Guanghui Wang, Toronto Metropolitan University

Research

computer vision Machine learning 3D mapping autonomous systems convolutional neural network environment perception robotics structure from motion

Latest papers

Artificial intelligence-based prediction of procedural success in transcatheter mitral valve edge-to-edge repair.
Echo research and practice · 2026
Supervised and Self-Supervised Learning for Assembly Line Action Recognition.
Journal of imaging · 2025 · senior author
A New Dataset and Comparative Study for Aphid Cluster Detection and Segmentation in Sorghum Fields.
Journal of imaging · 2024 · senior author

All 12 publications

Latest funding

Semantic 3D mapping and localization of intelligent drones in indoor environments
NSERC · 2023 · Principal investigator
$60,000
Intelligent Assembly Action Recognition for Next Generation Manufacturing
NSERC · 2022 · Principal investigator
$180,000
AI-enabled food waste differentiation for at-home compost nutrients estimation
NSERC · 2022 · Principal investigator
$60,000

All 6 grants and awards

12 publications.

01

Artificial intelligence-based prediction of procedural success in transcatheter mitral valve edge-to-edge repair.

Claeys M, Fam N, Xiao X, Vyas T, Chowdhury M, Moe G, Alnasser S, Prud'homme P, Merdad A, Bagai A, Connelly KA, Edwards J, Wang G, Ong G

Echo research and practice2026

DOI: 10.1186/s44156-026-00134-2 PMID: 42702733

02

Supervised and Self-Supervised Learning for Assembly Line Action Recognition.

Indris C, Ibrahim F, Ibrahem H, Bramesfeld G, Huo J, Ahmad HM, Hayat SK, Wang G

Journal of imaging2025Senior author

DOI: 10.3390/jimaging11010017 PMID: 39852330

03

A New Dataset and Comparative Study for Aphid Cluster Detection and Segmentation in Sorghum Fields.

Rahman R, Indris C, Bramesfeld G, Zhang T, Li K, Chen X, Grijalva I, McCornack B, Flippo D, Sharda A, Wang G

Journal of imaging2024Senior author

DOI: 10.3390/jimaging10050114 PMID: 38786568

04

Interpretable Computer Vision to Detect and Classify Structural Laryngeal Lesions in Digital Flexible Laryngoscopic Images.

Bur AM, Zhang T, Chen X, Kavookjian H, Kraft S, Karadaghy O, Farrokhian N, Mussatto C, Penn J, Wang G

Otolaryngology--head and neck surgery : official journal of American Academy of Otolaryngology-Head and Neck Surgery2023Senior author

DOI: 10.1002/ohn.411 PMID: 37350279

05

Aphid cluster recognition and detection in the wild using deep learning models.

Zhang T, Li K, Chen X, Zhong C, Luo B, Grijalva I, McCornack B, Flippo D, Sharda A, Wang G

Scientific reports2023Senior author

DOI: 10.1038/s41598-023-38633-5 PMID: 37591898

06

Gender, Smoking History, and Age Prediction from Laryngeal Images.

Zhang T, Bur AM, Kraft S, Kavookjian H, Renslo B, Chen X, Luo B, Wang G

Journal of imaging2023Senior author

DOI: 10.3390/jimaging9060109 PMID: 37367457

07

Dynamic Label Assignment for Object Detection by Combining Predicted IoUs and Anchor IoUs.

Zhang T, Luo B, Sharda A, Wang G

Journal of imaging2022Senior author

DOI: 10.3390/jimaging8070193 PMID: 35877638

08

Harnessing the Power of Artificial Intelligence in Otolaryngology and the Communication Sciences.

Wilson BS, Tucci DL, Moses DA, Chang EF, Young NM, Zeng FG, Lesica NA, Bur AM, Kavookjian H, Mussatto C, Penn J, Goodwin S, Kraft S, Wang G, Cohen JM, Ginsburg GS, Dawson G, Francis HW

Journal of the Association for Research in Otolaryngology : JARO2022

DOI: 10.1007/s10162-022-00846-2 PMID: 35441936

09

A Discriminative Channel Diversification Network for Image Classification.

Patel K, Wang G

Pattern recognition letters2022Senior author

DOI: 10.1016/j.patrec.2021.12.004 PMID: 35938044

10

Colonoscopy polyp detection and classification: Dataset creation and comparative evaluations.

Li K, Fathan MI, Patel K, Zhang T, Zhong C, Bansal A, Rastogi A, Wang JS, Wang G

PloS one2021Senior author

DOI: 10.1371/journal.pone.0255809 PMID: 34403452

Semantic 3D mapping and localization of intelligent drones in indoor environments

Principal investigatorNSERC2023Alliance Grants

Principal investigators: Wang, Guanghui G

Keywords: computer vision; indoor drone; machine learning; object detection; semantic map building; visual slam

$60,000

Intelligent Assembly Action Recognition for Next Generation Manufacturing

Principal investigatorNSERC2022Alliance Grants

Principal investigators: Wang, Guanghui G

Keywords: Assembly action recognition; Computer vision; Machine learning; Manufacturing; Self-supervised learning

$180,000

AI-enabled food waste differentiation for at-home compost nutrients estimation

Principal investigatorNSERC2022Alliance Grants

Principal investigators: Wang, Guanghui G

Keywords: Compost; Computer vision; Deep learning; Food waste classification; Image analysis; Machine learning

$60,000

Non-coding RNA Structure Analysis Based on Deep Neural Networks

Principal investigatorNSERC2022Alliance Grants

Principal investigators: Wang, Guanghui G

$25,000

Promoting 3D Environment Perception Ability of Autonomous Systems

Principal investigatorNSERC2021Discovery Grants Program - Individual

Principal investigators: Wang, Guanghui

Keywords: computer vision; environment perception; convolutional neural network; autonomous systems; structure from motion; 3d mapping; robotics

$116,000

Wildlife habitat mapping using a small aerial vehicle

Co-investigatorNSERC2021Alliance Grants

Principal investigators: Bramesfeld, Goetz G

$709,700

From CIHR, NSERC and SSHRC funding decisions: CIHR since 2008, NSERC since 1991 and SSHRC since 1998, including their latest published competition results.

Frequent collaborators

Goetz Bramesfeld

Aerospace Engineering

1 shared papers, latest 2024

Write to this professor

A short, specific email works best. This draft uses one of their recent papers; replace the parts in brackets with your own details before sending.

Applying for

Paper to mentionMention their NSERC grant from 2023

Subject: Prospective PhD student: computer vision Dear Professor Wang, My name is [your name], and I am a [your current degree or role] at [your institution]. I am applying for a PhD position starting in [term and year]. I read your paper "Artificial intelligence-based prediction of procedural success in transcatheter mitral valve edge-to-edge repair." (2026), and it connects closely to my own work on [your research topic]. [One or two sentences on what you did and what you learned.] I also saw your NSERC-funded project "Semantic 3D mapping and localization of intelligent drones in indoor environments" (2023), and I would be glad to contribute to work in that direction. Are you accepting new PhD students for [term and year]? I have attached my CV and transcripts, and I would be glad to talk at a time that suits you. Thank you for your time. Kind regards, [your name]