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Khalid M. Hosny

Khalid M. Hosny

D-Index & Metrics

Computer Science

D-Index
39
Citations
5710
World Ranking
9841
National Ranking
10

Research.com Recognitions

  • 2010 - ACM Senior Member

Overview

Khalid M. Hosny is affiliated with Zagazig University in Egypt and has contributed extensively to research in computer science, particularly in computer vision and related subfields. Their work spans numerous areas including artificial intelligence, media technology, computer networks and communications, and electrical and electronic engineering.

The scientist's research topics include:

  • Chaos-based Image/Signal Encryption
  • Advanced Steganography and Watermarking Techniques
  • Digital Media Forensic Detection
  • Image Retrieval and Classification Techniques
  • Advanced Image and Video Retrieval Techniques
  • Image Processing Techniques and Applications
  • AI in cancer detection

With a publication record of 289 papers in computer science, Khalid M. Hosny has focused significantly on computer vision and pattern recognition, contributing to 196 papers in this subfield. Other notable subfields of study include artificial intelligence with 49 publications, media technology with 20, and 17 publications each in computer networks and communications as well as electrical and electronic engineering.

Frequent coauthors collaborating with the scientist include:

  • Mohamed Darwish
  • Hanaa M. Hamza
  • Mostafa M. Fouda
  • Nabil A. Lashin
  • Doaa Sami Khafaga

Khalid M. Hosny's recent publications encompass multiple studies primarily related to machine learning applications in medical imaging and image classification:

  • Classification of Skin Lesions into Seven Classes Using Transfer Learning with AlexNet, 2020, Journal of Digital Imaging
  • Machine Learning and Deep Learning Methods for Skin Lesion Classification and Diagnosis: A Systematic Review, 2021, Diagnostics
  • Skin Lesions Classification Into Eight Classes for ISIC 2019 Using Deep Convolutional Neural Network and Transfer Learning, 2020, IEEE Access
  • New machine learning method for image-based diagnosis of COVID-19, 2020, PLoS ONE
  • A New Image Encryption Algorithm for Grey and Color Medical Images, 2021, IEEE Access

Publications have appeared in journals and venues where the scientist has been a frequent contributor, including:

  • IEEE Access
  • Multimedia Tools and Applications
  • Scientific Reports
  • Alexandria Engineering Journal
  • Neural Computing and Applications

Khalid M. Hosny also has authored books published by Springer Nature, such as:

  • Multimedia Security Using Chaotic Maps: Principles and Methodologies, 2020
  • Recent Advances in Computer Vision Applications Using Parallel Processing, 2023

Recognition includes the ACM Senior Member award received in 2010.

Best Publications

  • New machine learning method for image-based diagnosis of COVID-19.

    Mohamed Abd Elaziz;Mohamed Abd Elaziz;Khalid M. Hosny;Ahmad Salah;Mohamed M. Darwish

  • Classification of skin lesions using transfer learning and augmentation with Alex-net

    Khalid M. Hosny;Mohamed A. Kassem;Mohamed M. Foaud

  • Skin Lesions Classification Into Eight Classes for ISIC 2019 Using Deep Convolutional Neural Network and Transfer Learning

    Mohamed A. Kassem;Khalid M. Hosny;Mohamed M. Fouad

  • Skin Cancer Classification using Deep Learning and Transfer Learning

    Khalid M. Hosny;Mohamed A. Kassem;Mohamed M. Foaud

  • A New Image Encryption Algorithm for Grey and Color Medical Images

    Sara T. Kamal;Khalid M. Hosny;Taha M. Elgindy;Mohamed M. Darwish

  • Machine Learning and Deep Learning Methods for Skin Lesion Classification and Diagnosis: A Systematic Review

    Mohamed A. Kassem;Khalid M. Hosny;Robertas Damaševičius;Mohamed Meselhy Eltoukhy

  • Classification of Skin Lesions into Seven Classes Using Transfer Learning with AlexNet

    Khalid M. Hosny;Mohamed A. Kassem;Mohamed M. Fouad

  • New Image Encryption Algorithm Using Hyperchaotic System and Fibonacci Q-Matrix

    Khalid M. Hosny;Sara T. Kamal;Mohamed M. Darwish;George A. Papakostas

  • A color image encryption technique using block scrambling and chaos

    Khalid M. Hosny;Sara T. Kamal;Mohamed M. Darwish

  • Exact Legendre moment computation for gray level images

    Khalid M. Hosny

  • Image representation using accurate orthogonal Gegenbauer moments

    Khalid M. Hosny

  • Fast computation of accurate Zernike moments

    Khalid M. Hosny;Khalid M. Hosny

  • Robust color image watermarking using invariant quaternion Legendre-Fourier moments

    Khalid M. Hosny;Mohamed M. Darwish

  • Skin melanoma classification using ROI and data augmentation with deep convolutional neural networks

    Khalid M. Hosny;Mohamed A. Kassem;Mohamed M. Foaud

  • Exact and fast computation of geometric moments for gray level images

    Khalid M. Hosny

  • New fractional-order Legendre-Fourier moments for pattern recognition applications

    Khalid M Hosny;Mohamed M Darwish;Tarek Aboelenen;Tarek Aboelenen

  • New set of multi-channel orthogonal moments for color image representation and recognition

    Khalid M. Hosny;Mohamed M. Darwish

  • Resilient Color Image Watermarking Using Accurate Quaternion Radial Substituted Chebyshev Moments

    Khalid M. Hosny;Mohamed M. Darwish

  • New geometrically invariant multiple zero-watermarking algorithm for color medical images

    Khalid M. Hosny;Mohamed M. Darwish

  • Parallel Multi-Core CPU and GPU for Fast and Robust Medical Image Watermarking

    Khalid M. Hosny;Mohamed M. Darwish;Kenli Li;Ahmad Salah

  • Robust Color Images Watermarking Using New Fractional-Order Exponent Moments

    Khalid M. Hosny;Mohamed M. Darwish;Mostafa M. Fouda

Frequent Co-Authors

Mohamed Abd Elaziz
Mohamed Abd Elaziz Ajman University of Science and Technology
Kenli Li
Kenli Li Hunan University
Mohamed M. F. Darwish
Mohamed M. F. Darwish Benha University
Mohamed Elhoseny
Mohamed Elhoseny University of Sharjah
Dimitrios E. Koulouriotis
Dimitrios E. Koulouriotis National Technical University of Athens
Songfeng Lu
Songfeng Lu Huazhong University of Science and Technology

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