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This repository contains the implementation, benchmarks, and supporting tools for my MSc dissertation project: Self-learning Variational Autoencoder for EEG Artifact Removal (Key code only). Benchmark ...

PROGRAMMING ALERT: Watch author Jason Chaffetz discuss this topic and more on Fox News Channel's "Hannity" at 9 pm ET. Imagine a world where every text you send, every purchase you make, and every ...

Researchers have developed a deep learning model called LSTM-SAM that predicts extreme water levels from tropical cyclones more efficiently and accurately, especially in data-scarce coastal regions, ...

A few years back, one of us sat in a school district meeting where administrators and educators talked about the latest student achievement results. The news was not good. Students’ test scores hadn’t ...

Objective: To explore the value of combined radiomics and deep learning models using different machine learning algorithms based on mammography (MG) and magnetic resonance imaging (MRI) for predicting ...

cDepartment of Genetics, Icahn School of Medicine at Mount Sinai, New York, NY, USA dDivision of Data Driven and Digital Medicine (D3M), Department of Medicine, Icahn School of Medicine at Mount Sinai ...

Abstract: In this paper, we propose a new deep-learningbased framework for the automatic analysis of microorganism images in MATLAB. In fact, this is an effort to improve the accuracy and efficiency ...

Fractures play a crucial role in tight sandstone gas reservoirs with low permeability and low effective porosity. If open, they not only significantly increase the permeability of the reservoir but ...