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"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...

This work is based on research and advocacy with the people of two multiethnic indigenous resguardos located at the outskirts of the Colombian towns of Leticia and Puerto Nariño. Through an analysis of the relationship ...

Subjects / keywords: Derecho; Defensa de Menores

Subjects / keywords: Redes

Subjects / keywords: Ingeniería y Tecnología; General

Subjects / keywords: Ingeniería y Tecnología; Ingeniería (General)

Subjects / keywords: ROGERS, EVERRETT M; THE FREE PRESS; 004.65 R725c

Subjects / keywords: MARTIN, JAMES; PRENTICE-HALL; 004.65 M381c

Subjects / keywords: DAVIES, D. W; JOHN WILEY & SONS; 004.65 C737c

Subjects / keywords: FORD, L. R; PRINCETON UNIVERSITY PRESS; 519.72 F699f

Subjects / keywords: NEWELL, G. F; THE MIT PRESS; 388 N545t

We report on a series of experiments with convolutional neural networks (CNN) trained on top of pre-trained word vectors for sentence-level classification tasks. We show that a simple CNN with little hyperparameter tunin...

Convolutional neural networks (CNNs) are inherently limited to model geometric transformations due to the fixed geometric structures in their building modules. In this work, we introduce two new modules to enhance the tr...

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...

Wireless distributed microsensor systems will enable the reliable monitoring of a variety of environments for both civil and military applications. In this paper, we look at communication protocols, which can have signif...

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...

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, exceed the state-of-the-art in semantic segme...

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...

Abstract This book provides the first comprehensive treatment of feed-forward neural networks from the perspective of statistical pattern recognition. After introducing the basic concepts of pattern recognition, the book...

Recurrent neural networks (RNNs) are a powerful model for sequential data. End-to-end training methods such as Connectionist Temporal Classification make it possible to train RNNs for sequence labelling problems where th...

Convolutional neural networks are built upon the convolution operation, which extracts informative features by fusing spatial and channel-wise information together within local receptive fields. In order to boost the rep...

Subjects / keywords: SKILLING, HUGH HILDRETH; JOHN WILEY & SONS; 621.3192 S628e

Subjects / keywords: BUSTAMANTE LL; ENRIQUE; EDITORIAL LIMUSA WILEY; 621.3 B982m

Governance of permissioned blockchains is a key issue for the short-term success and further development and consolidation of decentralized ledger technology (DLT) general purpose networks. The present book, written by t...