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Andrew Hryniowski

DVQI: A Multi-task, Hardware-integrated Artificial Intelligence System for Automated Visual Inspection in Electronics Manufacturing

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Dec 14, 2023
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COVID-Net Biochem: An Explainability-driven Framework to Building Machine Learning Models for Predicting Survival and Kidney Injury of COVID-19 Patients from Clinical and Biochemistry Data

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Apr 24, 2022
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COVID-Net Clinical ICU: Enhanced Prediction of ICU Admission for COVID-19 Patients via Explainability and Trust Quantification

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Sep 14, 2021
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AttendSeg: A Tiny Attention Condenser Neural Network for Semantic Segmentation on the Edge

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Apr 29, 2021
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Inter-layer Information Similarity Assessment of Deep Neural Networks Via Topological Similarity and Persistence Analysis of Data Neighbour Dynamics

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Dec 07, 2020
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Insights into Fairness through Trust: Multi-scale Trust Quantification for Financial Deep Learning

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Nov 03, 2020
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Where Does Trust Break Down? A Quantitative Trust Analysis of Deep Neural Networks via Trust Matrix and Conditional Trust Densities

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Sep 30, 2020
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How Much Can We Really Trust You? Towards Simple, Interpretable Trust Quantification Metrics for Deep Neural Networks

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Sep 20, 2020
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DeepLABNet: End-to-end Learning of Deep Radial Basis Networks with Fully Learnable Basis Functions

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Nov 21, 2019
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State of Compact Architecture Search For Deep Neural Networks

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Oct 15, 2019
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