Eswaramoorthy

Lane Detection for Advanced Driver Assistance Systems (ADAS)

Developed a lane detection system for Advanced Driver Assistance Systems (ADAS) to identify and track road lane markings in real time. Implemented computer vision and image processing techniques to detect lane boundaries from road images. Enabled driver assistance functionalities such as lane departure warning and lane keeping support. Improved road safety by ensuring the vehicle maintains correct lane positioning.

Deep Learning-Based Sound Classification for Auditory Scene Analysis in Digital Hearing Aids

Designed a deep learning model using Convolutional Neural Networks (CNN) to classify environmental sounds for auditory scene analysis. Trained and tested the model on auditory datasets to differentiate between multiple environmental sound categories. Evaluated model performance using metrics such as accuracy, precision, and recall. Compared different CNN architectures to identify the most effective model for sound classification in digital hearing aid applications