Abstract:
Farming inputs are very vital, yet they are not always available to farmers. The goal of this
research was to construct an intelligence system utilizing the recognition of eggplant
diseases utilizing picture treatment techniques in order to educate farmers about eggplant
sickness. The lack of data for both disorders encouraged us to develop a standard dataset
for two prominent diseases in the laboratory. Pre-trained Eggplant-disease classification
Visual Geometry Group 16 (VGG16) resnet50 and inceptionV3 architectures are used in
our work. Further, VGG16 was utilized as the 8th convolution layer feature extractor and
these features were used to graduate illnesses. An equivalent or in some cases a greater
accuracy was shown in the analysis. There have been proposed possible causes for
variations in interclass precision and future direction. Our highest accuracy is achieved by
VGG16 the accuracy rate is 99.55%.
