This tutorial is a component of a series where I’ll explore deep learning applications across various domains, each with its own project.
The main focus here is on learning deep Learning and image classification.
We could have chosen to categorise cats, dogs, or flowers, but for this project, we opted to work with satellite images as they supply a singular and exciting challenge.
For this, we’ll use the EuroSAT_RGB dataset, generously shared by my friend Blanchon on Hugging Face. A special because of him for making this dataset available to the community, enabling projects like this.
On this case, the goal is to show a model to categorize several types of environments — like forests, rivers, or urban areas — based on satellite imagery.
Nevertheless, the potential applications of one of these technology extend far beyond satellite images, including:
- Medical imaging, like detecting tumors in X-rays or MRIs.
- Autonomous vehicles, enabling them to acknowledge roads, obstacles, and pedestrians.
- Retail, for customer behavior evaluation through video footage.
