Deep learning for Geospatial data applications — Multi-label Classification
A beginner's guide and tutorial for classifying satellite images with Fastai
Artificial intelligence (AI) and Machine learning (ML) have touched on every possible domain and the Geospatial world is no exception. The intersection of Geospatial data and AI is already disrupting many industries and holds great potential in many Geospatial driven applications including agriculture, insurance, transportation, urban planning and disaster management.
Classifying, detecting or segmenting multiple objects from satellite images is a hard and tedious task that AI can perform with more speed, consistency and perhaps more accurate than humans can perform. We call this Computer vision, and in particular, a subtype of machine learning called Deep Learning (DL) is disrupting the industry. Deep learning, an algorithm inspired by the human brain using Neural networks and big data, learns (maps) inputs to outputs.
However, Neural networks require a large number of parameters and fine-tuning to perform well and not in the distant past using neural networks required building a large number of parameters from scratch. In addition, Graphics Processing Unit (GPU) availability was limited, which is crucial for doing deep learning. With…
