Vehicle_detection_and_tracking
| Project Name | Stars | Downloads | Repos Using This | Packages Using This | Most Recent Commit | Total Releases | Latest Release | Open Issues | License | Language |
|---|---|---|---|---|---|---|---|---|---|---|
| Vehicle Detection | 1,068 | 6 years ago | 1 | Jupyter Notebook | ||||||
| Vehicle detection using machine learning and computer vision techniques for Udacity's Self-Driving Car Engineer Nanodegree. | ||||||||||
| Vehicle Detection | 509 | 2 years ago | 20 | gpl-3.0 | Python | |||||
| Created vehicle detection pipeline with two approaches: (1) deep neural networks (YOLO framework) and (2) support vector machines ( OpenCV + HOG). | ||||||||||
| Vehicle Detection Yolo Ver | 100 | 7 years ago | 3 | Python | ||||||
| real-time Vehicle Detection( tiny YOLO ver) and HOG+SVM method | ||||||||||
| Vehicle_counting_hog_svm | 78 | 7 years ago | 3 | mit | C++ | |||||
| Vehicle Detection, Tracking and Counting by SVM with HOG Features with OpenCV | ||||||||||
| Vehicle Tracking 2 | 60 | 6 years ago | 1 | mit | Jupyter Notebook | |||||
| A vehicle detection and tracking pipeline with OpenCV, histogram of oriented gradients (HOG), and support vector machines (SVM). | ||||||||||
| Vehicle Detection And Tracking | 55 | 6 years ago | Jupyter Notebook | |||||||
| Udacity Self-Driving Car Engineer Nanodegree. Project: Vehicle Detection and Tracking | ||||||||||
| License Plate Detection | 41 | 6 years ago | Python | |||||||
| {Python}: Detect and extract the license plate of vehicles using Machine Learning and Image Processing Techniques | ||||||||||
| Carnd Vehicle Detection | 40 | 7 years ago | 4 | Jupyter Notebook | ||||||
| A vehicle tracker based on sliding windows, HOG and an SVM | ||||||||||
| Vehicle_detection_hog_svm | 27 | 7 years ago | 1 | Python | ||||||
| Vehicle detection using HOG + SVM and sliding windows | ||||||||||
| Carnd Vehicle Detection | 26 | 7 years ago | 1 | Jupyter Notebook | ||||||
| Monocular vehicle detection using SVM and Deep Learning classifiers | ||||||||||
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