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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,...

By introducing the artificial intelligence technology, on improved Nelder-Mead acceleration algorithm based on the neural network is proposed to obtain better optimization results. A back analysis method for construction...

The ability to learn tasks in a sequential fashion is crucial to the development of artificial intelligence. Until now neural networks have not been capable of this and it has been widely thought that catastrophic forget...

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

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...

Feature pyramids are a basic component in recognition systems for detecting objects at different scales. But pyramid representations have been avoided in recent object detectors that are based on deep convolutional netwo...

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...

We trained a large, deep convolutional neural network to classify the 1.2 million high-resolution images in the ImageNet LSVRC-2010 contest into the 1000 different classes. On the test data, we achieved top-1 and top-5 e...

Despite the breakthroughs in accuracy and speed of single image super-resolution using faster and deeper convolutional neural networks, one central problem remains largely unsolved: how do we recover the finer texture de...

Subjects / keywords: Convolutional neural network; Skin cancer; Artificial intelligence; Deep learning; Medicine; Computer science; Biopsy; Skin biopsy; Deep neural networks; Cancer; Pattern recognition (psychology); Dermatology

Subjects / keywords: Convolutional neural network; Computer science; Deep learning; Artificial intelligence; Activation function; Artificial neural network; Computation; Machine learning; Graphics; Pattern recognition (psychology); Algorithm...

Subjects / keywords: Cluster analysis; Inference; Computational biology; Computer science; Gene regulatory network; Artificial intelligence; Biology; Genetics; Gene; Gene expression

In this work we address the task of semantic image segmentation with Deep Learning and make three main contributions that are experimentally shown to have substantial practical merit. First, we highlight convolution with...

Very deep convolutional networks have been central to the largest advances in image recognition performance in recent years. One example is the Inception architecture that has been shown to achieve very good performance ...