On the Impact of Interlanguage Dependencies in Multilanguage Systems Empirical Case Study on Java Native Interface Applications (JNI)

M. Grichi, M. Abidi, F. Jaafar, E. E. Eghan and B. Adams, « On the Impact of Interlanguage Dependencies in Multilanguage Systems Empirical Case Study on Java Native Interface Applications (JNI), » in IEEE Transactions on Reliability, Volume 70, No. 1, pp. 428-440, March 2021.

Investigating Design Anti-pattern and Design Pattern Mutations and Their Change- and Fault-proneness

Z.A. Kermansaravi, M.S. Rahman, F. Khomh, F. Jaafar and Y.-G. Guéhéneuc, « Investigating Design Anti-pattern and Design Pattern Mutations and Their Change- and Fault-proneness » in Empirical Software Engineering, Springer,  Issue 1/2021.

Train fast while reducing false positives: improving animal classification performance using Convolutional Neural Networks

M. Moreni, J. Theau and S. Foucher, « Train fast while reducing false positives: improving animal classification performance using Convolutional Neural Networks », in Geomatics, no. 1: 34-49, 2021.

New Interferometric Phase Unwrapping Method Based on Energy Minimization From Contextual Modeling

A. Tlili, F. Cavayas, S. Foucher and G. L. Siles, « New Interferometric Phase Unwrapping Method Based on Energy Minimization From Contextual Modeling », in IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Volume 13, pp. 6524-6532, December 2020.

Automatic Detection of Flavescence Dorée Symptoms Across White Grapevine Varieties Using Deep Learning

J. Boulent, P.L. St-Charles, S. Foucher and J. Théau, « Automatic Detection of Flavescence Dorée Symptoms Across White Grapevine Varieties Using Deep Learning », in Frontiers in Artificial Intelligence, November 2020.

A Circular Invariant Convolution Model-Based Mapping for Multimodal Change Detection

R. Touati, M. Mignotte and M. Dahmane, « A Circular Invariant Convolution Model-Based Mapping for Multimodal Change Detection », in Advances in Science, Technology and Engineering Systems Journal, Vol. 5, No. 5, pp. 1288-1298, 2020.

A Study of Inductive Biases for Unsupervised Speech Representation Learning

G. Boulianne, « A Study of Inductive Biases for Unsupervised Speech Representation Learning », in IEEE/ACM Transactions on Acoustics, Speech and Language Processing, October, 2020, pp. 2781-2795.

On the Use of Blind Channel Response Estimation and a Residual Neural Network to Detect Physical Access Attacks to Speaker Verification Systems

A. R. Avila, J. Alam, F. O. Costa Prado, D. O’Shaughnessy, and T. H. Falk, « On the Use of Blind Channel Response Estimation and a Residual Neural Network to Detect Physical Access Attacks to Speaker Verification Systems » in Computer Speech & Language journal, Elsevier, October, 2020.

Generalized End-to-End Detection of Spoofing Attacks to Automatic Speaker Recognizers

J. Montiero, J, Alam, and T. Falk, « Generalized End-to-End Detection of Spoofing Attacks to Automatic Speaker Recognizers », Special issue of Computer Speech & Language Journal, Volume 63, September, 2020.

On the Use of the I-vector Speech Representation for Instrumental Quality Measurement

A. R. Avila, J. Alam, D. O’Shaughnessy, and T. Falk, « On the Use of the I-vector Speech Representation for Instrumental Quality Measurement » in Quality and User Experience Journal, Springer, Volume 5, Number 6, June, 2020, pp. 1-14.