Browsing Engineering (Faculty of) by Subject "convolutional neural networks"
Now showing items 1-8 of 8
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An Analysis Framework for the Quantization-Aware Design of Efficient, Low-Power Convolutional Neural Networks
(University of Waterloo, 2022-04-29)Deep convolutional neural network (CNN) algorithms have emerged as a powerful tool for many computer vision tasks such as image classification, object detection, and semantic segmentation. However, these algorithms are ... -
Anomaly Detection in Textured Surfaces
(University of Waterloo, 2019-12-17)Detecting anomalies in textured surfaces is an important and interesting problem that has practical applications in industrial defect detection and infrastructure asset management with a lot of potential financial benefits. ... -
Enhancing the Decoding Performance of Steady-State Visual Evoked Potentials based Brain-Computer Interface
(University of Waterloo, 2019-08-14)Non-invasive Brain-Computer Interfaces (BCIs) based on steady-state visual evoked potential (SSVEP) responses are the most widely used BCI. SSVEP are responses elicited in the visual cortex when a user gazes at an object ... -
Fair Compression of Machine Learning Vision Systems
(University of Waterloo, 2023-09-01)Model pruning is a simple and effective method for compressing neural networks. By identifying and removing the least influential parameters of a model, pruning is able to transform networks into smaller, faster networks ... -
Fusion of Estimated Depth and RGB Features for Improved Grasp-Type Selection of Novel Objects
(University of Waterloo, 2022-09-01)Prostheses can alleviate some of the challenges faced by upper limb amputees in performing activities of daily living. However, electric-powered prosthetic hands have not seen much improvement over the past decade. Unintuitive ... -
Learning-based Image Scale Estimation for Quantitative Visual Inspection of Civil Structures
(University of Waterloo, 2021-02-25)The number of assets of civil infrastructure (e.g., bridges or roads) have been increasing to meet the demands of growing populations around the world. However, they degrade over time due to environmental factors and must ... -
Machine Learning Approaches in Crystal Plasticity
(University of Waterloo, 2022-04-27)The continued advancements in material development and design require understanding the relationships between microstructure and flow behaviour. Crystal plasticity (CP) is a high-fidelity computational method that helps ... -
Sea Ice Concentration Estimation: Using Passive Microwave and SAR Data with Fully Convolutional Networks
(University of Waterloo, 2020-09-01)Sea ice concentration is of great interest to ship navigators and scientists who require regional ice cover understanding. Passive microwave data and image analysis charts are typically used to estimate ice concentration, ...