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Channel-spatial attention network for fewshot classification.

PloS one
Learning a powerful representation for a class with few labeled samples is a challenging problem. Although some state-of-the-art few-shot learning algorithms perform well based on meta-learning, they only focus on novel network architecture and fail ...

An attention-based deep learning model for clinical named entity recognition of Chinese electronic medical records.

BMC medical informatics and decision making
BACKGROUND: Clinical named entity recognition (CNER) is important for medical information mining and establishment of high-quality knowledge map. Due to the different text features from natural language and a large number of professional and uncommon...

Simultaneously learning affinity matrix and data representations for machine fault diagnosis.

Neural networks : the official journal of the International Neural Network Society
Recently, preserving geometry information of data while learning representations have attracted increasing attention in intelligent machine fault diagnosis. Existing geometry preserving methods require to predefine the similarities between data point...

The Effects of Population Tuning and Trial-by-Trial Variability on Information Encoding and Behavior.

The Journal of neuroscience : the official journal of the Society for Neuroscience
Identifying the features of population responses that are relevant to the amount of information encoded by neuronal populations is a crucial step toward understanding population coding. Statistical features, such as tuning properties, individual and ...

Being watched over by a conversation robot may enhance safety in simulated driving.

Journal of safety research
INTRODUCTION: In an aging society that is more and more information-oriented, being able to replace human passengers' protective effects on vehicle drivers with those of social robots is both essential and promising. However, the effects of a social ...

Computational Approaches to Comics Analysis.

Topics in cognitive science
Comics are complex documents whose reception engages cognitive processes such as scene perception, language processing, and narrative understanding. Possibly because of their complexity, they have rarely been studied in cognitive science. Modeling th...

Convolutional neural networks for decoding of covert attention focus and saliency maps for EEG feature visualization.

Journal of neural engineering
OBJECTIVE: Convolutional neural networks (CNNs) have proven successful as function approximators and have therefore been used for classification problems including electroencephalography (EEG) signal decoding for brain-computer interfaces (BCI). Arti...

Learning Cascade Attention for fine-grained image classification.

Neural networks : the official journal of the International Neural Network Society
Fine-grained image classification is a challenging task due to the large inter-class difference and small intra-class difference. In this paper, we propose a novel Cascade Attention Model using the Deep Convolutional Neural Network to address this pr...

Effects of robotic neurorehabilitation through lokomat plus virtual reality on cognitive function in patients with traumatic brain injury: A retrospective case-control study.

The International journal of neuroscience
Traumatic brain injury (TBI) is a clinical condition characterized by damage due to a mechanical physical event, which has a devastating impact on both the patient and his/her family. The purpose of this study is to evaluate the effects of robotic n...

A Dual-Modal Attention-Enhanced Deep Learning Network for Quantification of Parkinson's Disease Characteristics.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
It is well known that most patients with Parkinson's disease (PD) have different degree of movement disorders, such as shuffling, festination and akinetic episodes, which could degenerate the life quality of PD patients. Therefore, it is very useful ...