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Image Search Results
Journal: Procedia Computer Science
Article Title: Grape Leaf Disease Diagnosis System Using Fused Deep Learning Features Based System
doi: 10.1016/j.procs.2024.04.037
Figure Lengend Snippet: Fig. 2. The methods recommended processing flow Third, combine the deep characteristics that were retrieved using either concatenation of canonical correlation analyses, CCA sum, or straight concatenation. The deep-fused characteristics should then be fed into a fine-trained SVM classifier, which may subsequently output the various diseases present in the input grape leaves. A multi-class SVM classifier may be trained using the “appropriate class output codes for error correction. “MATLAB 2020b's (fitcecoc) function is used using its built-in parameterization. The "fitcecoc" function uses a model of binary SVM with a one-to-one encoding architecture to boost the classifier's categorization effectiveness. Table 2 displays some of the default settings used throughout the training phase. Table 2 Several common training-stage parameters. Component Rate
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