• Ashwini A

Weather classification is vital for meteorologists and weather forecasters to predict patterns and communicate information to the public. This project focuses on classifying weather phenomena into five categories: Cloudy, Shine, Rain, Foggy, and Sunrise. Deep learning methods, particularly transfer learning using VGG19 is employed for high-performance weather classification. Accurate weather classification has far-reaching applications, including environmental monitoring, weather forecasting, and improved agricultural planning. By leveraging transfer learning techniques, this project aims to enhance weather prediction accuracy and contribute to various sectors reliant on weather analysis.

"WeatherNet Automated Weather Classification using Transfer Learning_removed", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.10, Issue 8, page no.f797-f809, August-2023, Available :http://www.jetir.org/papers/JETIR2308596.pdf

"WeatherNet Automated Weather Classification using Transfer Learning_removed", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.10, Issue 8, page no. ppf797-f809, August-2023, Available at : http://www.jetir.org/papers/JETIR2308596.pdf