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.