for HEVC Based on TCM and Machine Learning
(University of Waterloo, 2016-09-27)High Efficiency Video Coding (HEVC) is the latest video coding standard. Compared with the previous standard H.264/AVC, it can reduce the bit-rate by around 50% while maintaining the same perceptual quality. This performance ... -
Fault Driven Supervised Tie Breaking for Test Case Prioritization
(University of Waterloo, 2018-10-26)Regression test suites are an excellent tool to validate the existing functionality of an application during the development process. However, they can be large and time consuming to execute, thus making them inefficient ... -
Forest Fire Prediction Using Heterogeneous Data Sources and Machine Learning Methods
(University of Waterloo, 2023-08-18)Forest fires pose a significant and urgent threat to ecosystems and human lives, necessitating accurate prediction for effective mitigation strategies. Predicting forest fires has been a longstanding challenge due to the ... -
Greedy Representative Selection for Unsupervised Data Analysis
(University of Waterloo, 2013-01-25)In recent years, the advance of information and communication technologies has allowed the storage and transfer of massive amounts of data. The availability of this overwhelming amount of data stimulates a growing need to ...