Detection of Fungal Infections in Gloriosa Superba Plant Using the Convolution Neural Network Model

Table 1

Algorithm for the proposed work.

---

(i) Acquire the time image of Gloriosa superba plant

(ii) Contains both healthy and fungal-affected leaves

(iii) Data augmentation to extend and improve the dataset

(iv) Preprocessing dataset by standardization and normalization to rescale the original image

(v) For extracting the fungal spotted area by using scale-invariant feature transform

(vi) Assign the classes to the label

(vii) Categorize the data among training and testing dataset selecting from the class label.

(viii) Particle swarm optimization to hyperparameter optimization CNN classifier

(ix) Train the CNN model with help of training image

(x) Test the CNN model with help of testing image

(xi) Classify the input test images as healthy or fungal-affected class

(xii) Validate the performance of proposed model

(xiii) Compare the validation results with existing models

---