HYBRID EVENT: Join us in person in Singapore or attend virtually from anywhere.

6th Edition of

International Public Health Conference

March 15-17, 2027 | Singapore

Neural Networks

Neural Networks

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.

Committee Members
Speaker at IPHC 2027 - Kenneth R Pelletier

Kenneth R Pelletier

University of California, United States
Speaker at IPHC 2027 - Thomas J Webster

Thomas J Webster

Brown University, United States
Speaker at IPHC 2027 - Anyou Wang

Anyou Wang

DIFIBER LLC, United States
IPHC 2027 Speakers
Speaker at IPHC 2027 - Vijayan Gurumurthy Iyer

Vijayan Gurumurthy Iyer

Techno-Economic-Environmental Study and Check Consultancy Services
Speaker at IPHC 2027 - K. R. Aneja

K. R. Aneja

Kurukshetra University
Speaker at IPHC 2027 - Fred Moss

Fred Moss

Founder, Welcome to Humanity Grass Valley, California
Speaker at IPHC 2027 - Misgana E Woldemeskel

Misgana E Woldemeskel

The George Washington University

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