Real-Time Turmeric Leaf Identification and Classification Using Advanced Deep Learning Models: Initiative to Smart Agriculture

Agriculture is observed to be a cornerstone of the Indian economy, constituting one of its formidable pillars. The agriculture industry contributes significantly to the GDP of the country and provides work for many rural communities. Agriculture is the most important part of everyone's life. Crops and plants play a significant role in sustaining life, and the vital task of nurturing and managing these agricultural entities is both crucial and challenging. Thus, to detect the disease in plants, the following research paper is formulated which tells whether the plant is healthy or not. The dataset consists of turmeric plant leave collected from one of the fields located in Andhra Pradesh, India. Many image classification models as well as transfer learning models are applied. A plant disease hindering normal growth constitutes a significant factor contributing to reduced agricultural yields and accompanying financial losses. Early disease identification contributes to the advancement of medicines capable of healing plant diseases. Leaf examination is one of the best techniques for detecting plant diseases. Thanks to advancements in computer vision and machine learning, computers can now recognize and understand data from digital photos. Deep Learning models CNN and transfer learning models like InceptionV3 and VGG16 are applied with and without data augmentation. The most successful model was found to be CNN with data augmentation which showed an accuracy of 90 percent, and it also predicted almost all the testing images correctly. Enhancing the model's accuracy can be achieved by augmenting the size of the dataset.