M. Emre Celebi
Affiliation confirmed via AI analysis of OpenAlex, ORCID, and web sources.
Professor and Chair
Also affiliated: Louisiana State University (2009–2014); Georgia Institute of Technology (2014); University of Bridgeport (2007); Manisa Celal Bayar University (2009); The University of Texas at Arlington (2004–2008); Missouri University of Science and Technology (2007–2009); Bartin University (2024); Louisiana State University in Shreveport (2007–2016); Skin Cancer Foundation (2009); Southern University at Shreveport (2008); Stamford Hospital (2009); Islamic University (2024); Conway School of Landscape Design (2016–2025)
Faculty Researcher
Research Areas
Biomedical Subjects
Biography and Research Information
OverviewAI-generated summary
M. Emre Celebi's research program focuses on the application of artificial intelligence and machine learning techniques to biomedical data, particularly in the area of dermatology and skin lesion analysis. He has investigated the use of deep learning for skin lesion segmentation and developed methods for melanoma detection in microscopic images. His work also includes advancements in data preprocessing for biomedical data fusion and the evaluation of image-based artificial intelligence reports in dermatology.
Celebi's research extends to broader areas of computer vision and image processing, including automatic face recognition systems using deep convolutional architectures and AdaBoost classifiers. He has also contributed to the field of color quantization, publishing surveys on modern algorithmic approaches and comparative studies of different methods. His scholarship metrics include an h-index of 52, with over 200 publications and more than 12,000 citations, designating him as a highly cited researcher.
He leads a research group and maintains an active lab website. Key collaborators include Yassine Daadaa and J.P. Maxwell, both from the University of Central Arkansas.
Metrics
- h-index: 52
- Publications: 206
- Citations: 12,162
Selected Publications
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Incubating Artificial Intelligence (AI) Initiatives and Careers in Dermatology (2026)
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Grey wolf optimization for color quantization (2026)
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Correction to: Medical Image Computing and Computer Assisted Intervention – MICCAI 2024 Workshops (2025)
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An Innovative Attention-based Triplet Deep Hashing Approach to Retrieve Histopathology Images (2024)
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Color quantization using an accelerated Jancey k-means clustering algorithm (2024)
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Quantum Face Recognition With Multigate Quantum Convolutional Neural Network (2024)
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A comparative study of color quantization methods using various image quality assessment indices (2024)
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An ensemble-based deep learning model for detection of mutation causing cutaneous melanoma (2023)
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Automatic Face Recognition System Using Deep Convolutional Mixer Architecture and AdaBoost Classifier (2023)
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A survey on deep learning for skin lesion segmentation (2023)
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cq100: a high-quality image dataset for color quantization research (2023)
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Image analysis in advanced skin imaging technology (2023)
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Forty years of color quantization: a modern, algorithmic survey (2023)
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Guest Editorial Skin Image Analysis in the Age of Deep Learning (2023)
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Guest Editorial Emerging Challenges for Deep Learning (2022)
Collaboration Network
Top Collaborators
- A survey on deep learning for skin lesion segmentation
- Checklist for Evaluation of Image-Based Artificial Intelligence Reports in Dermatology
- Guest Editorial Skin Image Analysis in the Age of Deep Learning
- A comparative study of color quantization methods using various image quality assessment indices
- cq100: a high-quality image dataset for color quantization research
- Gray Wolf Optimization for Color Quantization
- Image synthesis with adversarial networks: A comprehensive survey and case studies
- Advances in domain adaptation for computer vision
- Image synthesis with adversarial networks: A comprehensive survey and case studies
- Advances in domain adaptation for computer vision
- Skin Melanoma Detection in Microscopic Images Using HMM-Based Asymmetric Analysis and Expectation Maximization
- An Innovative Attention-based Triplet Deep Hashing Approach to Retrieve Histopathology Images
- Checklist for Evaluation of Image-Based Artificial Intelligence Reports in Dermatology
- Guest Editorial Skin Image Analysis in the Age of Deep Learning
- Checklist for Evaluation of Image-Based Artificial Intelligence Reports in Dermatology
- Guest Editorial Skin Image Analysis in the Age of Deep Learning
- Checklist for Evaluation of Image-Based Artificial Intelligence Reports in Dermatology
- Incubating Artificial Intelligence (AI) Initiatives and Careers in Dermatology
- Checklist for Evaluation of Image-Based Artificial Intelligence Reports in Dermatology
- Incubating Artificial Intelligence (AI) Initiatives and Careers in Dermatology
- Checklist for Evaluation of Image-Based Artificial Intelligence Reports in Dermatology
- Guest Editorial Skin Image Analysis in the Age of Deep Learning
- Automatic Face Recognition System Using Deep Convolutional Mixer Architecture and AdaBoost Classifier
- An ensemble-based deep learning model for detection of mutation causing cutaneous melanoma
- Automatic Face Recognition System Using Deep Convolutional Mixer Architecture and AdaBoost Classifier
- An ensemble-based deep learning model for detection of mutation causing cutaneous melanoma
- Image synthesis with adversarial networks: A comprehensive survey and case studies
- Image synthesis with adversarial networks: A comprehensive survey and case studies
- Image synthesis with adversarial networks: A comprehensive survey and case studies
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