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Subjects / keywords: ACADEMIC PRESS; 003.52 P316p

El eje central de la XII edición del congreso (COMPDES2019) ha sido nuevamente el Internet de las Cosas (Internet of Things). Este eje se tomado como orientación general de los trabajos con las siguientes líneas temá...

El reconocimiento facial de emociones básicas (RFEB) se ha estudiado en la variante conductual de la demencia frontotemporal (DFTvc) y en la demencia tipo Alzheimer(DTA), con hallazgos contradictorios, especialmente al ...

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...

Remarkable progress has been made in image recognition, primarily due to the availability of large-scale annotated datasets and deep convolutional neural networks (CNNs). CNNs enable learning data-driven, highly represen...

Subjects / keywords: Computer science; Segmentation; Artificial intelligence; Annotation; Volume (thermodynamics); Set (abstract data type); Training set; Pattern recognition (psychology); Test data; Computer vision; Physics; Quantum mechani...

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...

State-of-the-art object detection networks depend on region proposal algorithms to hypothesize object locations. Advances like SPPnet [1] and Fast R-CNN [2] have reduced the running time of these detection networks, expo...

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...

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...

Subjects / keywords: Computer science; Artificial intelligence; Convolutional neural network; Image (mathematics); Pixel; Perception; Transformation (genetics); Ground truth; Transfer (computing); Computer vision; Pattern recognition (psycho...

Subjects / keywords: Overfitting; Random forest; Classifier (UML); Computer science; Outlier; Artificial intelligence; Pattern recognition (psychology); Curse of dimensionality; Machine learning; Decision tree; Remote sensing; Data mining

IMPORTANCE: Limited information exists about the epidemiology, recognition, management, and outcomes of patients with the acute respiratory distress syndrome (ARDS). OBJECTIVES: To evaluate intensive care unit (ICU) inci...