Recognition of Mexican cultural content with Deep learning networks

The chosen sample consists of 200 members belonging to associations of this kind in the capital Algiers; the chosen method is the follow-up and the analysis and the

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

Supervised learning consists of learning the conditional

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 systematically depicted different cross- modality learning approaches of four methods based on Con- volutional Neural Networks for pedestrian recognition: (1)

The first Week for Biological and Cultural Diversity staged in 2001 in San Cristóbal de las Casas in the state of Chiapas and the follow-up event in 2002,

While the output feature vector is robust to local changes, its robustness to global deformations needs improvements since it preserves too much spatial information. In [5, 7,

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