Forthcoming and Online First Articles

International Journal of Signal and Imaging Systems Engineering

International Journal of Signal and Imaging Systems Engineering (IJSISE)

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International Journal of Signal and Imaging Systems Engineering (One paper in press)

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  • Grape Cluster and Disease Detection with Hybrid Fuzzy Residual Maxout Network   Order a copy of this article
    by Rajkumar Bhimrao Pawar, Madhuri Rao 
    Abstract: This paper proposes a novel deep-learning method for grape cluster detection. Primarily, the grape cluster image is pre-processed using a bilateral filter to remove noise and the image is enhanced by the decorrelation stretching. Then, segmentation is performed using Mobile U-Net to segment the required regions. Later, features from the segmented images are extracted using different feature extractors. Afterwards, features fed into the Hybrid Fuzzy Residual Maxout Network (HFRMN) model for the detection of grape clusters. Here, the HFRMN model is designed by the incorporation of Deep Maxout Network (DMN), Deep Residual Network (DRN), and the Fuzzy concept. Finally, disease detection is accomplished by utilizing the proposed HFRMN. Moreover, HFRMN attained superior values of 90.0% for True Positive Rate (TPR), 91.3% for True Negative Rate (TNR), 91.4% for accuracy, 92.4% for F1-score, 71.3% for computational efficiency, 1.04% for Mean Squared Error (MSE), and 89.6% for Mean Average Precision (MAP).
    Keywords: grape cluster; bilateral filter; decorrelation stretching; Deep Maxout Network; Deep Residual Network.
    DOI: 10.1504/IJSISE.2024.10069173