Frontiers

Emotion estimation from video footage with LSTM

Emotion estimation is a field that has been studied for a long time, and several approaches using machine learning models exist. This article presents BlendFER-Lite, an LSTM model that uses ...
Scientific Research Publishing

An Optimized Port Operation Efficiency Prediction Model Based on ESN and LSTM ()

With the in-depth digital transformation of the global shipping industry, the accurate prediction of smart port operation efficiency has become a key factor in enhancing the competitiveness of ...
GitHub

LSTM and RNN Tutorial with Demo (with Stock/Bitcoin Time Series Prediction, Sentiment Analysis, Music Generation)

What is Deep Learning (DL)? "Deep Learning is a subfield of machine learning concerned with algorithms inspired by the structure and function of the brain called artificial neural networks." There are ...
GitHub

Deep Neural Network Based Fault Classification and Location Detection in Power Transmission Lines

This project investigates the application of Deep Neural Networks (DNNs) for automated fault classification and fault location in power transmission lines. Using data generated from a simulated 4-bus ...
Frontiers

Contextual MEG and EEG Source Estimates Using Spatiotemporal LSTM Networks

Most magneto- and electroencephalography (M/EEG) based source estimation techniques derive their estimates sample wise, independently across time. However, neuronal assemblies are intricately ...
Hacker

Five video classification methods implemented in Keras and TensorFlow

Classifying video presents unique challenges for machine learning models. As I’ve covered in my previous posts, video has the added (and interesting) property of temporal features in addition to the ...