Long Short Term Memory

Long Short-Term Memory (LSTM) networks are a type of recurrent neural network designed to process sequential data by learning long-term dependencies, enabling accurate predictions and classifications in various applications. Current research focuses on enhancing LSTM architectures, such as incorporating convolutional layers, attention mechanisms, and hybrid models combining LSTMs with other deep learning techniques like transformers or graph neural networks, to improve efficiency and accuracy. This work is significant because LSTMs are proving highly effective across diverse fields, from financial forecasting and environmental monitoring to medical image analysis and activity recognition, offering powerful tools for analyzing complex temporal data.

Papers

December 13, 2023

December 12, 2023

LSTM-CNN Network for Audio Signature Analysis in Noisy Environments
Praveen Damacharla, Hamid Rajabalipanah, Mohammad Hosein Fakheri
Long Short Term Memory Audio Datasets Noisy Environment Audio Forensics Speaker Detection

December 11, 2023

December 9, 2023

December 3, 2023

Enhancing Algorithm Performance Understanding through tsMorph: Generating Semi-Synthetic Time Series for Robust Forecasting Evaluation
Moisés Santos, André de Carvalho, Carlos Soares
Long Short Term Memory Faithful Generation Time Series Forecasting Synthetic Time Series Forecasting Method Algorithm Performance

December 2, 2023

Short-term Precipitation Forecasting in The Netherlands: An Application of Convolutional LSTM neural networks to weather radar data
Petros Demetrakopoulos
Neural Network Long Short Term Memory Radar Data ConvLSTM Network Convolutional LSTM

November 28, 2023

B-LSTM-MIONet: Bayesian LSTM-based Neural Operators for Learning the Response of Complex Dynamical Systems to Length-Variant Multiple Input Functions
Zhihao Kong, Amirhossein Mollaali, Christian Moya, Na Lu, Guang Lin
Long Short Term Memory Neural Operator Bayesian Perspective Deep Operator Network Complex Dynamical System Resized Diverse Input

November 26, 2023

IA-LSTM: Interaction-Aware LSTM for Pedestrian Trajectory Prediction
Yuehai Chen
Long Short Term Memory Trajectory Prediction Pedestrian Trajectory Prediction Human Interaction Interaction Representation Human Human Interaction Correntropy Learning

November 24, 2023

November 23, 2023

Object Location Prediction in Real-time using LSTM Neural Network and Polynomial Regression
Petar Stojković, Predrag Tadić
Recurrent Neural Network Long Short Term Memory Real Time Polynomial Regression

November 22, 2023

Applying Dimensionality Reduction as Precursor to LSTM-CNN Models for Classifying Imagery and Motor Signals in ECoG-Based BCIs
Soham Bafana
Long Short Term Memory Dimensionality Reduction Brain Computer Interface Visual Imagery Motor Imagery Classification Motor Impairment Functional Outcome Uniform Manifold Approximation and Projection

November 21, 2023

Harnessing FPGA Technology for Enhanced Biomedical Computation
Nisanur Alici, Kayode Inadagbo, Murat Isik
Long Short Term Memory Field Programmable Gate Array MIT BIH Arrhythmia FPGA Implementation

November 20, 2023

A Compact LSTM-SVM Fusion Model for Long-Duration Cardiovascular Diseases Detection
Siyang Wu
Long Short Term Memory Support Vector Machine Electrocardiogram Signal Atrial Fibrillation MIT BIH Arrhythmia Cardiovascular Disease Detection

November 16, 2023

November 15, 2023

Harnessing LSTM for Nonlinear Ship Deck Motion Prediction in UAV Autonomous Landing amidst High Sea States
Feifan Yu, Wenyuan Cong, Xinmin Chen, Yue Lin, Jiqiang Wang
Long Short Term Memory Autonomous Landing Ship Motion

Long Short Term Memory

Papers

PTT: Point-Trajectory Transformer for Efficient Temporal 3D Object Detection

Automatic Bug Detection in Games using LSTM Networks

LSTM-CNN Network for Audio Signature Analysis in Noisy Environments

Improving age prediction: Utilizing LSTM-based dynamic forecasting for data augmentation in multivariate time series analysis

Transformer Attractors for Robust and Efficient End-to-End Neural Diarization

Keyword spotting -- Detecting commands in speech using deep learning

Enhancing Financial Data Visualization for Investment Decision-Making

Enhancing Algorithm Performance Understanding through tsMorph: Generating Semi-Synthetic Time Series for Robust Forecasting Evaluation

Short-term Precipitation Forecasting in The Netherlands: An Application of Convolutional LSTM neural networks to weather radar data

B-LSTM-MIONet: Bayesian LSTM-based Neural Operators for Learning the Response of Complex Dynamical Systems to Length-Variant Multiple Input Functions

IA-LSTM: Interaction-Aware LSTM for Pedestrian Trajectory Prediction

Digital Twin Technology Enabled Proactive Safety Application for Vulnerable Road Users: A Real-World Case Study

StableSSM: Alleviating the Curse of Memory in State-space Models through Stable Reparameterization

Object Location Prediction in Real-time using LSTM Neural Network and Polynomial Regression

Applying Dimensionality Reduction as Precursor to LSTM-CNN Models for Classifying Imagery and Motor Signals in ECoG-Based BCIs

Harnessing FPGA Technology for Enhanced Biomedical Computation

A Compact LSTM-SVM Fusion Model for Long-Duration Cardiovascular Diseases Detection

Formal Verification of Long Short-Term Memory based Audio Classifiers: A Star based Approach

Future Full-Ocean Deep SSPs Prediction based on Hierarchical Long Short-Term Memory Neural Networks

Harnessing LSTM for Nonlinear Ship Deck Motion Prediction in UAV Autonomous Landing amidst High Sea States