Paper Title
Road Extraction using CNN & Swarm Intelligence from Remote Sensing Images

Abstract
The updated road network, which is a key aspect of the transportation network, is used in a variety of applications. Therefore, an intensive study is carried out in enhancing overall automation for road segmentation methodologies from remote sensing photos. Conventional System data updates rely on field samplings or artificial land mapping interpretations in remotely sensed images. The flaws are serious shortcomings: expensive costs, long production times, and even a high human need. To overcome this challenge, we employ a convolutional deep learning neural network to extract road data from a multispectral picture. We also investigated our algorithm's sensitivity to various ant colony optimization parameter values. Keywords - Convolutional Neural Network, Multi-Resolution Segmentation, Multispectral Satellite Images, Remote Sensing Technology, Swarm