Symposium Program

Overview and details of the sessions of the 45th Canadian Symposium on Remote Sensing. Please select a date or location to show only sessions at that day or location. Please select a single session for further details on the presentations. Once you select a session or choose the List View of the program, you can access the extended abstracts by clicking on the button "Show Downloads" . *** You should be logged into your ConfTool account to be able to see the downloadable items ***

 
Authors
 
Preliminary Program of the Canadian Symposium on Remote Sensing
Session
Poster Session 1: Artificial Intelligence Methods and Models - Part 1
Time:
Tuesday, 11/June/2024:
4:40pm - 5:40pm

 Location: SUB McInnes Room

Poster stand numbers: 01-09

Show help for 'Increase or decrease the abstract text size'
Presentations

Improving the resolution of multispectral satellite imagery using Deep Learning-based Pansharpening

K. Roy, S. Homayouni, Dr. Y. Zhang

INRS, Canada


Spatially Informed Tabular Deep Learning for Accurate Building Extraction from UAV Imagery: A GEOBIA Approach

M. Hossain, Dr. D. Chen

Queen's University, Canada


An Automated Method for Pavement Surface Distress Evaluation

D. Satheesan, M. Talib, Dr. S. Li, Dr. A. X. Yuan

Toronto Metropolitan University, Canada


Discrete Wavelet Transformation for De-noising of AI Classified Ground Data

H. Steiner1, M. L. Ethier2, O. Brown2, O. Pylypenko1

1GeoBC, Canada; 2University of Victoria, BC, Canada


Estimating Biases in TROPOMI concentration methane product using a machine learning algorithm

M. Marjani1, M. Mahdianpari1,2, E. W Gill1, F. Mohammadimanesh2

1Memorial University of Newfoundland, Canada; 2C-CORE


Evaluation of Hybrid Satellite On-Board Computer Architectures for Edge-Compute and Machine-Learning Focussed Applications

A. Amellal, J. Langille, M. Seto

Dalhousie University, Canada


Non-Cooperative Vessel Detection using Multispectral Satellite Imaging and Machine Learning Applied towards Onboard Satellite Dark Vessel Detection

K. J. M. Earle, Dr. M. L. Seto

Dalhousie University


Conifer Tree Classification using Detectron2 and ConvNext from UAV Imagery Data

R. Sharma, K. F. Zhang

University of fraser valley, Canada