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Top 115 feature-extraction open source projects

Computer Vision Guide
📖 This guide is to help you understand the basics of the computerized image and develop computer vision projects with OpenCV. Includes Python, Java, JavaScript, C# and C++ examples.
Automated feature extraction in Python
Bert Attributeextraction
USING BERT FOR Attribute Extraction in KnowledgeGraph. fine-tuning and feature extraction. 使用基于bert的微调和特征提取方法来进行知识图谱百度百科人物词条属性抽取。
Amazing Feature Engineering
Feature engineering is the process of using domain knowledge to extract features from raw data via data mining techniques. These features can be used to improve the performance of machine learning algorithms. Feature engineering can be considered as applied machine learning itself.
An intuitive library to extract features from time series
Time series features
Tf featureextraction
Convenient wrapper for TensorFlow feature extraction from pre-trained models using tf.contrib.slim
Augmented reality
💎 "Marker-less Augmented Reality" with OpenCV and OpenGL.
Emotion Recognition Using Speech
Building and training Speech Emotion Recognizer that predicts human emotions using Python, Sci-kit learn and Keras
Direct Graphical Models (DGM) C++ library, a cross-platform Conditional Random Fields library, which is optimized for parallel computing and includes modules for feature extraction, classification and visualization.
Machine Learning Workflow With Python
This is a comprehensive ML techniques with python: Define the Problem- Specify Inputs & Outputs- Data Collection- Exploratory data analysis -Data Preprocessing- Model Design- Training- Evaluation
Speech signal processing and classification
Front-end speech processing aims at extracting proper features from short- term segments of a speech utterance, known as frames. It is a pre-requisite step toward any pattern recognition problem employing speech or audio (e.g., music). Here, we are interesting in voice disorder classification. That is, to develop two-class classifiers, which can discriminate between utterances of a subject suffering from say vocal fold paralysis and utterances of a healthy subject.The mathematical modeling of the speech production system in humans suggests that an all-pole system function is justified [1-3]. As a consequence, linear prediction coefficients (LPCs) constitute a first choice for modeling the magnitute of the short-term spectrum of speech. LPC-derived cepstral coefficients are guaranteed to discriminate between the system (e.g., vocal tract) contribution and that of the excitation. Taking into account the characteristics of the human ear, the mel-frequency cepstral coefficients (MFCCs) emerged as descriptive features of the speech spectral envelope. Similarly to MFCCs, the perceptual linear prediction coefficients (PLPs) could also be derived. The aforementioned sort of speaking tradi- tional features will be tested against agnostic-features extracted by convolu- tive neural networks (CNNs) (e.g., auto-encoders) [4]. The pattern recognition step will be based on Gaussian Mixture Model based classifiers,K-nearest neighbor classifiers, Bayes classifiers, as well as Deep Neural Networks. The Massachussets Eye and Ear Infirmary Dataset (MEEI-Dataset) [5] will be exploited. At the application level, a library for feature extraction and classification in Python will be developed. Credible publicly available resources will be 1used toward achieving our goal, such as KALDI. Comparisons will be made against [6-8].
R/shiny interface for interactive visualization of data in SummarizedExperiment objects
Color recognition
🎨 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.
.NET library for 1D signal processing focused specifically on audio processing
Fast and simple music and audio analysis using RNN in Python 🕵️‍♀️ 🥁
👷‍♂️ A simple package for extracting useful features from character objects 👷‍♀️
Sourceafis Java
Fingerprint recognition engine for Java that takes a pair of human fingerprint images and returns their similarity score. Supports efficient 1:N search.
🏗 Statistical models for biomolecular dynamics 🏗
The Building Data Genome Project
A collection of non-residential buildings for performance analysis and algorithm benchmarking
A C++ Qt GUI desktop program to calculate Harris, FAST, SIFT and SURF image features with OpenCV
Dimensionality reduction alo codes
Kaggle Competitions
There are plenty of courses and tutorials that can help you learn machine learning from scratch but here in GitHub, I want to solve some Kaggle competitions as a comprehensive workflow with python packages. After reading, you can use this workflow to solve other real problems and use it as a template.
Deep Learning: Image classification, feature visualization and transfer learning with Keras
A sparsity aware and memory efficient implementation of "Attributed Social Network Embedding" (TKDE 2018).
A sparsity aware implementation of "Enhanced Network Embedding with Text Information" (ICPR 2018).
Edge extraction
Fast and robust algorithm to extract edges in unorganized point clouds
Seg Mentor
TFslim based semantic segmentation models, modular&extensible boutique design
Algorithms for matching audio file similarities. Mirror of
Automatic feature extraction and node role assignment for transfer learning on graphs (ReFeX & RolX)
Comprehensive toolkit for generating various numerical features of protein sequences
Cbir System
Content-Based Image Retrieval system (KTH DD2476 Project)
A large scale feature extraction tool for text-based machine learning
💬 SpeechPy - A Library for Speech Processing and Recognition:
Automatic extraction of relevant features from time series:
Open-source python package for the extraction of Radiomics features from 2D and 3D images and binary masks. Support:
Feature Selection
Features selector based on the self selected-algorithm, loss function and validation method
Feature Engineering And Feature Selection
A Guide for Feature Engineering and Feature Selection, with implementations and examples in Python.
Awesome Feature Engineering
A curated list of resources dedicated to Feature Engineering Techniques for Machine Learning
Highly comparative time-series analysis
Fully Convolutional Geometric Features: Fast and accurate 3D features for registration and correspondence.
This repository contains the code related to Natural Language Processing using python scripting language. All the codes are related to my book entitled "Python Natural Language Processing"
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