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 …

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

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

LSTM action recognition.

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.

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

Clinical Named Entity Recognition for EHR

NLP with LSTM for Sentiment Analysis of English texts

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

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