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Mark Thomas
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Marine mammal species classification using convolutional neural networks and a novel acoustic representation
M Thomas, B Martin, K Kowarski, B Gaudet, S Matwin
Machine Learning and Knowledge Discovery in Databases: European Conference …, 2020
622020
ConfusionVis: Comparative evaluation and selection of multi-class classifiers based on confusion matrices
A Theissler, M Thomas, M Burch, F Gerschner
Knowledge-Based Systems 247, 108651, 2022
532022
Inverse problem for time-series valued computer model via scalarization
P Ranjan, M Thomas, H Teismann, S Mukhoti
arXiv preprint arXiv:1605.09503, 2016
162016
An end-to-end approach for true detection of low frequency marine mammal vocalizations
M Thomas, B Martin, K Kowarski, B Gaudet, S Matwin
The Journal of the Acoustical Society of America 146 (4_Supplement), 2959-2959, 2019
72019
Towards a Novel Data Representation for Classifying Acoustic Signals
M Thomas
Advances in Artificial Intelligence: 32nd Canadian Conference on Artificial …, 2019
12019
Detecting Endangered Baleen Whales within Acoustic Recordings using R-CNNs
M Thomas, B Martin, K Kowarski, B Gaudet, S Matwin
1
Applications of Deep Convolutional Neural Networks to Passive Acoustic Monitoring of Baleen Whales
M Thomas
2024
Interpreting the latent representations of a convolutional neural network trained on spectrograms
M Thomas, B Martin, K Kowarski, B Gaudet, S Matwin
The Journal of the Acoustical Society of America 146 (4_Supplement), 2958-2959, 2019
2019
Leveraging Unlabelled Data through Semi-supervised Learning to Improve the Performance of a Marine Mammal Classification System
M Thomas, B Martin, S Matwin
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Articles 1–9