Search Results - Fully connected sparse autoencoder

A deep learning algorithm using a fully connected sparse autoencoder neural network for landslide susceptibility prediction

Authors: Faming Huang Jing Zhang Chuangbing Zhou et al.

Contributors: Faming Huang Jing Zhang Chuangbing Zhou et al.

Source: Landslides. 17:217-229

Subject Terms: back-propagation neural network, landslide susceptibility prediction, deep learning, support vector machine, fully connected sparse autoencoder, 01 natural sciences, 0105 earth and related environmental sciences

Access URL: https://link.springer.com/article/10.1007/s10346-019-01274-9

A deep learning algorithm using a fully connected sparse autoencoder neural network for landslide susceptibility prediction

Authors: Huang, Faming Zhang, Jing Zhou, Chuangbing et al.

Contributors: Huang, Faming Zhang, Jing Zhou, Chuangbing et al.

Subject Terms: landslide susceptibility prediction, deep learning, fully connected sparse autoencoder, support vector machine, back-propagation neural network

Relation: Landslides Vol. 17, Issue 1, p. 217-229; http://hdl.handle.net/1959.13/1424739; uon:38139

Availability: http://hdl.handle.net/1959.13/1424739

Electroencephalogram Sensor Data Compression Using an Asymmetrical Sparse Autoencoder with a Discrete Cosine Transform Layer

Authors: Zhu, Xin Pan, Hongyi Rong, Shuaiang et al.

Source: ICASSP 2024 - 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). :2160-2164

Subject Terms: Signal Processing (eess.SP), FOS: Computer and information sciences, Computer Science - Machine Learning, Artificial Intelligence (cs.AI), Computer Science - Artificial Intelligence, FOS: Electrical engineering, electronic engineering, information engineering, 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology, Electrical Engineering and Systems Science - Signal Processing, Machine Learning (cs.LG)

Access URL: http://arxiv.org/abs/2309.12201

XAI-DSCSA: explainable-AI-based deep semi-supervised convolutional sparse autoencoder for facial expression recognition

Authors: M. Mohana P. Subashini George Ghinea

Source: Signal, Image and Video Processing. 19

Subject Terms: autoencoder, semi-supervised learning, convolutional sparse autoencoder, facial expression recognition, feature representation, unsupervised learning

Access URL: https://bura.brunel.ac.uk/handle/2438/31141

Electroencephalogram Sensor Data Compression Using An Asymmetrical Sparse Autoencoder With A Discrete Cosine Transform Layer

Authors: Zhu, Xin Pan, Hongyi Rong, Shuaiang et al.

Index Terms: Electrical Engineering and Systems Science - Signal Processing, Computer Science - Artificial Intelligence, Computer Science - Machine Learning, text

URL: http://arxiv.org/abs/2309.12201

XAI-DSCSA: explainable-AI-based deep semi-supervised convolutional sparse autoencoder for facial expression recognition.

Authors: Mohana, M. Subashini, P. Ghinea, George

Source: Signal, Image & Video Processing; May2025, Vol. 19 Issue 5, p1-18, 18p

Compressive Reconstruction Based on Sparse Autoencoder Network Prior for Single-Pixel Imaging.

Authors: Zeng, Hong Dong, Jiawei Li, Qianxi et al.

Source: Photonics; Oct2023, Vol. 10 Issue 10, p1109, 21p

Subject Terms: PIXELS, MULTICHANNEL communication, COMPRESSED sensing, FEATURE extraction, IMAGE reconstruction, LINEAR equations, INFORMATION networks

An attention mechanism and fully connected layer-based dual-branch network for bioluminescent tomographic reconstruction.

Authors: Wang, Lin Pan, Chenrui Zhao, Minghua et al.

Source: Journal of Innovative Optical Health Sciences; Jul2025, Vol. 18 Issue 4, p1-19, 19p

Compressive Reconstruction Based on Sparse Autoencoder Network Prior for Single-Pixel Imaging

Authors: Hong Zeng Jiawei Dong Qianxi Li et al.

Source: Photonics, Vol 10, Iss 10, p 1109 (2023)

Subject Terms: sparse autoencoder network prior, single-photon counting compressive imaging, single-pixel imaging, multi-channel prior, numerical gradient descent, Applied optics. Photonics, TA1501-1820

File Description: electronic resource

Relation: https://www.mdpi.com/2304-6732/10/10/1109; https://doaj.org/toc/2304-6732

Access URL: https://doaj.org/article/48f428c1b807403680477c220849c39b

ELECTROENCEPHALOGRAM SENSOR DATA COMPRESSION USING AN ASYMMETRICAL SPARSE AUTOENCODER WITH A DISCRETE COSINE TRANSFORM LAYER

Sensor-Driven Surrogate Modeling and Control of Nonlinear Dynamical Systems Using FAE-CAE-LSTM and Deep Reinforcement Learning

Authors: Kherad, M. Moayyedi, M. K. Fotouhi-Ghazvini, F. et al.

Source: Sensors. 25(16)

Subject Terms: Autoencoders, Control Of Dynamical Systems, Cyber-physical Systems, Deep Reinforcement Learning, Long Short-term Memory, Sensor-driven Modeling, Circular Cylinders, Computer Control Systems, Convolution, Dynamical Systems, Dynamics, Embedded Systems, Flow Control, Fuel Additives, Nonlinear Dynamical Systems, Real Time Control, Robust Control, Auto Encoders, Control Of Dynamical System, Cybe-physical Systems, High-dimensional, Higher-dimensional, Reinforcement Learning Agent, Reinforcement Learnings, Short Term Memory

File Description: print

Access URL: https://urn.kb.se/resolve?urn=urn:nbn:se:mdh:diva-73172
https://doi.org/10.3390/s25165149

EKAResNet: Enhancing ResNet with Kolmogorov–Arnold Network-Based Nonlinear Feature Mapping.

Authors: Dang, Zhiming Wu, Tonghua Zhang, Wulin et al.

Source: Computation; Nov2025, Vol. 13 Issue 11, p248, 15p

Subject Terms: DEEP learning, COMPUTER vision, ARTIFICIAL neural networks, IMAGE recognition (Computer vision)

Classification of Nonalcoholic Fatty Liver Grades using Pre-Trained Convolutional Neural Networks and a Random Forest Classifier on B-Mode Ultrasound Images.

Authors: Naderi Yaghouti, Amir Reza Shalbaf, Ahmad

Source: Journal of Biomedical Physics & Engineering; Oct2025, Vol. 15 Issue 5, p437-450, 14p

Subject Terms: NON-alcoholic fatty liver disease, CONVOLUTIONAL neural networks, ULTRASONIC imaging, FEATURE extraction, RANDOM forest algorithms, MACHINE learning

Stacked pruning sparse denoising autoencoder based intelligent fault diagnosis of rolling bearings.

Authors: Zhu, Haiping Cheng, Jiaxin Zhang, Cong et al.

Source: Applied Soft Computing. Mar2020, Vol. 88, pN.PAG-N.PAG. 1p.

Subject Terms: Fault diagnosis, Pruning, Knowledge transfer, Information networks, Intelligent transportation systems, Bears, Redundancy in engineering, Video coding

Learning the Structure of Auto-Encoding Recommenders

Authors: Khawar, Farhan Poon, Leonard Zhang, Nevin Lianwen

Index Terms: Collaborative Filtering, Shallow Networks., Sparse Autoencoder, Structure Learning, Wide Autoencoder, Conference paper

URL: http://repository.ust.hk/ir/Record/1783.1-104134
http://lbdiscover.ust.hk/uresolver?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rfr_id=info:sid/HKUST:SPI&rft.genre=article&rft.issn=&rft.volume=&rft.issue=&rft.date=2020&rft.spage=519&rft.aulast=Khawar&rft.aufirst=&rft.atitle=Learning%20the%20Structure%20of%20Auto-Encoding%20Recommenders&rft.title=WWW%20'20%3A%20Proceedings%20of%20The%20Web%20Conference%202020
http://www.scopus.com/record/display.url?eid=2-s2.0-85086570333&origin=inward
http://gateway.isiknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcAuth=LinksAMR&SrcApp=PARTNER_APP&DestLinkType=FullRecord&DestApp=WOS&KeyUT=000626273300047

Vocorder Device Validation in Clinical Settings - Continuous Monitoring of Individuals (Vocorder Clinical Validation-VCV) (VCV)

Authors: ETH Zurich (Switzerland) Institute of Communications and Computer Systems, Athens, Greece AIDEAS OU et al.

Contributors: ETH Zurich (Switzerland) Institute of Communications and Computer Systems, Athens, Greece AIDEAS OU et al.

Source: Vocorder Device Validation in Clinical Settings - Continuous Monitoring of Individuals (Vocorder Clinical Validation-VCV). This Clinical Study Will Explore the Correlation Analysis Between Volatile Organic Compounds (VOC) Profiles in Breath As Detected by the VOCORDER Breath Analyser and Electronic Medical Data As Collected by Medical Professionals. the Obtained Results Are Expected to Be Significant in Refining the Technology of Breath Analysis in the VOCORDER Breath Analyser for the Early Detection of Diseases of Interest.

ASD-SAENet: A Sparse Autoencoder, and Deep-Neural Network Model for Detecting Autism Spectrum Disorder (ASD) Using fMRI Data.

Authors: Almuqhim, Fahad Saeed, Fahad

Source: Frontiers in Computational Neuroscience; 4/8/2021, Vol. 15, pN.PAG-N.PAG, 10p

Subject Terms: AUTISM spectrum disorders, FUNCTIONAL magnetic resonance imaging, BRAIN imaging, NEURAL development, FEATURE extraction

NeuroFusionNet: cross-modal modeling from brain activity to visual understanding.

Authors: Lang, Kehan Fang, Jianwei Su, Guangyao

Source: Frontiers in Computational Neuroscience; 2025, p1-12, 12p

Subject Terms: COMPUTER vision, COGNITIVE computing, SIGNAL processing, MACHINE learning, DEEP learning

GEAR PITTING FAULT DIAGNOSIS USING RAW ACOUSTIC EMISSION SIGNAL BASED ON DEEP LEARNING.

Alternate Title: DIAGNOSTYKA PITTINGU KÓŁ ZĘBATYCH NA PODSTAWIE SUROWEGO SYGNAŁU EMISJI AKUSTYCZNEJ W OPARCIU O GŁĘBOKIE UCZENIE MASZYNOWE. (Polish)

Authors: Xueyi LI Jialin LI David HE et al.

Source: Maintenance & Reliability / Eksploatacja i Niezawodność; 2019, Vol. 21 Issue 3, p403-410, 8p

Subject Terms: DEEP learning, ACOUSTIC emission, FAULT diagnosis, RECURRENT neural networks, ARTIFICIAL neural networks, REINFORCEMENT learning

Deep learning genome-wide genetics through biregular sparse decoder layer: deriving new disease genetic associations and disease risk predictions

Authors: Gustafsson, M Dwivedi, S Hellberg, S et al.

Source: Research Square.

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