European Journal of Molecular & Clinical Medicine

Abstract

With the technological advancements in the field of Computer Vision along with Machine learning, agricultural automation has an important role for small fields to achieve high efficiency and precision at low cost. Combined with deep learning techniques, every aspect of agricultural production and monitoring based on large datasets promotes more economic and robust performance for the production and development of agricultural automation systems in a more intelligent manner. This paper intends to focus on the applications of image processing techniques in agriculture, plant and fruit detection, weed detection using Multispectral imaging technique alon with Backpropagation classifiers to improve the performance.