Stacked Autoencoder

Stacked autoencoders (SAEs), a type of deep learning architecture, are used to learn complex data representations by successively encoding and decoding information through multiple layers. Current research focuses on applying SAEs to diverse problems, including feature extraction for improved classification (e.g., in ransomware detection, emotion classification, and speaker recognition), denoising signals (e.g., in radio astronomy and medical imaging), and generating data (e.g., in music composition and fluid dynamics simulations). The effectiveness of SAEs in these applications stems from their ability to reduce dimensionality, extract relevant features, and handle noisy or incomplete data, leading to improved performance in various fields.

Papers

October 4, 2024

Improving Arabic Multi-Label Emotion Classification using Stacked Embeddings and Hybrid Loss Function
Muhammad Azeem Aslam, Wang Jun, Nisar Ahmed, Muhammad Imran Zaman, Li Yanan, Hu Hongfei, Wang Shiyu, Xin Liu
Low Resource Multi Label Classification Stacked Autoencoder Hybrid Loss

May 11, 2024

Towards an Accessible and Rapidly Trainable Rhythm Sequencer Using a Generative Stacked Autoencoder
Alex Wastnidge
Deep Learning Music Generation Auto Encoder Rhythmic Pattern Stacked Autoencoder Music Sequence

March 3, 2024

SANGRIA: Stacked Autoencoder Neural Networks with Gradient Boosting for Indoor Localization
Danish Gufran, Saideep Tiku, Sudeep Pasricha
Localization Focus Indoor Localization Indoor Environment Gradient Boosting Stacked Autoencoder Device Heterogeneity

February 17, 2024

Ransomware detection using stacked autoencoder for feature selection
Mike Nkongolo, Mahmut Tokmak
Long Short Term Memory Supervised Autoencoder Feature Selection Stacked Autoencoder Ransomware Detection

January 17, 2024

AntiPhishStack: LSTM-based Stacked Generalization Model for Optimized Phishing URL Detection
Saba Aslam, Hafsa Aslam, Arslan Manzoor, Chen Hui, Abdur Rasool
Anti Phishing Stacked Autoencoder Phishing Attack Url Detection

November 6, 2023

Stacked Autoencoder Based Feature Extraction and Superpixel Generation for Multifrequency PolSAR Image Classification
Tushar Gadhiya, Sumanth Tangirala, Anil K. Roy
Classification Algorithm Stacked Autoencoder Softmax Classifier Polarimetric Synthetic Aperture Radar PolSAR Image

July 27, 2023

VISU at WASSA 2023 Shared Task: Detecting Emotions in Reaction to News Stories Leveraging BERT and Stacked Embeddings
Vivek Kumar, Sushmita Singh, Prayag Tiwari
Ticket BERT Shared Task Emotion Classification Contextual Embeddings Emotion Detection Human Reaction Short Term Memory Stacked Autoencoder

July 6, 2023

DSARSR: Deep Stacked Auto-encoders Enhanced Robust Speaker Recognition
Zhifeng Wang, Chunyan Zeng, Surong Duan, Hongjie Ouyang, Hongmin Xu
Speaker Recognition Discriminant Analysis Stacked Autoencoder

May 9, 2023

Localisation of Mammographic masses by Greedy Backtracking of Activations in the Stacked Auto-Encoders
Shamna Pootheri, Govindan V K
Image Analysis Targeted Activation Penalty Mammogram Classification Stacked Autoencoder Multidimensional Backtracking

March 15, 2023

Health Monitoring of Movement Disorder Subject based on Diamond Stacked Sparse Autoencoder Ensemble Model
Likun Tang, Jie Ma, Yongming Li
Feature Learning Wearable Sensor Health Monitoring Stacked Autoencoder Feature Reduction Movement Disorder

October 25, 2022

A new Stack Autoencoder: Neighbouring Sample Envelope Embedded Stack Autoencoder Ensemble Model
Chuanyan Zhou, Jie Ma, Fan Li, Yongming Li, Pin Wang, Xiaoheng Zhang
Stacked Autoencoder Envelope Tracking Sparse Auto Encoders

October 24, 2022

Removing Radio Frequency Interference from Auroral Kilometric Radiation with Stacked Autoencoders
Allen Chang, Mary Knapp, James LaBelle, John Swoboda, Ryan Volz, Philip J. Erickson
Denoising Autoencoder Stacked Autoencoder Radio Frequency Interference Auroral Classification

September 20, 2022

Boosting the Discriminant Power of Naive Bayes
Shihe Wang, Jianfeng Ren, Xiaoyu Lian, Ruibin Bai, Xudong Jiang
Feature Augmentation Naive Bayes Classifier Naive Bayes Auto Encoders Discriminative Power Stacked Autoencoder

March 9, 2022

Anomaly Detection for Unmanned Aerial Vehicle Sensor Data Using a Stacked Recurrent Autoencoder Method with Dynamic Thresholding
Victoria Bell1, Divish Rengasamy, Benjamin Rothwell, Grazziela P Figueredo
Anomaly Detection Long Short Term Memory Outlier Detection Stacked Autoencoder UAV Dataset UAV Data

February 18, 2022

Learning Physics-Informed Neural Networks without Stacked Back-propagation
Di He, Shanda Li, Wenlei Shi, Xiaotian Gao, Jia Zhang, Jiang Bian, Liwei Wang, Tie-Yan Liu
Neural Network LeArning Abstract Physic Informed Neural Network High Dimensional Partial Differential Equation Stacked Autoencoder Second Order Derivative

February 17, 2022

Combining Varied Learners for Binary Classification using Stacked Generalization
Sruthi Nair, Abhishek Gupta, Raunak Joshi, Vidya Chitre
Machine Learning Ensemble Learning Binary Classification Generalization Error Stacked Autoencoder Student Learning Polycystic Ovary Syndrome

December 13, 2021

Stacked Generative Machine Learning Models for Fast Approximations of Steady-State Navier-Stokes Equations
Shen Wang, Mehdi Nikfar, Joshua C. Agar, Yaling Liu
Computational Fluid Dynamic Fluid Dynamic Diverse Equation Navier Stokes Efficient Approximation Stacked Autoencoder

December 9, 2021

Sparse-View CT Reconstruction using Recurrent Stacked Back Projection
Wenrui Li, Gregery T. Buzzard, Charles A. Bouman
Iterative Reconstruction Fast Reconstruction Stacked Autoencoder Learning Based Reconstruction Sparse View CT Reconstruction

Stacked Autoencoder

Papers

Improving Arabic Multi-Label Emotion Classification using Stacked Embeddings and Hybrid Loss Function

Towards an Accessible and Rapidly Trainable Rhythm Sequencer Using a Generative Stacked Autoencoder

SANGRIA: Stacked Autoencoder Neural Networks with Gradient Boosting for Indoor Localization

Ransomware detection using stacked autoencoder for feature selection

AntiPhishStack: LSTM-based Stacked Generalization Model for Optimized Phishing URL Detection

Stacked Autoencoder Based Feature Extraction and Superpixel Generation for Multifrequency PolSAR Image Classification

VISU at WASSA 2023 Shared Task: Detecting Emotions in Reaction to News Stories Leveraging BERT and Stacked Embeddings

DSARSR: Deep Stacked Auto-encoders Enhanced Robust Speaker Recognition

Localisation of Mammographic masses by Greedy Backtracking of Activations in the Stacked Auto-Encoders

Health Monitoring of Movement Disorder Subject based on Diamond Stacked Sparse Autoencoder Ensemble Model

A new Stack Autoencoder: Neighbouring Sample Envelope Embedded Stack Autoencoder Ensemble Model

Removing Radio Frequency Interference from Auroral Kilometric Radiation with Stacked Autoencoders

Boosting the Discriminant Power of Naive Bayes

Anomaly Detection for Unmanned Aerial Vehicle Sensor Data Using a Stacked Recurrent Autoencoder Method with Dynamic Thresholding

Learning Physics-Informed Neural Networks without Stacked Back-propagation

Combining Varied Learners for Binary Classification using Stacked Generalization

Stacked Generative Machine Learning Models for Fast Approximations of Steady-State Navier-Stokes Equations

Sparse-View CT Reconstruction using Recurrent Stacked Back Projection