Convolutional operators in the time-frequency domain

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

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

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

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

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,

 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..