Overview
The Meteor Reduction System is a project developed by SAIL in collaboration with the UAE Meteor Monitoring Network (UAEMMN). The system is designed to automatically filter out false data captured by the UAEMMN cameras.
Key Features
Image Classification and Object Algorithms
Advanced deep learning models are used to distinguish meteors from background noise, improving the overall detection process.
Image Processing
High-resolution images captured from UAEMMN towers are processed to identify meteor trails, ensuring precise localization and trajectory analysis.
Automated Data Reduction:
The system automates data reduction, making it easier for scientists to focus on important meteor events rather than sifting through massive amounts of raw data.
Image Classification and Object Algorithms
Advanced deep learning models are used to distinguish meteors from background noise, improving the overall detection process.
Image Processing
High-resolution images captured from UAEMMN towers are processed to identify meteor trails, ensuring precise localization and trajectory analysis.
Automated Data Reduction:
The system automates data reduction, making it easier for scientists to focus on important meteor events rather than sifting through massive amounts of raw data.
Advanced deep learning models are used to distinguish meteors from background noise, improving the overall detection process.
Image Processing
High-resolution images captured from UAEMMN towers are processed to identify meteor trails, ensuring precise localization and trajectory analysis.
Automated Data Reduction:
The system automates data reduction, making it easier for scientists to focus on important meteor events rather than sifting through massive amounts of raw data.
Gallery
