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Jesse Thé

University of Waterloo

Waterloo, N2L 3G1

Canada

  • University of Waterloo

SCHOLARLY PAPERS

3

DOWNLOADS

198

TOTAL CITATIONS

1

Scholarly Papers (3)

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1.

Evaluation of Deep Learning Methods for Forecasting Turbidity in River Networks Using Sentinel-2 Remote Sensing Data

Number of pages: 36 Posted: 29 Jan 2025
Victor Santos, Paulo Rocha, Jesse Thé and Bahram Gharabaghi
University of Guelph, Federal University of Ceara, University of Waterloo and University of Guelph
Downloads 80 (803,225)
Citation 1

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Sentinel Satellite Constellation, machine learning, Turbidity, Spectral Indices, Mississippi River, Missouri River

2.

Enhancing Turbidity Modeling in the Mississippi River Using Machine Learning and Sentinel-2 Satellite Remote Sensing Data: A Generalizability Analysis

Number of pages: 35 Posted: 08 Oct 2024
Victor Santos, Paulo Alexandre Rocha, Jesse Thé and Bahram Gharabaghi
Federal University of Ceará, Federal University of Ceará, University of Waterloo and University of Guelph
Downloads 68 (891,180)

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Sentinel Satellite Constellation, Machine Learning, Turbidity, Spectral Indices, Mississippi River, Missouri River

3.

Multi-Step Forecast of Pm2.5 and Pm10 Concentrations Using Convolutional Neural Network Integrated with Spatial-Temporal Attention and Residual Learning

Number of pages: 41 Posted: 30 Sep 2022
Kefei Zhang, Xiaolin Yang, Hua Cao, Jesse Thé, Zhongchao Tan and Hesheng Yu
affiliation not provided to SSRN, affiliation not provided to SSRN, affiliation not provided to SSRN, University of Waterloo, University of Waterloo and affiliation not provided to SSRN
Downloads 50 (1,086,013)

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PM concentration forecasting, Deep learning, Spatial-temporal attention, Residual learning, Convolutional neural network