activity
20152021
most citedMCUa: Multi-level Context and Uncertainty aware Dynamic Deep Ensemble for Breast Cancer Histology Image Classification

76 citations · 83 across the 7 of their papers we have counts for

collaborators
Showing cs.LGShow all

8 papers · 1 filter

cs.LG2020

Co-eye: A Multi-resolution Symbolic Representation to TimeSeries Diversified Ensemble Classification

Zahraa S. Abdallah, Mohamed Medhat Gaber

Time series classification (TSC) is a challenging task that attracted many researchers in the last few years. One main challenge in TSC is the diversity of domains where time serie…

cs.LG20201 cited

DeepStreamCE: A Streaming Approach to Concept Evolution Detection in Deep Neural Networks

Lorraine Chambers, Mohamed Medhat Gaber, Zahraa S. Abdallah

Deep neural networks have experimentally demonstrated superior performance over other machine learning approaches in decision-making predictions. However, one major concern is the…

cs.LG2020

Prune2Edge: A Multi-Phase Pruning Pipelines to Deep Ensemble Learning in IIoT

Besher Alhalabi, Mohamed Gaber, Shadi Basurra

Most recently, with the proliferation of IoT devices, computational nodes in manufacturing systems IIoT(Industrial-Internet-of-things) and the lunch of 5G networks, there will be m…

cs.LG2019

A Heuristically Modified FP-Tree for Ontology Learning with Applications in Education

Safwan Shatnawi, Mohamed Medhat Gaber, Mihaela Cocea

We propose a heuristically modified FP-Tree for ontology learning from text. Unlike previous research, for concept extraction, we use a regular expression parser approach widely ad…

cs.LG2019

EnSyth: A Pruning Approach to Synthesis of Deep Learning Ensembles

Besher Alhalabi, Mohamed Medhat Gaber, Shadi Basurra

Deep neural networks have achieved state-of-art performance in many domains including computer vision, natural language processing and self-driving cars. However, they are very com…

cs.LG2018

AnyThreat: An Opportunistic Knowledge Discovery Approach to Insider Threat Detection

Diana Haidar, Mohamed Medhat Gaber, Yevgeniya Kovalchuk

Insider threat detection is getting an increased concern from academia, industry, and governments due to the growing number of malicious insider incidents. The existing approaches…