Robust Feature Extraction Algorithm for analysis of Radar Targets using Multi-Object Tracking on Range Velocity Space

In this thesis, we propose, a Robust data extraction algorithm capable of extracting reliable target features of multiple moving targets of different classes over all channels of an S-Band Doppler Polarimetric Radar PARSAX. The proposed algorithm is capable of generating a time series data by tracking, clusters of detections - representing...

Recommender Systems with Evolutionary Algorithms: Many­-Objective Optimization for Large­-Scale Music Recommendation: A demonstration showing the reliability of serving users recommendations with trade-­off for large music collections, by leveraging diverse Recommender Systems and Evolutionary Algorithms

Using Recommender Systems with Evolutionary Algorithms is an extremely niche domain. It holds the key to enabling new user interaction designs, where users can effectively configure their experience with a Recommender System. This thesis answers important questions about the scientific aspects of its application to large-scale data through a...