Land Cover Classification using MATLAB
Title:- An Efficient Land Cover Classification Using Generative Adversarial Network
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Software Requirements:
1. Matlab-R2020a
2. Windows-10 (64-bit) operating system
Note:
1) Paste the code into E drive
2) Don't Delete any file or folders project contains......
Implementation Plan:
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Step 1: Initially we load the input images from the datasets
Step 2: Next we perform the process of split the images based on the Dilated Convolutions process.
Step 3: Next we perform the image augmentation and Segmentation process, In this process we rotate the images in terms of several degrees such as 10°, 90°, 180°, and 270°. After rotating the images, instance segmentation is performed for the images using Generative Adversarial Network algorithm.
Step 4: Nex we perform feature extraction from the segmented images and perform classification of land covers using Dove Swarm Optimization Algorithm.
Step 5: Finally, The performance of this research is evaluated in terms of following metrics, sensitivity, Specificity, Accuracy, Precision, Recall,F-Measure,NPV,FPR,FNR,MCC and MIOU .
