🚗 Building the Future of Autonomous Vehicles with Deep Learning 🤖
Welcome to the Multi-Model Autonomous Driving project! Here, we're on a journey to advance the world of self-driving cars using the power of deep learning and sensor fusion.
In this repository, you'll find a comprehensive exploration of multiple deep learning models designed to enhance autonomous driving capabilities. We're not just building models; we're paving the way for safer, smarter, and more efficient autonomous vehicles.
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Multi-Model Approach: 📊 We've developed and tested various deep learning models to detect and classify traffic signals, spot obstacles, and identify lanes.
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Comparative Study: 📈 We've conducted in-depth comparative studies using prominent models like Mask-RCNN, ResNet50, InceptionV3, and MobileNet in realistic simulated environments.
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3D Data Visualization: 🌐 Our work includes KITTI 3D data visualization, which plays a pivotal role in understanding the vehicle's surroundings.
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Algorithm Implementation: 🤖 We've worked with various cutting-edge algorithms, including FCNN, DeepSort, MTAN, SFA 3D, UNetXST, and ViT, to improve vehicle perception.
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Real Autonomous Vehicle: 🚀 We've taken our knowledge and applied it to build a tangible autonomous driving vehicle. This real-world system uses Jetson Nano, Arduino, and Ultrasonic Sensors to detect lanes, avoid obstacles, and respond to traffic signals through deep learning and image segmentation.
Ready to dive into the world of autonomous driving and deep learning? Check out our project's code, data, and documentation:
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Code - Explore the deep learning models and code used in the project.
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Data - Access the datasets and data preprocessing scripts.
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Documentation - Dive into our project documentation to understand the algorithms, models, and implementation details.
This project is open-source under the MIT License. Feel free to use, modify, and contribute to our work.
We'd like to express our gratitude to the open-source community, researchers, and developers who have paved the way for advancements in autonomous driving and deep learning.
Happy Coding and Safe Driving! 🛣️👨💻🚗