Vehicle detection, tracking and counting by SVM is trained with HOG features using OpenCV on c++.
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Updated
Sep 30, 2017 - C++
Vehicle detection, tracking and counting by SVM is trained with HOG features using OpenCV on c++.
The goal of this project is to solve the task of name transcription from handwriting images implementing a NN approach.
Object detection program, using HoG+SVM, OpenCV2.4.10, VS2013
Bag of Visual Words and HOG based object detection in python/opencv
Detect traffic sign and recognize them using Image Processing algorithms and Machine Learning(Random Forest)
The histogram of oriented gradients (HOG) implemented in tensorflow.
This algorithm counts occurrences of gradient orientation in localized portions of an image and visualize it in an image.
Fast computation of rectangular histogram of oriented gradients (R-HOG) features using integral histogram
Python implementation of 3D Voxel HOG from the paper "A 3D Scene Analysis Framework and Descriptors for Risk Evaluation" by Rob Dupre, Vasileios Argyriou, D. Greenhill, Georgios Tzimiropoulos.
Lab Experiments under Lab component of CSE3018 - Content-based Image and Video Retrieval course at Vellore Institute of Technology, Chennai
Histogram of oriented gradients (HOG) on GPU
Worked on a Medical Computer Vision project involving Parkinson's Disease Detection by using Histogram of Oriented Gradients (HOG), Machine Learning and OpenCV on the images generated by the Spiral-Wave test
Using Support Vector Machine and Extracting Histogram of Oriented Gradient Features
Program for Harris Corner Detection with non-maximum Suppression, HOG Feature Extraction, Feature Comparison, Gaussian Noise and Smoothing.
In this repository, we implement common image processing techniques in Python and fully describe their algorithms.
Um pouco dos trabalhos desenvolvidos durante a disciplina de Visão Computacional <3
Image Search via Feature Vectors.
This repository hosts a project that aims to tackle the issue of plagiarism in handwritten submissions. The system developed based on Multi-level detection using the combination of digital pattern analysis and text content comparison to detect potential instances of plagiarism.
Use a Histogram of Oriented Gradients (HOG), Spatial Binning of Color, Histograms of Color, a Linear Support Vector Machine and multi-scale sliding windows for vehicle detection and tracking
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