Artificial Neural Network - Basic Concepts - Neural networks are parallel computing devices, which is basically an attempt to make a computer model of the brain. The main objective is to develop a system to perform various computational tasks faster than
Chapter 1-Introduction to Artificial Neural Network (ANN) as a Predictive Tool for Drug Design, Discovery, Delivery, and Disposition: Basic Concepts and Modeling. In Artificial Neural Network for Drug Design, Delivery and Disposition; Academic Press: Boston, MA, USA, 2016; pp. 3-13, ISBN 978...
The adjective "neural" refers to a neuron, while "network" refers to a graph-like structure. The term "artificial neural network" describes computer processes based on the basic concept of biological neural networks. ANN is made up of interconnected artificial neurons that are programmed to ...
Artificial neural network (ANN) models in the present study. Schema showing the input, hidden, and output layers of (A) ANN model 1 to predict sICH, and (B) ANN model 2 to predict the 3-month mortality. Af, atrial fibrillation; ANN, artificial neural network; BP, blood pressure; DM,...
“Deep Learning in a Nutshell: Core Concepts”Dettmers, Tim. Technical Blog. NVIDIA, 3 Nov 2015. “Accelerate Machine Learning with the cuDNN Deep Neural Network Library”Brown, Larry. Technical Blog. NVIDIA, 7 Sep 2014. “cuDNN v2: Higher Performance for Deep learning on GPUs”Brown, Larr...
This article offers a brief glimpse of the history and basic concepts of machine learning. We will take a look at the first algorithmically described neural network and the gradient descent algorithm in context of adaptive linear neurons, which will not only introduce the principles of machine ...
1. Feedforward Neural Network These are the most basic ANNs. The data moves only in one direction, passing through various input nodes till it reaches the output node. It calculates the sum of the products of all the inputs and their weights, this is then fed to the output. 2. Radial...
Introduction to Artificial Neural Network (ANN) Methods: What They Are and How to Use Them 来自 Semantic Scholar 喜欢 0 阅读量: 103 作者: J Zupan 摘要: Basic concepts of ANNs together with three most widely used ANN learning strategies (error back-propagation, Kohonen, and counter- ...
Artificial neural networks (ANN) methodology is a modeling method with great ability to adapt to a new situation, or control an unknown system, using data acquired in previous experiments. In this paper, a brief history of ANN and the basic concepts behind the computing, the mathematical and ...
4.5 Deep neural network 5Chapter 5 Machine Learning 5.1 Supervised learning 5.2 Basic theories and methods of deep learning 5.3 Deep learning applications 5.4 Reinforcement learning 5.5 Transfer learning 5.6 Machine game 5.7 Machine art creation ...