Multiple Object Detection and Segmentation for Remote Sensing Images

The Convolutional Neural Network (CNN) has been playing a significant role in processing remote sensing images and providing specific data from those images. The proposed system aims in processing the remote sensing images using CNN (AlexNet) through Unsupervised Learning algorithm and perform multiple object detection and segmentation. The object detection focus on detecting the required objects in the image and segmentation helps in representing those detected images more precisely using different segmentation processes. It is observed that the proposed system has delivered more effective output images with specific data present in the image. The proposed system has a huge scope in the field of Satellite Communication and with required update and advancement in technology the proposed system can be used for various applications.