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convolutional-encoder-decoder

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Frontiers

AM-MTEEG: multi-task EEG classification based on impulsive associative memory

Electroencephalogram-based brain-computer interfaces (BCIs) hold promise for healthcare applications but are hindered by cross-subject variability and limited data. This article proposes a multi-task ...
Scientific Research Publishing

A Combination Method of Stacked Convolutional Auto-Encoder and Selective Kernel Attention Mechanism for Image Classification ()

1 College of Information Engineering, Xinchuang Software Industry Base, Yancheng Teachers University, Yancheng, China. 2 Yancheng Agricultural College, Yancheng, China. Convolutional auto-encoders ...
Live Science

AI 'brain decoder' can read a person's thoughts with just a quick brain scan and almost no training

It's quick and easy to access Live Science Plus, simply enter your email below. We'll send you a confirmation and sign you up for our daily newsletter, keeping you up to date with the latest science ...
IEEE

Supervised Convolutional Encoder-Decoder With Gated Linear Units for Detecting Fetal R-Peaks

Abstract: Noninvasive fetal electrocardiography (ECG) is prevalently used for monitoring fetal heartbeats during pregnancy due to its affordability, ease of use, and constant monitoring capability. A ...
Scientific Research Publishing

Chollampatt, S. and Ng, H.T. (2018) A Multilayer Convolutional Encoder-Decoder Neural Network for Grammatical Error Correction. Proceedings of the AAAI Conference on Artificial ...

ABSTRACT: With the widespread use of Chinese globally, the number of Chinese learners has been increasing, leading to various grammatical errors among beginners. Additionally, as domestic efforts to ...
Frontiers

DeepCGAN: early Alzheimer's detection with deep convolutional generative adversarial networks

Introduction: Alzheimer's disease (AD) is a neurodegenerative disorder and the most prevailing cause of dementia. AD critically disturbs the daily routine, which usually needs to be detected at its ...
IEEE

Optimizing the Hyperparameters of Fully Convolutional Encoder–Decoder Networks for SAR Image Segmentation

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 ...