Results 41 to 50 of about 1,966,391 (262)
, 2016 In this paper, we propose a bidimensional attention based recursive autoencoder (BattRAE) to integrate clues and sourcetarget interactions at multiple levels of granularity into bilingual phrase representations.
Su, Jinsong, Xiong, Deyi, Zhang, Biao
core +1 more source
Discriminating different classes of biological networks by analyzing the graphs spectra distribution [PDF]
, 2012 The brain's structural and functional systems, protein-protein interaction, and gene networks are examples of biological systems that share some features of complex networks, such as highly connected nodes, modularity, and small-world topology.
Andre ́ Fujita +5 more
core +3 more sources
Comparing Self-Report vs. Performance Measures of Attentional Control and Efficiency
NeuroSciBackground: The Attention Control Scale (ATTC) is a widely used self-report measure of attentional control capacities. However, research questions whether it accurately substitutes for objective attention control tasks.
Mohammad Ahsan Khodami +4 more
doaj +1 more source
Сибирский научный медицинский журнал, 2019 The cognitive decline in cardiac patients may be associated with insufficiency of the cerebral blood supply and inhibition of the brain functional state that manifested as a slowing of spontaneous EEG activity.
I. V. Tarasova +2 more
doaj +1 more source
Sequence-to-Sequence Models Can Directly Translate Foreign Speech
, 2017 We present a recurrent encoder-decoder deep neural network architecture that directly translates speech in one language into text in another. The model does not explicitly transcribe the speech into text in the source language, nor does it require ...
Chen, Zhifeng +4 more
core +1 more source
Modulation of Repeated Anodal HD-tDCS on Attention in Healthy Young Adults
Frontiers in Psychology, 2020 High-definition transcranial direct current stimulation (HD-tDCS) is a valid brain stimulation technology to optimize cognitive function. Recent evidence indicates that single anodal tDCS session enhances attention; however, the variation in attention ...
Hongliang Lu +6 more
doaj +1 more source
Assessing knee OA severity with CNN attention-based end-to-end architectures [PDF]
, 2019 This work proposes a novel end-to-end convolutional neural network (CNN) architecture to automatically quantify the severity of knee osteoarthritis (OA) using X-Ray images, which incorporates trainable attention modules acting as unsupervised fine ...
Antony, Joseph +4 more
core
A Context-aware Attention Network for Interactive Question Answering
, 2017 Neural network based sequence-to-sequence models in an encoder-decoder framework have been successfully applied to solve Question Answering (QA) problems, predicting answers from statements and questions.
Ge, Yong +3 more
core +1 more source
, 2020 Semantic segmentation models based on convolutional neural networks (CNNs) have gained much attention in relation to remote sensing and have achieved remarkable performance for the extraction of buildings from high-resolution aerial images.
Choi, Jihwan P. +5 more
core +1 more source
Pediatric Blood &Cancer, EarlyView.ABSTRACT Pediatric gastroenteropancreatic neuroendocrine neoplasms (GEP‐NENs) are extremely rare and clinically heterogeneous. Management has largely been extrapolated from adult practice. This European Standard Clinical Practice Guideline (ESCP), developed by the EXPeRT network in collaboration with adult NEN experts, provides (adult) evidence ...
Michaela Kuhlen +23 more
wiley +1 more source