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Subjects / keywords: network intelligence, neural networks, general networks, network learning, network optimization, software publication; Technology: Technology (General): Industrial engineering. Management engineering: Information technol...

Security governance surrounding infectious diseases necessitates collaboration and information sharing among diverse actors, including nation-states and institutions. The Global Antimicrobial Resistance Surveillance Syst...

La inteligencia artificial permite la innovación y el cambio en todos los aspectos de la vida moderna. La mayoría de los avances actuales se basan en Deep Learning, un área de conocimiento muy madura que permite a las...

The network society (Van Dijk, 2020) has completely blurred the traditional difference between virtual and real life, Our day to day is increasingly characterised by our continuous connection to the Internet, Multiple da...

The Artificial Intelligence (AI) revolution, in its different manifestations -expert systems, neural networks, intelligent hybrid systems, etc.- brings with it many technological advances. Although this technology has so...

El vertiginoso crecimiento y la precisión de las técnicas de Inteligencia Artificial (AI, del inglés Artificial Intelligence) permiten analizar grandes volúmenes de datos de forma rápida y eficiente. En ese sentido,...

The long-anticipated revision of this #1 selling book offers the most comprehensive, state of the art introduction to the theory and practice of artificial intelligence for modern applications. Intelligent Agents. Solvin...

Social insects--ants, bees, termites, and wasps--can be viewed as powerful problem-solving systems with sophisticated collective intelligence. Composed of simple interacting agents, this intelligence lies in the networks...

PROBLEM/CONDITION: Autism spectrum disorder (ASD). PERIOD COVERED: 2014. DESCRIPTION OF SYSTEM: The Autism and Developmental Disabilities Monitoring (ADDM) Network is an active surveillance system that provides estimates...

Subjects / keywords: Business intelligence; Computer network resources; Industrial management

Subjects / keywords: ChatGPT; Neural networks (Computer science); Artificial intelligence; Chatbots; Social networks

Subjects / keywords: Artificial intelligence; Neural networks (Computer science); Art and technology

Subjects / keywords: Intelligence service; Computer networks; Colombia

Subjects / keywords: Neural networks (Computer science); Artificial intelligence; Electronic data processing; Electronic books

Subjects / keywords: Neural networks (Computer science); Artificial intelligence; Information networks; Machine learning

Subjects / keywords: Artificial intelligence; Neural networks (Computer science); Electronic books

"The scientific study of networks, including computer networks, social networks, and biological networks, has received an enormous amount of interest in the last few years. The rise of the Internet and the wide availabil...

We present a highly accurate single-image superresolution (SR) method. Our method uses a very deep convolutional network inspired by VGG-net used for ImageNet classification [19]. We find increasing our network depth sho...

DeepMind presented notably accurate predictions at the recent 14th Critical Assessment of Structure Prediction (CASP14) conference. We explored network architectures that incorporate related ideas and obtained the best p...

In the first part of this paper, a regular recurrent neural network (RNN) is extended to a bidirectional recurrent neural network (BRNN). The BRNN can be trained without the limitation of using input information just up ...

Recent work has shown that convolutional networks can be substantially deeper, more accurate, and efficient to train if they contain shorter connections between layers close to the input and those close to the output. In...

We propose a technique for producing `visual explanations' for decisions from a large class of Convolutional Neural Network (CNN)-based models, making them more transparent. Our approach - Gradient-weighted Class Activat...

Lots of learning tasks require dealing with graph data which contains rich relation information among elements. Modeling physics systems, learning molecular fingerprints, predicting protein interface, and classifying dis...

We propose a deep learning method for single image super-resolution (SR). Our method directly learns an end-to-end mapping between the low/high-resolution images. The mapping is represented as a deep convolutional neural...