Convolutional operators in the time-frequency domain

Here, we have used a data-driven clustering method, called smoothing spline clustering (SSC), that overcomes the aforementioned obstacles using a mixed-effect smoothing spline model

This strategy is much harder and not feasible for common objects as they are a lot more diverse. As an illustration, the winner of the COCO challenge 2017 [274], which used many of

This thesis studies empirical properties of deep convolutional neural net- works, and in particular the Scattering Transform.. Indeed, the theoretical anal- ysis of the latter is

 pushing forward to weakly supervised learning the problem Medical Image Segmentation of Thoracic Organs at Risk in CT-images..

Modern signal processing techniques previously used in the field of speech recognition have also made significant progress in the field of automatic detection of abnormal voice..

Enfin, figurent également dans l’exposition des exemplaires de journaux comme la Chronique genevoise ou de journaux satiriques comme Le Carillon de St-Gervais et le Pierrot

In this paper, we evaluate the efficiency of using CNNs for source camera model identification based on deep learning and convolutional neural networks.. The contribution repre- sents

Chaumont, ”Camera Model Identification Based Machine Learning Approach With High Order Statistics Features”, in EUSIPCO’2016, 24th European Signal Processing Conference 2016,