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Computer Science

D-Index
37
Citations
7237
World Ranking
10595
National Ranking
667

Overview

Stephen Marshall is affiliated with the University of Strathclyde in the United Kingdom. Their research spans multiple areas within engineering and computer science, with a particular focus on computer vision, pattern recognition, and media technology. The subfields they contribute to include artificial intelligence, industrial and manufacturing engineering, and biomedical engineering.

The scientist's work extensively covers topics such as remote-sensing image classification, advanced image fusion techniques, image and signal denoising methods, advanced image and video retrieval techniques, industrial vision systems and defect detection, advanced steganography and watermarking techniques, and geochemistry and geologic mapping.

Some of Stephen Marshall's recent papers are:

  • A framework for breast cancer classification using Multi-DCNNs, 2021, Computers in Biology and Medicine
  • Varietal Classification of Rice Seeds Using RGB and Hyperspectral Images, 2020, IEEE Access
  • Tri-CNN: A Three Branch Model for Hyperspectral Image Classification, 2023, Remote Sensing
  • A Review of Spatial Enhancement of Hyperspectral Remote Sensing Imaging Techniques, 2023, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
  • Achieving remanufacturing inspection using deep learning, 2020, Journal of remanufacturing

Frequent coauthors collaborating with Stephen Marshall include:

  • Paul Murray
  • Jinchang Ren
  • Jaime Zabalza
  • Huimin Zhao
  • Nour Aburaed

Stephen Marshall often publishes in the following venues:

  • arXiv (Cornell University)
  • Remote Sensing
  • IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
  • IEEE Access
  • Scientific Reports

In addition to journal articles and conference papers, Stephen Marshall has contributed to book publications. Notably, they have published a book titled Communications, Signal Processing, and Systems in 2022 under Springer Science+Business Media.

Best Publications

  • Activation functions: comparison of trends in practice and research for deep learning

    Chigozie Enyinna Nwankpa;Winifred Ijomah;Anthony Gachagan;Stephen Marshall

  • Breast cancer detection using deep convolutional neural networks and support vector machines

    Dina A. Ragab;Dina A. Ragab;Maha Sharkas;Stephen Marshall;Jinchang Ren

  • Novel segmented stacked autoencoder for effective dimensionality reduction and feature extraction in hyperspectral imaging

    Jaime Zabalza;Jinchang Ren;Jiangbin Zheng;Huimin Zhao

  • Novel Folded-PCA for improved feature extraction and data reduction with hyperspectral imaging and SAR in remote sensing

    Jaime Zabalza;Jinchang Ren;Mingqiang Yang;Yi Zhang

  • Convergence Criteria for Genetic Algorithms

    David Greenhalgh;Stephen Marshall

  • Novel Two-Dimensional Singular Spectrum Analysis for Effective Feature Extraction and Data Classification in Hyperspectral Imaging

    Jaime Zabalza;Jinchang Ren;Jiangbin Zheng;Junwei Han

  • A framework for breast cancer classification using Multi-DCNNs.

    Dina Ahmed Ragab;Dina Ahmed Ragab;Omneya Attallah;Maha A. Sharkas;Jinchang Ren

  • Multiresolution morphological fusion of MR and CT images of the human brain

    G.K. Matsopoulos;S. Marshall;J.N.H. Brunt

  • Unsupervised image saliency detection with Gestalt-laws guided optimization and visual attention based refinement

    Yijun Yan;Jinchang Ren;Genyun Sun;Huimin Zhao

  • Effective Denoising and Classification of Hyperspectral Images Using Curvelet Transform and Singular Spectrum Analysis

    Tong Qiao;Jinchang Ren;Zheng Wang;Jaime Zabalza

  • New methods for automatic quantification of microstructural features using digital image processing

    Andrew Campbell;Paul Murray;Evgenia Yakushina;Stephen Marshall

  • Hyperspectral imaging combined with data classification techniques as an aid for artwork authentication

    Adam Polak;Timothy Kelman;Paul Murray;Stephen Marshall

  • Singular Spectrum Analysis for Effective Feature Extraction in Hyperspectral Imaging

    Jaime Zabalza;Jinchang Ren;Zheng Wang;Stephen Marshall

  • Effective Feature Extraction and Data Reduction in Remote Sensing Using Hyperspectral Imaging [Applications Corner]

    Jianchang Ren;Jaime Zabalza;Stephen Marshall;Jiangbin Zheng

  • Tri-CNN: A Three Branch Model for Hyperspectral Image Classification

    Unknown

  • Robust PCA micro-doppler classification using SVM on embedded systems

    Jaime Zabalza;Carmine Clemente;Gaetano Di Caterina;Jinchang Ren

  • Varietal Classification of Rice Seeds Using RGB and Hyperspectral Images

    Samson Damilola Fabiyi;Hai Vu;Christos Tachtatzis;Paul Murray

  • The use of genetic algorithms in morphological filter design

    Neal R. Harvey;Stephen Marshall

  • Cognitive Fusion of Thermal and Visible Imagery for Effective Detection and Tracking of Pedestrians in Videos

    Yijun Yan;Jinchang Ren;Huimin Zhao;Genyun Sun

  • Logic models of pathway biology.

    Steven Watterson;Stephen Marshall;Peter Ghazal

  • Genetic algorithm optimization of multidimensional grayscale soft morphological filters with applications in film archive restoration

    M.S. Hamid;N.R. Harvey;S. Marshall

Frequent Co-Authors

Jinchang Ren
Jinchang Ren Robert Gordon University
Edward R. Dougherty
Edward R. Dougherty Texas A&M University
Ivan Andonovic
Ivan Andonovic University of Strathclyde
Peter Ghazal
Peter Ghazal Cardiff University
Stephen McArthur
Stephen McArthur University of Strathclyde
Junwei Han
Junwei Han Northwestern Polytechnical University
Jon Atli Benediktsson
Jon Atli Benediktsson University of Iceland
Shutao Li
Shutao Li Hunan University
Peijun Du
Peijun Du Nanjing University
Xuelong Li
Xuelong Li China Telecom (China)

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