M. Emre Celebi Source Confirmed

Affiliation confirmed via AI analysis of OpenAlex, ORCID, and web sources.

High Impact

Professor and Chair

University of Central Arkansas

faculty

52 h-index 208 pubs 12,124 cited

Research Areas

Medical Imaging Techniques and Applications Advanced Neural Network Applications Dermatology and Skin Diseases Radiomics and Machine Learning in Medical Imaging Meta-analysis and systematic reviews Computer Graphics and Visualization Techniques Technology Adoption and User Behaviour

Links

ORCID Google Scholar Lab Website Research Group

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OverviewAI-generated summary

M. Emre Celebi's research focuses on the application of artificial intelligence, particularly deep learning techniques, to image analysis and data processing. His work includes developing and evaluating algorithms for tasks such as medical image segmentation, skin lesion detection, and face recognition. He has explored various methodologies, including deep convolutional neural networks, clustering algorithms, and hidden Markov models, often in the context of specific biomedical or image processing challenges.

Celebi has authored and co-authored numerous publications in these areas, contributing to the understanding and advancement of AI-driven image analysis. His scholarship metrics include an h-index of 52, with over 208 publications and more than 12,000 citations, indicating a significant impact in his field. He has also been recognized as a highly cited researcher.

His collaborative efforts include joint publications with researchers such as Yassine Daadaa and J.P. Maxwell from the University of Central Arkansas. Celebi maintains an active research group and lab website, reflecting his engagement in ongoing research and mentorship.

Metrics

h-index: 52
Publications: 208
Citations: 12,124

Selected Publications

Correction to: Medical Image Computing and Computer Assisted Intervention – MICCAI 2024 Workshops (2025) DOI
Color quantization using an accelerated Jancey k-means clustering algorithm (2024) DOI
Quantum Face Recognition With Multigate Quantum Convolutional Neural Network (2024) DOI
A comparative study of color quantization methods using various image quality assessment indices (2024) DOI
An ensemble-based deep learning model for detection of mutation causing cutaneous melanoma (2023) DOI
Automatic Face Recognition System Using Deep Convolutional Mixer Architecture and AdaBoost Classifier (2023) DOI
A survey on deep learning for skin lesion segmentation (2023) DOI
cq100: a high-quality image dataset for color quantization research (2023) DOI
Image analysis in advanced skin imaging technology (2023) DOI
Forty years of color quantization: a modern, algorithmic survey (2023) DOI
Guest Editorial Skin Image Analysis in the Age of Deep Learning (2023) DOI
Guest Editorial Emerging Challenges for Deep Learning (2022) DOI
Gray Wolf Optimization for Color Quantization (2022) DOI
The incremental online k-means clustering algorithm and its application to color quantization (2022) DOI
Deep Learning for Security and Privacy Preservation in IoT (2021) DOI