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emd

Python implementations of empirical mode decomposition as well as EEMD and CEEMD variants.

emd_lstm

emotional_classification_with_rnn

基于循环神经网络(RNN)的影评情感分类

entropy-weighted-nmf

Code for entropy weighted nonnegative matrix factorization

event-driven-stock-prediction-using-deep-learning

A deep learning method for event driven stock market prediction. Deep learning is useful for event-driven stock price movement prediction by proposing a novel neural tensor network for learning event embedding, and using a deep convolutional neural network to model the combined influence of long-term events and short-term events on stock price movements

exercise

exercise for nndl

expression-recognition

基于CNN的表情识别demo

facelogin

A demo for AI face Login and registor

facial-expression-recognition-using-cnn

Deep facial expressions recognition using Opencv and Tensorflow. Recognizing facial expressions from images or camera stream

facial-expression-recognition.pytorch

A CNN based pytorch implementation on facial expression recognition (FER2013 and CK+), achieving 73.112% (state-of-the-art) in FER2013 and 94.64% in CK+ dataset

fault-detection-for-predictive-maintenance-in-industry-4.0

This research project will illustrate the use of machine learning and deep learning for predictive analysis in industry 4.0.

feature-extraction

Computer vision feature extraction toolbox for image classification

feature-selection-for-fmri-fingerprinting

flow-forecast

Deep learning PyTorch library for time series forecasting, classification, and anomaly detection (originally for flood forecasting).

food-101-keras

Food Classification with Deep Learning in Keras / Tensorflow

food_classification

Food Image Recognition with Deep Convolutional features of Deep Learning

frame-predict-vae-lstm

Predicting image frames using autoencoder and LSTM

fraud_detection

Anomaly Detection Implementation : Credit card fraud

fruits-and-vegetable-recognition-system-using-cnn

Its a fruits and vegetable recognition system using CNN and provide the recipe suggestions to the user. User can click vegetable or fruit image using this app. This CNN model predicts the provided image and gives the available recipe suggestions as well as the procedures.

fsnmf

Transfer Learning via Feature Selection based Nonnegative Matrix Factorization

fully-automated-method-for-glaucoma-screening-using-cup-to-disc-ratio-computation-in-retinal-images

Python implementation of the paper "Fully Automated Method for Glaucoma Screening Using Robust Optic Nerve Head Detection and Unsupervised Segmentation Based Cup-To-Disc Ratio Computation in Retinal Fundus Images", by Amed Mvoulana et al., published in Computerized Medical Imaging and Graphics, 2019.

g-meta

Graph meta learning via local subgraphs (NeurIPS 2020)

g-mpnn-r

ga_pso_deep_learning

Multiple Time Series Fusion Based on LSTM: An Application to CAP A Phase Classification Using EEG

gat

Graph Attention Networks (https://arxiv.org/abs/1710.10903)

gatne

Source code and dataset for KDD 2019 paper "Representation Learning for Attributed Multiplex Heterogeneous Network"

gbs

A Study of Graph-based System for Multi-view Clustering

gbssl

Graph-Based Semi-Supervised Learning Algorithms

gcn

Implementation of Graph Convolutional Networks in TensorFlow

gdn

Implementation code for the paper "Graph Neural Network-Based Anomaly Detection in Multivariate Time Series"