Session: Convolutional Neural Network (Deep Learning)
One of the basic human abilities is to analyze their environment. This involves in most cases recognizing the elements of our field of vision: finding others, identifying cars, animals, etc. This task was difficult for a computer until the emergence of convolutional neural networks in 2012. Luckily, the approach of these networks inspired by our visual cortex has opened many applications, whether in medical imaging, or autonomous cars…ect.
First of all I will give a brief introduction on Deep Learning and Artificial Neural networks then i will explain how a convolutional neural network works. In particular, I will present the different elements of a CNN architecture (convolutions, pooling, ReLU, flattening, dense ...) and real networks used in production.
- Artificial Intelligence /Deep learning
- Artificial neural networks /Convolutional Neural Networks
- Transfer Learning
Computer Engineer/Android Developer/Data Scientist