Deep learning techniques are based on neural networks, sometimes referred to as artificial neural networks (ANNs) or simulated neural networks (SNNs), which are a subset of machine learning. Their structure and nomenclature are modelled after the human brain, mirroring the communication between organic neurons. A node layer, which includes an input layer, one or more hidden layers, and an output layer, makes up artificial neural networks. Each node, or artificial neuron, is connected to others and has a weight and threshold that go along with it. Any node whose output exceeds the defined threshold value is activated and begins providing data to the network's uppermost layer. Otherwise, no data is sent to the network's next tier.







Title : Change your genes – Change your life: Epigenetics of longevity
Kenneth R Pelletier, University of California, United States
Title : Harmonisation legislation issues in health care public policies to prevent obesity
Iuliana Vintila, Dunarea de Jos University, Galati, Romania