Title : DETECTION OF LAND COVER CLASSIFICATION USING ARTIFICIAL NEURAL NETWORK (ANN)
Author : Dr. K. Amit Bindaj, Mr.T. Gangadhar, Ms.S.Madhavi
Abstract :
- The land cover refers to the surface of the Earth, whereas land use describes the activities that take place on the land. Land cover may be anything from water to snow to grassland to deciduous woodland to bare soil. The goal of this research is to develop a method for classifying land cover using ANN. To begin, PCA (Principle Component Analysis) is applied to the input picture as a preprocessing step for dimensionality reduction. Next, the picture that has been preprocessed is taken to the feature extraction stage. In order to extract features, a convolutional filter is used. It is from this set of attributes that statistical features like minimum, maximum, and standard are extracted. In order to train and evaluate these features, the extracted features are transferred. Take a look at the ground truth picture afterwards. Areas of buildings, lakes, and farms are all shown in this ground truth picture.The next step in developing a classification model is to divide these photos into tw
