Detect and track vehicles using computer vision and classification techniques
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Updated
May 6, 2017 - Jupyter Notebook
Detect and track vehicles using computer vision and classification techniques
Supervised Classification using Python, SVM, HOG, Jupyter, Anaconda, AWS, Ubuntu
Explore object recognition, segmentation, and how to process depth data from camera sensors to help a robot better understand and navigate its world.
Python Image Search Engine with OpenCV
The project was run in ROS and RViz simulation to practice 3D image segmentation and train a robot with SVM algorithm.
Vehicle Detection Project from the Udacity Self-Driving Car Engineer Nanodegree
Color/Texture based Image Retrieval
Repository containing all the codes created for the lab sessions of CSE3018 Content Based Image and Video Retrieval at VIT University Chennai Campus
Image Search Engine
Multiple Moving objects in a surveillance video were detected and tracked using ML models such as AdaBoosting. The obtained results were compared with the results from Kalman Filter.
Working on Cifar-10 Dataset and Finding out its best SVM Model.
🎨 Color recognition & classification & detection on webcam stream / on video / on single image using K-Nearest Neighbors (KNN) is trained with color histogram features by OpenCV.
Lab Experiments under Lab component of CSE3018 - Content-based Image and Video Retrieval course at Vellore Institute of Technology, Chennai
A Java Desktop App to search similar images using colors histogram
Code to perform Image Colour HIstogram Matching between two Images
Pembuatan Aplikasi Desktop Pengenalan Jenis Masker dengan Metode Color Histogram dan Euclidean Distance
Create a moving object detection and tracking program using MATLAB & Python.
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