Automatic Cashew Detection System Using Deep Learning

Perennial cashew trees, often colloquially referred to as the "Poor man's crop," hold a significant place in global agriculture. India stands out as one of the leading cultivators of cashew, contributing substantially to the world's cashew production. A notable challenge in cashew harvesting lies in the labour-intensive process of manually picking fallen cashew fruits from the ground, a physically taxing task known for straining the back and neck. To address this issue, a proposed solution employs an innovative deep learning-based methodology. The approach focuses on automating the cashew fruit picking process using Convolutional Neural Networks (CNN). This advanced technology aims to discern cashew fruits accurately from images depicting them on the ground. The implementation of CNN brings efficiency to this task, alleviating the physical burden on labourers and revolutionizing the traditional harvesting method. By integrating cutting-edge technology into the agricultural landscape, this approach not only streamlines operations but also exemplifies the potential for transformative advancements in addressing challenges associated with labour-intensive practices in cashew cultivation.