A Novel Convolutional Neural Networks Based Spinach Classification and Recognition System

In the present scenario, Deep Learning (DL) is one of most popular research algorithms to increase accuracy data analysis. Due intra-class differences and inter-class variation, image classification difficult jobs in processing. Plant or spinach recognition deep learning applications through its leaf. Spinach more critical for human skin, bone, hair, etc. It provides vitamins, iron, minerals, protein. beneficial diet readily available people's surroundings. Many researchers have proposed various machine classify plant images accurately recent years. This paper presents a novel Convolutional Neural Network (CNN) recognize accurately. The CNN architecture classifies category, namely Amaranth leaves, Black nightshade, Curry Drumstick leaves. dataset contains 400 with four classes, each type has 100 images. were captured from agricultural land located at Thirumanur, Salem district, Tamil Nadu. achieves 97.5% accuracy. addition, performance compared Support Vector Machine (SVM), Random Forest, Visual Geometry Group 16 (VGG16), 19 (VGG19) Residual 50 (ResNet50). superior than other models, SVM, VGG16, VGG19 ResNet50.