Zahraa Said Abdallah

Orcid: 0000-0002-1291-2918

According to our database1, Zahraa Said Abdallah authored at least 29 papers between 2011 and 2024.

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

Timeline

Legend:

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PhD thesis 
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Bibliography

2024
Time-Series Classification for Dynamic Strategies in Multi-Step Forecasting.
CoRR, 2024

Investigating Brain Connectivity and Regional Statistics from EEG for Early Stage Parkinson's Classification.
Proceedings of the 34th IEEE International Workshop on Machine Learning for Signal Processing, 2024

2023
Bridging the gap between mechanistic biological models and machine learning surrogates.
PLoS Comput. Biol., 2023

Transfer Learning and Class Decomposition for Detecting the Cognitive Decline of Alzheimer Disease.
CoRR, 2023

A Time Series Approach to Parkinson's Disease Classification from EEG.
CoRR, 2023

IMG-NILM: A Deep learning NILM approach using energy heatmaps.
Proceedings of the 38th ACM/SIGAPP Symposium on Applied Computing, 2023

Chronic Care in a Life Transition: Challenges and Opportunities for Artificial Intelligence to Support Young Adults With Type 1 Diabetes Moving to University.
Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems, 2023

RED CoMETS: An Ensemble Classifier for Symbolically Represented Multivariate Time Series.
Proceedings of the Advanced Analytics and Learning on Temporal Data, 2023

2022
Temporal patterns in insulin needs for Type 1 diabetes.
CoRR, 2022

Understandable Controller Extraction from Video Observations of Swarms.
CoRR, 2022

Investigating Temporal Convolutional Neural Networks for Satellite Image Time Series Classification.
CoRR, 2022

Automatic Extraction of Understandable Controllers from Video Observations of Swarm Behaviors.
Proceedings of the Swarm Intelligence - 13th International Conference, 2022

2021
Transfer learning approach for detecting psychological distress in brexit tweets.
Proceedings of the SAC '21: The 36th ACM/SIGAPP Symposium on Applied Computing, 2021

2020
Co-eye: a multi-resolution ensemble classifier for symbolically approximated time series.
Mach. Learn., 2020

Co-eye: A Multi-resolution Symbolic Representation to TimeSeries Diversified Ensemble Classification.
CoRR, 2020

DeepStreamCE: A Streaming Approach to Concept Evolution Detection in Deep Neural Networks.
CoRR, 2020

2018
Activity Recognition with Evolving Data Streams: A Review.
ACM Comput. Surv., 2018

Effect of Hyper-Parameter Optimization on the Deep Learning Model Proposed for Distributed Attack Detection in Internet of Things Environment.
CoRR, 2018

Inferring Transportation Mode and Human Activity from Mobile Sensing in Daily Life.
Proceedings of the 15th EAI International Conference on Mobile and Ubiquitous Systems: Computing, 2018

2017
Data Preparation.
Proceedings of the Encyclopedia of Machine Learning and Data Mining, 2017

Multi-domain evaluation framework for named entity recognition tools.
Comput. Speech Lang., 2017

2016
AnyNovel: detection of novel concepts in evolving data streams.
Evol. Syst., 2016

2015
Scalable Energy-Efficient Distributed Data Analytics for Crowdsensing Applications in Mobile Environments.
IEEE Trans. Comput. Soc. Syst., 2015

Adaptive mobile activity recognition system with evolving data streams.
Neurocomputing, 2015

2014
CARDAP: A Scalable Energy-Efficient Context Aware Distributed Mobile Data Analytics Platform for the Fog.
Proceedings of the Advances in Databases and Information Systems, 2014

2012
Where Have You Been? Using Location Clustering and Context Awareness to Understand Places of Interest.
Proceedings of the Internet of Things, Smart Spaces, and Next Generation Networking, 2012

StreamAR: Incremental and Active Learning with Evolving Sensory Data for Activity Recognition.
Proceedings of the IEEE 24th International Conference on Tools with Artificial Intelligence, 2012

CBARS: Cluster Based Classification for Activity Recognition Systems.
Proceedings of the Advanced Machine Learning Technologies and Applications, 2012

2011
KB-CB-N classification: Towards unsupervised approach for supervised learning.
Proceedings of the IEEE Symposium on Computational Intelligence and Data Mining, 2011


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