Deep learning approach for estimation of Remaining Useful Life (RUL) of an engine

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PyTorch Code for running various time series models for different time stamps and confidence intervals for Solar Irradiance prediction.

[ICIVC 2019] "LSTM multi-modal UNet for Brain Tumor Segmentation"

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

S&P500 Stock Index Movement Forecastor with various Statistical and Machine Learning Models

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.

Image Captioning using LSTM and Deep Learning on Flickr8K dataset.

A Deep Learning Based Automated Video Colorization Framework

This repository aims to address the critical issue of identifying and understanding suicide ideation in social media conversations, specifically focusing on Twitter data.

A stock selection and prediction tool for the next day using a variety of stacked LSTM neural networks

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.

LSTM action recognition.

Deep learning system for automatic cardiac arrhythmia classification from 12-lead ECG signals. Implements CNN, LSTM, and hybrid architectures trained on PTB-XL dataset. Features multi-label classification for 5 diagnostic classes (NORM, MI, STTC, CD, HYP) with comprehensive visualization tools.

Autonomous stock trading application using deep neural networks

Clinical Named Entity Recognition for EHR

A comparative analysis of various machine learning models for time series forecasting, including traditional methods and LLMs.

An easy-to-use CLI tool for training and testing image classifiers

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

NLP with LSTM for Sentiment Analysis of English texts

Stress Pics Detection Using EEG Signals

The goal of this project is to build a VQA model that can take a pair of Image and Question (English) as input, then return the Answer for the Question about the Image.

VAE Implementation with LSTM Encoder and CNN Decoder

利用 keras 构建LSTM- CNN模型实现NLP模糊限制语的范围检测

A hybrid CNN-LSTM model to predict Indonesian gold prices based on historical time series data, with performance evaluation using RMSE and MSE.

Metaphor detection using cnn lstm

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.