Applications of Deep Learning in Agriculture

Abstract

Today's era is the era of technologies. Technologies have widely been employed in each and every field. The field of agriculture is not untouched with the technologies, and in several segments of agriculture; it has been employed at large. Deep learning techniques and its variants like convolutional neural networks (CNN), recurrent neural networks (RNN), generative adversarial network (AGN), and their various subcategories like AlexNet, ImageNet, visual geometry group (VGG), etc. have widely been employed in many sectors of agriculture in order to increase the quality and quantity of production. In this chapter, some applications of deep learning have been explored.

Topics & Concepts