Forthcoming Articles

International Journal of Innovative Computing and Applications

International Journal of Innovative Computing and Applications (IJICA)

Forthcoming articles have been peer-reviewed and accepted for publication but are pending final changes, are not yet published and may not appear here in their final order of publication until they are assigned to issues. Therefore, the content conforms to our standards but the presentation (e.g. typesetting and proof-reading) is not necessarily up to the Inderscience standard. Additionally, titles, authors, abstracts and keywords may change before publication. Articles will not be published until the final proofs are validated by their authors.

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International Journal of Innovative Computing and Applications (One paper in press)

Regular Issues

  • Comprehensive Analytical Research on Highly Similar Immunoassay Data based on ResNet and Convolutional Neural Networks   Order a copy of this article
    by Jianzhang Li, Zixuan Zhao 
    Abstract: Image recognition has become essential in biomedical research, particularly for disease diagnosis and biomarker detection. While Convolutional Neural Networks (CNNs) have achieved success in image tasks, their performance declines with complex, noisy biomedical data. This study compares ResNet and traditional CNNs in antibody immune detection. ResNet's residual connections effectively address vanishing gradients in deep networks, improving training stability and maintaining consistent performance. Its superior feature extraction captures subtle image variations, achieving high classification accuracy under noisy conditions. ResNet also shows strong robustness across different network depths. Experimental results demonstrate that ResNet outperforms conventional CNNs in detection accuracy, especially with specialised biomedical images, and holds significant promise for clinical application. The findings indicate that ResNet is a more reliable and accurate framework for biomedical image recognition, especially in complex and high-noise environments, offering advantages in both research and practical diagnostic contexts.
    Keywords: ResNet; CNN; immunoassay data; recognition.
    DOI: 10.1504/IJICA.2025.10073443
     

 

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