ml-course
Real-time-Object-Detection-for-Autonomous-Driving-using-Deep-Learning
| ml-course | Real-time-Object-Detection-for-Autonomous-Driving-using-Deep-Learning | |
|---|---|---|
| 8 | 8 | |
| 2,059 | 57 | |
| 2.4% | - | |
| 2.4 | 3.6 | |
| 3 days ago | about 3 years ago | |
| Jupyter Notebook | Jupyter Notebook | |
| MIT License | MIT License |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
ml-course
Real-time-Object-Detection-for-Autonomous-Driving-using-Deep-Learning
- Real-time Object Detection for Autonomous Driving using Deep Learning, Performance comparison of YOLO and Faster R-CNN based on the BDD100K dataset
- [P] Real-time Object Detection for Autonomous Driving using Deep Learning, Performance comparison of YOLO and Faster R-CNN on the BDD100K dataset, Goethe University Frankfurt Germany (Fall 2020)
- Real-time Object Detection for Autonomous Driving using Deep Learning, Performance comparison of YOLO and Faster R-CNN on the BDD100K dataset, Goethe University Frankfurt Germany (Fall 2020)
- Real-time Object Detection for Autonomous Driving using Deep Learning, Goethe University Frankfurt Germany (Fall 2020)
What are some alternatives?
pytorch-implementations - A collection of paper implementations using the PyTorch framework
get-started-with-JAX - The purpose of this repo is to make it easy to get started with JAX, Flax, and Haiku. It contains my "Machine Learning with JAX" series of tutorials (YouTube videos and Jupyter Notebooks) as well as the content I found useful while learning about the JAX ecosystem.
IJCAI2023-CoNR - IJCAI2023 - Collaborative Neural Rendering using Anime Character Sheets
yolo-tf2 - yolo(all versions) implementation in keras and tensorflow 2.x
Subway-Station-Hazard-Detection - This project is part of the CS course 'Systems Engineering Meets Life Sciences II' at Goethe University Frankfurt. In this Computer Vision project, we developed a first prototype of a security system which uses the surveillance cameras at subway stations to recognize dangerous situations. The training data was artificially generated by a Unity-based simulation.
HugsVision - HugsVision is a easy to use huggingface wrapper for state-of-the-art computer vision
TabularSemanticParsing - Translating natural language questions to a structured query language
simple-faster-rcnn-pytorch - A simplified implemention of Faster R-CNN that replicate performance from origin paper
Deep-Learning-Computer-Vision - My assignment solutions for Stanford’s CS231n (CNNs for Visual Recognition) and Michigan’s EECS 498-007/598-005 (Deep Learning for Computer Vision), version 2020.
lama - 🦙 LaMa Image Inpainting, Resolution-robust Large Mask Inpainting with Fourier Convolutions, WACV 2022
Made-With-ML - Learn how to design, develop, deploy and iterate on production-grade ML applications.
NYU-DLSP20 - NYU Deep Learning Spring 2020