Spinach Classification and Its Health Benefits Suggestion using Deep learning
G. Kirubasri, S. Sreesubha, G. Vidyasree, S. Anitha Elavarasi, Aanandha Saravanan K · 2024
Spinach is a popular green leafy vegetable known for its numerous health benefits. Accurate classification of spinach varieties is critical to ensure consistent quality and nutritional value. In recent years, deep learning techniques have shown remarkable success in classification. The proposed Deep Learning based Spinach Classification and Health benefit suggestion System (DL-SCHS) uses pre-trained VGG16 architecture for classification. The dataset of 2,500 images of 25 different spinach varieties, with each variety containing 100 images are used for training DL-SCHS. Our proposed system consists of three stages includes Pre-processing of the data, Training of the model, and Evaluation. During pre-processing, images are resized into 224 x 224 pixels and random transformations are applied for image augmentation. Canny filter is used for performing feature extraction. Training of the VGG16 model on the pre-processed data is implemented using the categorical cross-entropy loss function and the Adam optimizer. The experimental results showed that the VGG16 model achieved a higher accuracy of 94% on the testing set.