Processing biomedical data using LBP, HOG, and Gabor filters for enhanced analysis and feature extraction.
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Updated
Jul 6, 2024 - Python
Processing biomedical data using LBP, HOG, and Gabor filters for enhanced analysis and feature extraction.
このリポジトリは、顔検出および特徴量抽出のための様々な Python スクリプトを含んでいます。各スクリプトは異なるアルゴリズムや手法を使用しており、簡単に実行できるようになっています。
K-means clustering is an algorithm that groups similar data points into a predetermined number of clusters by minimizing the sum of squared distances between data points and their cluster centroids.
Detection algorithms and applications from famous papers; simple theory; solid code.
Face recognition is used for to unlocking cell phones. And with recent advancements in deep learning,In this repository how to develop a face recognition system that can detect faces in images, identify the faces, and even modify faces with "digital makeup" like you've experienced in popular mobile apps
Final Electronic Engineering project
🖐 An implementation of a machine learning model for detecting and recognizing hand signs (0-5) accurately using Python. The project pipeline involves the following modules: Preprocessing, Feature Extraction, Model selection and training, and finally performance analysis.
Digit Recognition Neural Network: Built from scratch using only NumPy. Optimised version includes HOG feature extraction. Third version utilises prebuilt ML libraries.
Facial Recognition and Tracking Application using Deep Learning.
content-based image retrieval system
🖐 An implementation of a machine learning model for detecting and recognizing hand signs (0-5) accurately using Python. The project pipeline involves the following modules: Preprocessing, Feature Extraction, Model selection and training, and finally performance analysis.
🖐 An implementation of a machine learning model for detecting and recognizing hand signs (0-5) accurately using Python. The project pipeline involves the following modules: Preprocessing, Feature Extraction, Model selection and training, and finally performance analysis.
Deep facial expressions recognition using Opencv and Tensorflow. Recognizing facial expressions from images or camera stream
Detecting Cars in real time and identifying the speed of cars and tracking
A face recognition app, using LBP method (Local Binary Pattern) and HOG (Histogram of Oriented Gradients)
OpenCV Human Detection using HOG descriptor
Detects Pedestrians in images using HOG as a feature extractor and SVM for classification
Attendance System using Face Recognition (HOG)
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