Feature Extraction of Satellite Images Using Machine Learning

Highlight extraction from high-goal satellite pictures holds enormous potential in different fields like ecological observing, metropolitan preparation, and asset the executives. This paper presents a clever way to deal with include extraction utilizing Convolutional Brain Organizations (CNNs), a kind of profound learning model capable at handling picture information. The technique spins around executing a CNN model prepared to perceive and group key elements in satellite symbolism, for example, expanses of land, water bodies, and backwoods. The viability of the model is highlighted by its better precision thought about than customary AI techniques, particularly because of the capacity of CNNs to keep up with the spatial setting of pictures and to oppose positional and rotational changes.