Identifying the economic wellbeing of a region with satellite images using deep learning Available to Purchase

High-resolution satellite data coupled with Deep Learning holds promise for estimating economic well-being accurately. Extracting object and texture features from satellite images to understandthe region’s economic situation. Specifically, focuses on the extraction of object and texture features from satellite images of Salem to estimate the region’s economic well-being. The research involves thedevelopment of deep learning computer vision methods capable of predicting Economic levels based on overhead satellite images. The emergence of very-high-resolution (VHR) imaging sensors has brought about significant changes, enabling the utilization of computer vision techniques for the analysis of man-made structures. This dissertation aims to develop computer vision and machine learning algorithms for the analysis with a focus on applications such as building detection.