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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,...

El objetivo del trabajo es realizar un diagnóstico socio-territorial de dos asentamientos espontáneos de la ciudad de Puerto Madryn (Chubut, Argentina): La Lomita y Alta Tensión, a partir de la aplicación del Método...

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

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...

Convolutional networks are powerful visual models that yield hierarchies of features. We show that convolutional networks by themselves, trained end-to-end, pixels-to-pixels, improve on the previous best result in semant...

Recently, several models based on deep neural networks have achieved great success in terms of both reconstruction accuracy and computational performance for single image super-resolution. In these methods, the low resol...

Subjects / keywords: Monte Carlo tree search; Computer science; Champion; Artificial neural network; Reinforcement learning; Artificial intelligence; Game tree; Value (mathematics); Search algorithm; Tree (set theory); Deep neural networks; ...

The popular Q-learning algorithm is known to overestimate action values under certain conditions. It was not previously known whether, in practice, such overestimations are common, whether they harm performance, and whet...

Deeper neural networks are more difficult to train. We present a residual learning framework to ease the training of networks that are substantially deeper than those used previously. We explicitly reformulate the layers...

Importance: Deep learning is a family of computational methods that allow an algorithm to program itself by learning from a large set of examples that demonstrate the desired behavior, removing the need to specify rules ...

Several variants of the long short-term memory (LSTM) architecture for recurrent neural networks have been proposed since its inception in 1995. In recent years, these networks have become the state-of-the-art models for...

In this work, we revisit the global average pooling layer proposed in [13], and shed light on how it explicitly enables the convolutional neural network (CNN) to have remarkable localization ability despite being trained...

Convolutional networks are at the core of most state of-the-art computer vision solutions for a wide variety of tasks. Since 2014 very deep convolutional networks started to become mainstream, yielding substantial gains ...

Subjects / keywords: Computer science; Pascal (unit); Object detection; Artificial intelligence; Resampling; Detector; Pixel; Single shot; Computation; Feature (linguistics); Artificial neural network; Minimum bounding box