Image Processing and classification using Machine Learning : Image Classification using Open CV and SVM machine learning model
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Updated
Jun 1, 2018 - Python
Image Processing and classification using Machine Learning : Image Classification using Open CV and SVM machine learning model
CRISP is a Fast Image Search application that retrieves similar images from a database based on the query image by using Parallel computing paradigm.
Classification of Clear Cell Renal Cell Carcinoma using CT textural feature analysis
We build a Content Based Image Retrieval (CBIR) based on some images features.
South African Coin Recognition System using multiple feature extraction techniques and classifiers
Character recognition on the street sign in Indonesian Cities
Simple OCR applied on license plates
This project is about real-time 2D object recognition. The goal is to have the computer identify a specified set of objects placed on a white surface in a translation, scale, and rotation invariant manner from a camera looking straight down. The computer should be able to recognize single objects placed in the image and identify the objects.
This is a jupyter notebook with 8 different solutions for common problems of digital image processing, including corners detection and image description and representation.
Usando Momentos de Hu para extração de atributos na tarefa de classificação de formas simples.
Image processing and classification using random forest classifier
blosobjectclassifier2: An upgraded, well-documented and fully in English version of the object classifier using computer vision developed as part of the internship program of the XXVII Scientific Research Summer at the CIC-IPN
This C++ from-scratch project implements a machine learning system to classify images of washers and coins using the K-nearest neighbors (Knn) classifier and K-means clustering for segmentation. The system incorporates Sobel edge detection and Hu moments for shape analysis, allowing it to accurately distinguish between similar circular objects.
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