PD36-C is a 1.25 million parameter CNN achieving 99.53% average test accuracy on 38 plant disease classes from the New Plant Diseases Dataset, with a Qt-based app enabling edge deployment.
Deep Transfer Learning Technique for Multimodal Disease Classification in Plant Images - Balaji - 2023 - Contrast Media & Molecular Imaging - Wiley Online Library
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A Compact and Efficient 1.251 Million Parameter Machine Learning CNN Model PD36-C for Plant Disease Detection: A Case Study
PD36-C is a 1.25 million parameter CNN achieving 99.53% average test accuracy on 38 plant disease classes from the New Plant Diseases Dataset, with a Qt-based app enabling edge deployment.