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March 4, 2026International Journal of Signal and Imaging Systems Engineering0 citationsOpen Access

An Intelligent Cancer Image Classification Framework Using Region-Vision Transformer-based Adaptive Multiscale EfficientNetB7 with Gated Recurrent Unit Layer

VGVipul G GajjarIndian Institute of Technology GandhinagarVKV. N. KamaleshJSS Academy of Higher Education and ResearchKBKavitha Rani BalmuriKakatiya University

Key Points

  • The aim is to develop a sophisticated framework for accurate cancer image classification using advanced deep learning techniques.
  • Utilized a region-vision transformer for feature extraction.
  • Implemented multiscale EfficientNetB7 for enhanced performance.
  • Integrated a gated recurrent unit layer to improve temporal data handling.
  • Achieved higher accuracy in image classification compared to traditional methods.
  • Demonstrated improved processing speed and efficiency in cancer detection tasks.

Abstract

Inderscience is a global company, a dynamic leading independent journal publisher disseminates the latest research across the broad fields of science, engineering and technology; management, public and business administration; environment, ecological economics and sustainable development; computing, ICT and internet/web services, and related areas.

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Cite This Study

Gajjar et al. (2026) studied this question.

synapsesocial.com/papers/69a7cd7ed48f933b5eed9e04https://doi.org/10.1504/ijsise.2026.10076704
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