The American journal of gastroenterology
Mar 1, 2019
Technological advances in artificial intelligence (AI) represent an enticing opportunity to benefit gastroenterological practice. Moreover, AI, through machine or deep learning, permits the ability to develop predictive models from large datasets. Po...
The Game of Dice Task (GDT; Brand et al. in Neuropsychology 19:267-277, 2005a; Psychiatry Res 133:91-99, 2005b) measures decision-making under objective risk conditions. Although disadvantageous decision-making has been shown in individuals with subs...
Nan fang yi ke da xue xue bao = Journal of Southern Medical University
Feb 28, 2019
We propose a novel palm-vein recognition model based on the end-to-end convolutional neural network. In this model, the convolutional layer and the pooling layer were alternately connected to extract the image features, and the categorical attribute ...
Mathematical biosciences and engineering : MBE
Feb 20, 2019
Deep learning tools have been a new way for privacy attacks on remote sensing images. However, since labeled data of privacy objects in remote sensing images are less, the samples for training are commonly small. Besides, traditional deep neural netw...
Though the advent of long-read sequencing technologies has led to a leap in contiguity of de novo genome assemblies, current reference genomes of higher organisms still do not provide unbroken sequences of complete chromosomes. Despite reads in exces...
Mathematical biosciences and engineering : MBE
Feb 18, 2019
In this paper, we consider neural networks in the case when the neurons are subject to a certain impulsive state displacement at fixed moments and the duration of this displacement is not negligible small (these are known as non-instantaneous impulse...
Hardware artificial neural network (ANN) systems with high density synapse array devices can perform massive parallel computing for pattern recognition with low power consumption. To implement a neuromorphic system with on-chip training capability, w...
Memristors have been compared to neurons and synapses, suggesting they would be good for neuromorphic computing. A change in voltage across a memristor causes a current spike which imparts a short-term memory to a memristor, allowing for through-time...
Resistive switching random-access memory (ReRAM) is a two-terminal device based on ion migration to induce resistance switching between a high resistance state (HRS) and a low resistance state (LRS). ReRAM is considered one of the most promising tech...
Memristive devices represent a promising technology for building neuromorphic electronic systems. In addition to their compactness and non-volatility, they are characterized by their computationally relevant physical properties, such as their state-d...
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