Vijay Nagar

About Vijay Nagar

Passionate Computer Vision Engineer with expertise in designing and developing cutting-edge Vision & ML models, specializing in Traffic Control and Advanced Driver Assistance Systems (ADAS). Proficient in Image Processing, Signal Processing, Machine Learning, and Deep Learning. Skilled in collecting and processing large-scale traffic sign training databases and optimizing models for real-time applications. Successfully developed tools to enhance traffic sign recognition and post-processing algorithms. M-Tech thesis research focused on contact-less fingerprint recognition using Deep Learning models at PRIA Lab, IIT Indore.

Experience

1. Computer Vision Engineer

   Continental

   Oct 2021 — Present · Bangalore Urban, IN

   3D Traffic Sign Detection using LiDAR-Camera Fusion. Transformed front-view images to BEV using camera intrinsic, deployed optimized road marking detection model on hardware.Engineered and optimized a CNN-based object detection model for Traffic Signs, Lights & Road Marking signs achieving substantial real-time performance.Developed training, evaluation, and visualization pipelines with custom dataloaders and inference tool for object detection in python.Spearhead the design and development of Vision & ML models, including PC, SVM, CNN, and OCR, for accurate traffic sign recognition in ADAS applications.Optimize models to ensure real-time performance and efficiency.Collaborate with cross-functional teams to gather requirements and ensure seamless integration with ADAS systems.Implement after-classification post-processing algorithms to enhance the accuracy and reliability of traffic sign recognition.

Education

• Indian Institute of Technology, Indore

  Master of Technology - MTech

  2018 — 2020

• SKIT Jaipur

  Bachelor of Technology - BTech

  2013 — 2017