There are 2 repositories under lstm-cnn topic.
Deep learning approach for estimation of Remaining Useful Life (RUL) of an engine
[ICIVC 2019] "LSTM multi-modal UNet for Brain Tumor Segmentation"
PyTorch Code for running various time series models for different time stamps and confidence intervals for Solar Irradiance prediction.
End-to-end-Sequence-Labeling-via-Bi-directional-LSTM-CNNs-CRF-Tutorial
Undergraduate Research Project
Activity Recognition using Temporal Optical Flow Convolutional Features and Multi-Layer LSTM
Keras implementation of path-based link prediction model for knowledge graph completion
Sarcasm is a term that refers to the use of words to mock, irritate, or amuse someone. It is commonly used on social media. The metaphorical and creative nature of sarcasm presents a significant difficulty for sentiment analysis systems based on affective computing. The technique and results of our team, UTNLP, in the SemEval-2022 shared task 6 on sarcasm detection are presented in this paper.
S&P500 Stock Index Movement Forecastor with various Statistical and Machine Learning Models
Image Captioning using LSTM and Deep Learning on Flickr8K dataset.
A Deep Learning Based Automated Video Colorization Framework
This deep learning model uses a CNN-LSTM architecture to predict whether a given domain name is genuine or was artificially generated by a DGA.
Clinical Named Entity Recognition for EHR
An easy-to-use CLI tool for training and testing image classifiers
A stock selection and prediction tool for the next day using a variety of stacked LSTM neural networks
NLP with LSTM for Sentiment Analysis of English texts
This project is dedicated to forecasting 1-hour EURUSD exchange rates through the strategic amalgamation of advanced deep learning techniques. The incorporation of key technical indicators—RSI, MA, EMA, and VWAP—enhances the model's grasp of market dynamics
A Machine Learning-based Empirical study to predict the Stock Market Price of the future 10 days Using Historical Data. Research Paper is published at https://ieeexplore.ieee.org/document/9342571
Deep Learning models to predict traffic intensity in Madrid city
This repository contains code for a highly efficient LSTM based DL model which could predict greenhouse gas emissions using satellite imagery data.
Use several classical deep learning models to solve multi-label NLP classification problem
Sentiment Analysis using Conv1D and LSTM
Heavy Drinking Detection using deep learning techniques
VAE Implementation with LSTM Encoder and CNN Decoder
LSTM (Long Short-Term Memory) is a type of recurrent neural network used for processing sequential data. It has the ability to store and access information over a longer period of time, allowing it to handle tasks such as language modeling, speech recognition, and sequence prediction.
A repository contains necessary foundational exercises in NLP for beginners.