Abdullah Sheneamer

Orcid: 0000-0002-2372-4154

According to our database1, Abdullah Sheneamer authored at least 13 papers between 2016 and 2024.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

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2020
2021
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2023
2024
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Legend:

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In proceedings 
Article 
PhD thesis 
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Links

On csauthors.net:

Bibliography

2024
Vulnerable JavaScript functions detection using stacking of convolutional neural networks.
PeerJ Comput. Sci., 2024

Detecting and forecasting cryptojacking attack trends in Internet of Things and wireless sensor networks devices.
PeerJ Comput. Sci., 2024

Enhancing Precision Agriculture and Land Cover Classification: A Self-Attention 3D Convolutional Neural Network Approach for Hyperspectral Image Analysis.
IEEE Access, 2024

Visualized Malware Images using Hybrid Ensemble Deep Transfer Learning.
Proceedings of the 7th International Conference on Information and Computer Technologies, 2024

2023
Graph-of-Code: Semantic Clone Detection Using Graph Fingerprints.
IEEE Trans. Software Eng., August, 2023

Early Predicting of Students Performance in Higher Education.
IEEE Access, 2023

2021
Multiple Similarity-based Features Blending for Detecting Code Clones using Consensus-Driven Classification.
Expert Syst. Appl., 2021

An Effective Semantic Code Clone Detection Framework Using Pairwise Feature Fusion.
IEEE Access, 2021

2020
An Automatic Advisor for Refactoring Software Clones Based on Machine Learning.
IEEE Access, 2020

2018
A detection framework for semantic code clones and obfuscated code.
Expert Syst. Appl., 2018

CCDLC Detection Framework-Combining Clustering with Deep Learning Classification for Semantic Clones.
Proceedings of the 17th IEEE International Conference on Machine Learning and Applications, 2018

2017
Schemes for Labeling Semantic Code Clones using Machine Learning.
Proceedings of the 16th IEEE International Conference on Machine Learning and Applications, 2017

2016
Semantic Clone Detection Using Machine Learning.
Proceedings of the 15th IEEE International Conference on Machine Learning and Applications, 2016


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