Controlling crystalline material defects is crucial, as they affect properties of the material that may be detrimental or beneficial for the final performance of a device. Defect analysis on the sub-nanometer scale is enabled by high-resolution scann...
Small (Weinheim an der Bergstrasse, Germany)
May 3, 2021
Real-time field-emission scanning electron microscopy (FE-SEM) measurements and neural network analysis were successfully merged to observe the temperature-induced behavior of soft liquid microdomains in mixtures of different ionic liquids with water...
The use of deep learning models to identify lesions on cotton leaves on the basis of images of the crop in the field is proposed in this article. Cultivated in most of the world, cotton is one of the economically most important agricultural crops. It...
BACKGROUND: Less experienced clinicians sometimes make misdiagnosis of hip fractures. We developed computer-aided diagnosis (CAD) system for hip fractures on plain X-rays using a deep learning model trained on a large dataset. In this study, we exami...
Single cell RNA sequencing (scRNAseq) can be used to infer a temporal ordering of cellular states. Current methods for the inference of cellular trajectories rely on unbiased dimensionality reduction techniques. However, such biologically agnostic or...
IEEE transactions on neural networks and learning systems
May 3, 2021
Coronavirus disease (COVID-19) has been the main agenda of the whole world ever since it came into sight. X-ray imaging is a common and easily accessible tool that has great potential for COVID-19 diagnosis and prognosis. Deep learning techniques can...
IEEE transactions on neural networks and learning systems
May 3, 2021
Neurobiologists recently found the brain can use sudden emerged channels to process information. Based on this finding, we put forward a question whether we can build a computation model that is able to integrate a sudden emerged new type of perceptu...
IEEE transactions on neural networks and learning systems
May 3, 2021
This article focuses on the hybrid effects of memristor characteristics, time delay, and biochemical parameters on neural networks. First, we propose a novel neuron system with memristor and time delays in which the memristor is characterized by a sm...
IEEE transactions on neural networks and learning systems
May 3, 2021
Vision-based autonomous driving through imitation learning mimics the behavior of human drivers by mapping driver view images to driving actions. This article shows that performance can be enhanced via the use of eye gaze. Previous research has shown...
Join thousands of healthcare professionals staying informed about the latest AI breakthroughs in medicine. Get curated insights delivered to your inbox.