Remote Sensing Image Category Classification Using Deep Learning

ABSTRACT The remote sensing Image Classification plays a major role in real-time applications. Deep Learning plays a vital role in different fields such as Natural language Processing, Computer Vision medical fields, and Image classification. Compared to the machine learning algorithms, deep networks provide higher accuracy, strong ability to learn data extraction. Geographical satellite images that are utilized for the investigation of environmental and geological fields are acquired through remote sensing techniques. The rough pictures accumulated from the satellites are not suitable for authentic assessment and exact report plans, so crude pictures experience the customary picture grouping systems, for example, information preprocessing, division, information include extraction and characterization. The old picture characterization techniques have spatial and otherworldly goals issues. The most recent picture order strategy specifically profound CNN systems. The CNN algorithm classifies the images into various categories namely water, land, forest, agricultural area. Keywords: Image Classification, Enhancement, Remote Sensing, Resolution, Satellite Sensors, deep learning, Convolution neural networks.