Subhashini Madhavan

Master Thesis – RADAR based Object Classification using Deep Learning, Goals: • Development and evaluation of deep learning model • Analysis of RADAR data suitable for classification in autonomous cars • RADAR based data augmentation and feature engineering

• Data acquisition in AUDI Q7 • Analysis of the data from LIDAR, RADAR, and Camera • Labelling Tool Management Tools and Libraries C++

• Collect and pre-process image to have noise in the image • Design and implementation of CNN model suitable for denoising • Development of three different models are developed for removing noise from image • Evaluation and comparison of results Matlab: MatConvnet ToolBox

• Front end GUI development using PyQT5 • RADAR sensor Data analysis using Numpy, Scipy • Radar data acquired from Audi Q7 for research in autonomous cars • Tool is created for visualizing, processing and filtering from raw radar data Tools and libraries Python: Numpy, Scipy, Pyqt5, matplotlib, GIT

• Web Application development for PhD students • Creation and maintenance of relational database • Design of frontend and backend functionalities • Security and performance testing Tools and Libraries: PHP, HTML5, CSS, Javascript, Mysql

• Resolving issues raised in JIRA • PeopleSoft development for Credit Risk Data Warehousing (CRDW) • Blackbox, functional, and unit testing • Preparation of design and test documents Tools C++, DB2, JIRA

• Hardware and software design of NLMS adaptive filter on FPGA • Testing of the adaptive filter

Signal Processing Machine Learning

Electronics and comunication