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Eslam Amer
Researcher at Misr International University
Publications - 36
Citations - 548
Eslam Amer is an academic researcher from Misr International University. The author has contributed to research in topics: Computer science & Malware. The author has an hindex of 7, co-authored 26 publications receiving 153 citations. Previous affiliations of Eslam Amer include Banha University & Technical University of Ostrava.
Papers
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Journal ArticleDOI
A dynamic Windows malware detection and prediction method based on contextual understanding of API call sequence
TL;DR: The use of word embedding is introduced to understand the contextual relationship that exists between API functions in malware call sequences and a prediction methodology that predicts whether an API call sequence is malicious or not from the initial API calling functions is proposed.
Proceedings ArticleDOI
Deep Learning Algorithms for Detecting Fake News in Online Text
TL;DR: The objective is to build a classifier that can predict whether a piece of news is fake or not based only its content, thereby approaching the problem from a purely deep learning perspective by RNN technique models (vanilla, GRU and LSTMs), and to increase accuracy by applying a hybrid model between theGRU and CNN techniques on the same data set.
Journal ArticleDOI
Social Media Cyberbullying Detection using Machine Learning
TL;DR: A supervised machine learning approach for detecting and preventing cyberbullying and shows that Neural Network performs better and achieves accuracy of 92.8% and NN outperforms other classifiers of similar work on the same dataset.
Journal ArticleDOI
An Efficient Slime Mould Algorithm Combined With K-Nearest Neighbor for Medical Classification Tasks
TL;DR: In this paper, an improved version of the slime mold algorithm (SMA) hybridized with the opposition-based learning (OBL) strategy based on the k-nearest neighbor (kNN) classifier was proposed for the classification approach.
Journal ArticleDOI
Comprehensive Survey of Using Machine Learning in the COVID-19 Pandemic.
Nora El-Rashidy,Samir Abdelrazik,Tamer AbuHmed,Eslam Amer,Farman Ali,Jong Wan Hu,Shaker El-Sappagh +6 more
TL;DR: In this article, the authors survey the decisive role of AI as a technology used to fight against the COVID-19 pandemic and highlight the open research challenges that could inspire the future application of AI in COVID19.