University of Waterloo

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University of Waterloo in Waterloo, Canada, is uniquely connected to the world and committed to making it better. This is a place where innovation has impact.

COVID-Net: A Tailored Deep Convolutional Neural Network Design for Detection of COVID-19 Cases from Chest Radiography Images

The COVID-19 pandemic continues to have a devastating effect on the heal...
03/22/2020 ∙ by Linda Wang, et al. ∙ 121 ∙ share

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SAUNet: Shape Attentive U-Net for Interpretable Medical Image Segmentation

Medical image segmentation is a difficult but important task for many cl...
01/21/2020 ∙ by Jesse Sun, et al. ∙ 69 ∙ share

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Improving Dataset Distillation

Dataset distillation is a method for reducing dataset sizes: the goal is...
10/06/2019 ∙ by Ilia Sucholutsky, et al. ∙ 46 ∙ share

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Deep Neural Network Fingerprinting by Conferrable Adversarial Examples

In Machine Learning as a Service, a provider trains a deep neural networ...
12/02/2019 ∙ by Nils Lukas, et al. ∙ 31 ∙ share

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BayesOD: A Bayesian Approach for Uncertainty Estimation in Deep Object Detectors

One of the challenging aspects of incorporating deep neural networks int...
03/09/2019 ∙ by Ali Harakeh, et al. ∙ 28 ∙ share

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Deep Learning for Image and Point Cloud Fusion in Autonomous Driving: A Review

Autonomous vehicles are experiencing rapid development in the past few y...
04/10/2020 ∙ by Yaodong Cui, et al. ∙ 24 ∙ share

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Deep Learning for LiDAR Point Clouds in Autonomous Driving: A Review

Recently, the advancement of deep learning in discriminative feature lea...
05/20/2020 ∙ by Ying Li, et al. ∙ 23 ∙ share

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Investigating the Impact of Inclusion in Face Recognition Training Data on Individual Face Identification

Modern face recognition systems leverage datasets containing images of h...
01/09/2020 ∙ by Chris Dulhanty, et al. ∙ 21 ∙ share

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AnoNet: Weakly Supervised Anomaly Detection in Textured Surfaces

Humans can easily detect a defect (anomaly) because it is different or s...
11/24/2019 ∙ by Manpreet Singh Minhas, et al. ∙ 20 ∙ share

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Principal Component Analysis Using Structural Similarity Index for Images

Despite the advances of deep learning in specific tasks using images, th...
08/25/2019 ∙ by Benyamin Ghojogh, et al. ∙ 19 ∙ share

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Active Preference Learning using Maximum Regret

We study active preference learning as a framework for intuitively speci...
05/08/2020 ∙ by Nils Wilde, et al. ∙ 19 ∙ share

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Representation Learning of Histopathology Images using Graph Neural Networks

Representation learning for Whole Slide Images (WSIs) is pivotal in deve...
04/16/2020 ∙ by Mohammed Adnan, et al. ∙ 16 ∙ share

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Affordance Learning In Direct Perception for Autonomous Driving

Recent development in autonomous driving involves high-level computer vi...
03/20/2019 ∙ by Chen Sun, et al. ∙ 14 ∙ share

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Gated-SCNN: Gated Shape CNNs for Semantic Segmentation

Current state-of-the-art methods for image segmentation form a dense ima...
07/12/2019 ∙ by Towaki Takikawa, et al. ∙ 14 ∙ share

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Unsupervised Domain Adaptation in Person re-ID via k-Reciprocal Clustering and Large-Scale Heterogeneous Environment Synthesis

An ongoing major challenge in computer vision is the task of person re-i...
01/14/2020 ∙ by Devinder Kumar, et al. ∙ 11 ∙ share

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Auto-Classification of Retinal Diseases in the Limit of Sparse Data Using a Two-Streams Machine Learning Model

Automatic clinical diagnosis of retinal diseases has emerged as a promis...
08/16/2018 ∙ by C. -H. Huck Yang, et al. ∙ 10 ∙ share

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Multivariate time-series modeling with generative neural networks

Generative moment matching networks (GMMNs) are introduced as dependence...
02/25/2020 ∙ by Marius Hofert, et al. ∙ 9 ∙ share

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Urban Driving with Multi-Objective Deep Reinforcement Learning

Autonomous driving is a challenging domain that entails multiple aspects...
11/21/2018 ∙ by Changjian Li, et al. ∙ 8 ∙ share

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Improving the Performance of the LSTM and HMM Models via Hybridization

Language models based on deep neural neural networks and traditionalstoc...
07/09/2019 ∙ by Larkin Liu, et al. ∙ 8 ∙ share

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Learning beamforming in ultrasound imaging

Medical ultrasound (US) is a widespread imaging modality owing its popul...
12/19/2018 ∙ by Sanketh Vedula, et al. ∙ 6 ∙ share

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Approximate Inference in Structured Instances with Noisy Categorical Observations

We study the problem of recovering the latent ground truth labeling of a...
06/29/2019 ∙ by Alireza Heidari, et al. ∙ 5 ∙ share

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p-Norm Flow Diffusion for Local Graph Clustering

Local graph clustering and the closely related seed set expansion proble...
05/20/2020 ∙ by Shenghao Yang, et al. ∙ 5 ∙ share

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Unsupervised Feature Learning Toward a Real-time Vehicle Make and Model Recognition

Vehicle Make and Model Recognition (MMR) systems provide a fully automat...
06/08/2018 ∙ by Amir Nazemi, et al. ∙ 4 ∙ share

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A Hierarchical Deep Architecture and Mini-Batch Selection Method For Joint Traffic Sign and Light Detection

Traffic light and sign detectors on autonomous cars are integral for roa...
06/20/2018 ∙ by Alex D. Pon, et al. ∙ 4 ∙ share

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Blind Image Quality Assessment Using A Deep Bilinear Convolutional Neural Network

We propose a deep bilinear model for blind image quality assessment (BIQ...
07/05/2019 ∙ by Weixia Zhang, et al. ∙ 3 ∙ share

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A Survey of Recent Advances in Texture Representation

Texture is a fundamental characteristic of many types of images, and tex...
01/31/2018 ∙ by Li Liu, et al. ∙ 2 ∙ share

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Tails of Triangular Flows

Triangular maps are a construct in probability theory that allows the tr...
07/10/2019 ∙ by Priyank Jaini, et al. ∙ 2 ∙ share

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Deep Learning for System Trace Restoration

Most real-world datasets, and particularly those collected from physical...
04/10/2019 ∙ by Ilia Sucholutsky, et al. ∙ 1 ∙ share

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FPCNet: Fast Pavement Crack Detection Network Based on Encoder-Decoder Architecture

Timely, accurate and automatic detection of pavement cracks is necessary...
07/04/2019 ∙ by Wenjun Liu, et al. ∙ 1 ∙ share

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Efficient Segmentation: Learning Downsampling Near Semantic Boundaries

Many automated processes such as auto-piloting rely on a good semantic s...
07/16/2019 ∙ by Dmitrii Marin, et al. ∙ 1 ∙ share

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Tri-graph Information Propagation for Polypharmacy Side Effect Prediction

The use of drug combinations often leads to polypharmacy side effects (P...
01/28/2020 ∙ by Hao Xu, et al. ∙ 1 ∙ share

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Pylearn2: a machine learning research library

Pylearn2 is a machine learning research library. This does not just mean...
08/20/2013 ∙ by Ian J. Goodfellow, et al. ∙ 0 ∙ share

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Quegel: A General-Purpose Query-Centric Framework for Querying Big Graphs

Pioneered by Google's Pregel, many distributed systems have been develop...
01/25/2016 ∙ by Da Yan, et al. ∙ 0 ∙ share

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Fast, deterministic computation of the Hermite normal form and determinant of a polynomial matrix

Given a nonsingular n × n matrix of univariate polynomials over a field ...
07/14/2016 ∙ by George Labahn, et al. ∙ 0 ∙ share

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Fast Computation of the Roots of Polynomials Over the Ring of Power Series

We give an algorithm for computing all roots of polynomials over a univa...
05/30/2017 ∙ by Vincent Neiger, et al. ∙ 0 ∙ share

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Fast Computation of Minimal Interpolation Bases in Popov Form for Arbitrary Shifts

We compute minimal bases of solutions for a general interpolation proble...
02/01/2016 ∙ by Claude-Pierre Jeannerod, et al. ∙ 0 ∙ share

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Order-Planning Neural Text Generation From Structured Data

Generating texts from structured data (e.g., a table) is important for v...
09/01/2017 ∙ by Lei Sha, et al. ∙ 0 ∙ share

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SquishedNets: Squishing SqueezeNet further for edge device scenarios via deep evolutionary synthesis

While deep neural networks have been shown in recent years to outperform...
11/20/2017 ∙ by Mohammad Javad Shafiee, et al. ∙ 0 ∙ share

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Joint 3D Proposal Generation and Object Detection from View Aggregation

We present AVOD, an Aggregate View Object Detection network for autonomo...
12/06/2017 ∙ by Jason Ku, et al. ∙ 0 ∙ share

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Generating Thematic Chinese Poetry with Conditional Variational Autoencoder

Computer poetry generation is our first step towards computer writing. W...
11/21/2017 ∙ by Xiaopeng Yang, et al. ∙ 0 ∙ share

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JADE: Joint Autoencoders for Dis-Entanglement

The problem of feature disentanglement has been explored in the literatu...
11/24/2017 ∙ by Ershad Banijamali, et al. ∙ 0 ∙ share

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Opposition based Ensemble Micro Differential Evolution

Differential evolution (DE) algorithm with a small population size is ca...
09/08/2017 ∙ by Hojjat Salehinejad, et al. ∙ 0 ∙ share

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The Mating Rituals of Deep Neural Networks: Learning Compact Feature Representations through Sexual Evolutionary Synthesis

Evolutionary deep intelligence was recently proposed as a method for ach...
09/07/2017 ∙ by Audrey Chung, et al. ∙ 0 ∙ share

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Exploring the Imposition of Synaptic Precision Restrictions For Evolutionary Synthesis of Deep Neural Networks

A key contributing factor to incredible success of deep neural networks ...
07/01/2017 ∙ by Mohammad Javad Shafiee, et al. ∙ 0 ∙ share

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Synthesizing Deep Neural Network Architectures using Biological Synaptic Strength Distributions

In this work, we perform an exploratory study on synthesizing deep neura...
07/01/2017 ∙ by A. H. Karimi, et al. ∙ 0 ∙ share

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Discovery Radiomics via Evolutionary Deep Radiomic Sequencer Discovery for Pathologically-Proven Lung Cancer Detection

While lung cancer is the second most diagnosed form of cancer in men and...
05/10/2017 ∙ by Mohammad Javad Shafiee, et al. ∙ 0 ∙ share

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Evolution in Groups: A deeper look at synaptic cluster driven evolution of deep neural networks

A promising paradigm for achieving highly efficient deep neural networks...
04/07/2017 ∙ by Mohammad Javad Shafiee, et al. ∙ 0 ∙ share

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Classification-based RNN machine translation using GRUs

We report the results of our classification-based machine translation mo...
03/22/2017 ∙ by Ri Wang, et al. ∙ 0 ∙ share

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Affective Neural Response Generation

Existing neural conversational models process natural language primarily...
09/12/2017 ∙ by Nabiha Asghar, et al. ∙ 0 ∙ share

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An Analysis of ISO 26262: Using Machine Learning Safely in Automotive Software

Machine learning (ML) plays an ever-increasing role in advanced automoti...
09/07/2017 ∙ by Rick Salay, et al. ∙ 0 ∙ share

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