ABSTRACT: Convolutional auto-encoders have shown their remarkable performance in stacking deep convolutional neural networks for classifying image data during the past several years. However, they are ...

Abstract: Fully convolutional encoder-decoder networks have been developed for the segmentation of sensing synthetic aperture radar (SAR) images. A recent one called the multiscaled attention U-net ...

About 350 million years ago, our planet witnessed the evolution of the first flying creatures. They are still around, and some of them continue to annoy us with their buzzing. While scientists have ...

State Key Laboratory of Physical Chemistry of Solid Surfaces, Collaborative Innovation Center of Chemistry for Energy Materials (iChEM), College of Chemistry and Chemical Engineering, Xiamen ...

Abstract: Deep networks have achieved excellent performance in learning representation from visual data. However, the supervised deep models like convolutional neural network require large quantities ...

Civil aviation is constantly striving to improve flight safety. To change the accident-prone nature of Chinese civil aviation and improve flight safety, the Civil Aviation Administration of China ...

A new publication from Opto-Electronic Advances, 10.29026/oea.2023.220148 discusses the direct field-to-pattern monolithic design of holographic metasurface via residual encoder-decoder convolutional ...

In terms of seizure prediction, how to fully mine relational data information among multiple channels of epileptic EEG? This is a scientific research subject worthy of further exploration. Recently, ...

Like other experimental techniques, X-ray photon correlation spectroscopy is subject to various kinds of noise. Random and correlated fluctuations and heterogeneities can be present in a two-time ...

In line with recent advances in neural drug design and sensitivity prediction, we propose a novel architecture for interpretable prediction of anticancer compound sensitivity using a multimodal ...