Bearing fault diagnosis model based on MCNN-LSTM

isolated & continuous sign language recognition using CNN+LSTM/3D CNN/GCN/Encoder-Decoder

Predict Vehicle collision moments before it happens in Carla!. CNN and LSTM hybrid architecture is used to understand a series of images.

No description provided.

Building Time series forecasting models, including the XGboost Regressor, GRU (Gated Recurrent Unit), LSTM (Long Short-Term Memory), CNN (Convolutional Neural Network), CNN-LSTM, and LSTM-Attention. Additionally, hybrid models like GRU-XGBoost and LSTM-Attention-XGBoost for Electricity Demand and price prediction

Speech Emotion Recognition from raw speech signals using 1D CNN-LSTM

Stock Price Prediction using CNN-LSTM

Using LSTM or Transformer to solve Image Captioning in Pytorch

A CNN-LSTM deep learning model for prognostic prediction and classification of Alzheimer's MRI neuroimages.

Embedding模型代码和学习笔记总结

NN models designed to analyze and predict stock market from any stock data given

Can chess engine use be detected just from the moves on the board? Let's try, using a CNN - LSTM architecture.

The project uses state of the art deep learning on collected data for automatic analysis of emotions.

Evolutionary Neural Architecture Search for Remaining Useful Life Prediction

Performed various Deep Learning techniques to detect Human Activity using Sequential Data detect human activities generated by sensor-based wearable devices

No description provided.

西南山区植被对水文气候变化的非线性响应量化研究，包括MODIS、GLDAS、Rs数据的预处理以及CNN-LSTM模型的搭建、训练和特征重要性分析.

Based on a Hybrid CNN-LSTM Network, an automated predicitve algorithm is constructed.

Predict the trajectory of the vehicles in HCM city streets with YOLOv7 + DeepSORT + CNN-LSTM/CNN-GRU.

Create a mid-price classifier for limit order books using a CNN and LSTM

This project extracts feature points based on the Mediapipe open-source model, uses LSTM, CNN, and Vision of Transformer network models for training to obtain a deep learning model, and finally deploys and applies it.

Integrating CNN-LSTM Networks with Statistical Filtering Techniques for Optimizing IoT Intrusion Detection

Deep learning models for classifying ECG time series

A Multi-classification of chinese text with cnn-rnn model.

An experimental project for autonomous vehicle driving perception with steering angle prediction and semantic segmentation using a combination of UNet, attention and transformers.

Fault Detection and Classification techniques using Deep Learning and Machine Learning based architectures to detect the UAV maloperation in Accelerometer and Gyroscope sensors.

This work entails the usage of a novel hybrid deep transfer learning method for thermal comfort prediction in buildings with no or very little labelled data

No description provided.

Deep learning techniques for detecting 6 types of hand movements from labeled dataset procured from Kaggle, Grasp-and-Lift EEG Detection.

This repository includes codes related to the detection of sinkholes using UNet and CNN-LSTM model.