Recep Erol
This is a likely match — the affiliation was inferred from OpenAlex, ORCID, and web sources but has not been fully confirmed. Treat with appropriate caution.
HPC Admin and AI Facilitator
Also affiliated: Conway School of Landscape Design (2017–2020)
Formerly Arkansas Affiliated with UA Little Rock, University of Central Arkansas through 2023.
Research Areas
Biomedical Subjects
Links
Biography and Research Information
OverviewAI-generated summary
Recep Erol's research utilizes data mining and artificial intelligence algorithms to address complex problems across various domains. His work includes developing texture-based methods for quantifying skin lesion abruptness to detect malignancy and evaluating convolutional neural network performance with explainable AI. Erol has also investigated the classification capabilities of data mining clustering algorithms for remotely sensed multispectral image data and analyzed cyber influence campaigns on YouTube. His research interests extend to predicting multi-class wine grades with hierarchical support vector machines and designing logical circuits using data clustering for decision-making predictions. He has a history of 12 publications and 58 citations, with an h-index of 4. Erol collaborates with researchers from the University of Arkansas at Little Rock, including Mariofanna Milanova, Nitin Agarwal, and Thomas Marcoux, as well as Esther Mead from Southern Arkansas University.
Metrics
- h-index: 4
- Publications: 12
- Citations: 58
Positions
-
HPC Admin and AI Facilitator publications 2016–2023University of Arkansas at Little Rock Institution web page
Selected Publications
-
Convolutional Neural Network Post-Compression Evaluation with Explainable AI (2023)
-
Analyzing Cyber Influence Campaigns on YouTube Using YouTubeTracker (2021)
-
Proposing a Broader Scope of Predictive Features for Modeling Refugee Counts (2021)
-
Reliability And Chaotic Risk Modeling For Real Time Data Driven Smart Systems (2020)
-
Systematic approach for content and construct validation: Case studies for arthroscopy and laparoscopy (2020)
-
Determining Big Data Complexity Using Hierarchical Structure of Groups and Clusters in Decision Tree (2018)
-
Classification Performances Of Data Mining Clustering Algorithms For Remotely Sensed Multispectral Image Data (2018)
-
Data Mining Models for Selection of the Best Spectral Reflectance Indices in Estimation of Crop Yields and Classification of Maize Hybrid Types Using SpectroRadiometer Data (2017)
-
Multi-class wine grades predictions with hierarchical support vector machines (2017)
-
Texture based skin lesion abruptness quantification to detect malignancy (2017)
-
Logical circuit design using orientations of clusters in multivariate data for decision making predictions: A data mining and artificial intelligence algorithm approach (2016)
Collaboration Network
Top Collaborators
- Classification Performances Of Data Mining Clustering Algorithms For Remotely Sensed Multispectral Image Data
- Logical circuit design using orientations of clusters in multivariate data for decision making predictions: A data mining and artificial intelligence algorithm approach
- Determining Big Data Complexity Using Hierarchical Structure of Groups and Clusters in Decision Tree
- Data Mining Models for Selection of the Best Spectral Reflectance Indices in Estimation of Crop Yields and Classification of Maize Hybrid Types Using SpectroRadiometer Data
- Reliability And Chaotic Risk Modeling For Real Time Data Driven Smart Systems
- Systematic approach for content and construct validation: Case studies for arthroscopy and laparoscopy
- Texture based skin lesion abruptness quantification to detect malignancy
- Systematic approach for content and construct validation: Case studies for arthroscopy and laparoscopy
- Texture based skin lesion abruptness quantification to detect malignancy
- Analyzing Cyber Influence Campaigns on YouTube Using YouTubeTracker
- Proposing a Broader Scope of Predictive Features for Modeling Refugee Counts
- Texture based skin lesion abruptness quantification to detect malignancy
- Texture based skin lesion abruptness quantification to detect malignancy
- Multi-class wine grades predictions with hierarchical support vector machines
- Multi-class wine grades predictions with hierarchical support vector machines
- Multi-class wine grades predictions with hierarchical support vector machines
- Data Mining Models for Selection of the Best Spectral Reflectance Indices in Estimation of Crop Yields and Classification of Maize Hybrid Types Using SpectroRadiometer Data
- Data Mining Models for Selection of the Best Spectral Reflectance Indices in Estimation of Crop Yields and Classification of Maize Hybrid Types Using SpectroRadiometer Data
- Classification Performances Of Data Mining Clustering Algorithms For Remotely Sensed Multispectral Image Data
- Systematic approach for content and construct validation: Case studies for arthroscopy and laparoscopy
- Systematic approach for content and construct validation: Case studies for arthroscopy and laparoscopy
- Systematic approach for content and construct validation: Case studies for arthroscopy and laparoscopy
Similar Researchers
Based on overlapping research topics