After many iterations, our system successfully identified new exoplanets and accurately classified their types. During this process, we also optimized processing speed and redesigned the architecture to make more efficient use of computing power and resources. These improvements enabled the system to handle large datasets within a specific timeframe while maintaining high accuracy,  advancing our capacity to explore and understand celestial bodies.

Our final goal was to attempt to further understand the underlying distribution patterns of certain types of exoplanets, focusing on their locations within the Milky Way as well as characteristics of their host stars. By analysing these distributions, we aimed to uncover patterns that might reveal where habitable planets are more likely to be found. This insight not only adds depth to our understanding of exoplanet distributions but also helps narrow down the search for worlds that might support life.