Dynamic hand gesture recognition is one of the most significant tools for human-computer interaction. In order to improve the accuracy of the dynamic hand gesture recognition, in this paper, a two-layer Bidirectional Recurrent Neural Network for the ...
In today's data-driven world, the ability to process large data volumes is crucial. Key tasks, such as pattern recognition and image classification, are well suited for artificial neural networks (ANNs) inspired by the brain. Neuromorphic computing a...
Computational intelligence and neuroscience
Apr 5, 2020
SSD (Single Shot MultiBox Detector) is one of the best object detection algorithms and is able to provide high accurate object detection performance in real time. However, SSD shows relatively poor performance on small object detection because its sh...
School bullying is a serious problem among teenagers. School violence is one type of school bullying and considered to be the most harmful. As AI (Artificial Intelligence) techniques develop, there are now new methods to detect school violence. This ...
Neural networks : the official journal of the International Neural Network Society
Mar 27, 2020
Object recognition is a primary function of the human visual system. It has recently been claimed that the highly successful ability to recognise objects in a set of emergent computer vision systems-Deep Convolutional Neural Networks (DCNNs)-can form...
Neural networks : the official journal of the International Neural Network Society
Mar 26, 2020
Depth is one of the key factors behind the success of convolutional neural networks (CNNs). Since ResNet (He et al., 2016), we are able to train very deep CNNs as the gradient vanishing issue has been largely addressed by the introduction of skip con...
Neural networks : the official journal of the International Neural Network Society
Mar 25, 2020
Weight-sharing is one of the pillars behind Convolutional Neural Networks and their successes. However, in physical neural systems such as the brain, weight-sharing is implausible. This discrepancy raises the fundamental question of whether weight-sh...
OBJECTIVES: The authors applied unsupervised machine-learning techniques for integrating echocardiographic features of left ventricular (LV) structure and function into a patient similarity network that predicted major adverse cardiac event(s) (MACE)...
Neural networks : the official journal of the International Neural Network Society
Mar 14, 2020
Field classification is a new extension of traditional classification frameworks that attempts to utilize consistent information from a group of samples (termed fields). By forgoing the independent identically distributed (i.i.d.) assumption, field c...