Browsing Systems Design Engineering by Subject "machine learning"
Now showing items 21-35 of 35
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Multivariate Time Series Data Causal Discovery
(University of Waterloo, 2021-10-05)One of the goals for Artificial Intelligence is to achieve human-like intelligence. To that end, several solutions were proposed over the decades, where causal structure discovery was proposed as a viable tool for enabling ... -
Observe, Predict, Adapt: A Neural model of Adaptive Motor Control
(University of Waterloo, 2024-01-24)Biological control systems have evolved to perform efficiently in an environment characterized by high uncertainty and unexpected disturbances, while relying on noisy sensors and unreliable actuators. Despite these ... -
Operational Sea-Ice Classification of Dual Polarized SAR Imagery
(University of Waterloo, 2023-11-28)Mapping sea ice in polar regions is crucial for research and operational applications, such as environmental modeling and ship navigation. Synthetic aperture radar (SAR) offers a dependable and efficient means of monitoring ... -
Pattern Discovery and Disentanglement for Clinical Data Analysis
(University of Waterloo, 2020-09-10)In recent years, machine learning approaches have important empirical successes on analysing data such as images, signals, texts and speeches with applications in biomedical and clinical areas. However, from the perspective ... -
Player tracking and identification in broadcast ice hockey video
(University of Waterloo, 2022-07-19)Tracking and identifying players is a fundamental step in computer vision-based ice hockey analytics. The data generated by tracking is used in many other downstream tasks, such as game event detection and game strategy ... -
Predicting Sea Ice Concentration with Calibrated Uncertainty Quantification using Passive Microwave and Reanalysis Data
(University of Waterloo, 2022-08-31)The adoption of deep learning (DL) techniques in the domain of remote sensing, and specifically sea ice concentration (SIC) prediction, using passive microwave (PM) data and atmospheric climate data has seen a growing ... -
Recognizing Magnification Levels in Microscopic Snapshots using Machine Learning
(University of Waterloo, 2020-09-25)State-of-of-the-art computer vision research has facilitated technology evolution in the field of medical imaging. The primary achievement of the imaging algorithms developed is the extraction of expressive features from ... -
Reinforcement Learning for Parameter Control of Image-Based Applications
(University of Waterloo, 2004)The significant amount of data contained in digital images present barriers to methods of learning from the information they hold. Noise and the subjectivity of image evaluation further complicate such automated processes. ... -
Set Representation Learning: A Framework for Learning Gigapixel Images
(University of Waterloo, 2021-09-13)In Machine Learning, we often encounter data as a set of instances such Point Clouds (set of x,y, and z coordinates), patches from gigapixel images (Digital Pathology, Satellite Imagery, Astronomical Images, etc.), Weakly ... -
Spatial Modeling of Compact Polarimetric Synthetic Aperture Radar Imagery
(University of Waterloo, 2023-08-14)The RADARSAT Constellation Mission (RCM) utilizes compact polarimetric (CP) mode to provide data with varying resolutions, supporting a wide range of applications including oil spill detection, sea ice mapping, and land ... -
Studying CNN representations through activation dimensionality reduction and visualization
(University of Waterloo, 2021-10-01)The field of explainable artificial intelligence (XAI) aims to explain the decisions of DNNs. Complete DNN explanations accurately reflect the inner workings of the DNN while interpretable explanations are easy for humans ... -
Synthetic Correlated Diffusion Imaging for Prostate Cancer Detection and Risk Assessment
(University of Waterloo, 2023-08-31)Prostate cancer (PCa) is the second most common form of cancer among men worldwide and the most frequently diagnosed cancer among men in 112 countries. While the overall 5-year survival rate for prostate cancer is very ... -
Task-Parameterized Transformer for Learning Gripper Trajectory from Demonstrations
(University of Waterloo, 2024-02-26)The goal of learning from demonstration or imitation learning is to teach the model to generalize across unseen tasks based on available demonstrations. This ability can be important for the stable performance of a robot ... -
Transparent Decision Support Using Statistical Evidence
(University of Waterloo, 2005)An automatically trained, statistically based, fuzzy inference system that functions as a classifier is produced. The hybrid system is designed specifically to be used as a decision support system. This hybrid system ... -
Using Natural Language Processing to Detect Breast Cancer Recurrence in Clinical Notes: A Hierarchical Machine Learning Approach
(University of Waterloo, 2021-04-26)The vast amount of data amassed in the electronic health records (EHRs) creates needs and opportunities for automated extraction of information from EHRs using machine learning techniques. Natural language processing (NLP) ...