Výsledky vyhledávání - "multitask autoencoder"

Two-Phase Multitask Autoencoder-Based Deep Learning Framework for Subject-Independent EEG Motor Imagery Classification

Autoři: Changgyun Jin Andrew H. Song Seong-Eun Kim

Zdroj: IEEE Access, Vol 12, Pp 77356-77367 (2024)

Témata: subject-independent, 0301 basic medicine, 0303 health sciences, 03 medical and health sciences, motor imagery, deep learning, EEG, Electrical engineering. Electronics. Nuclear engineering, multitask autoencoder, Classification, TK1-9971

Přístupová URL adresa: https://doaj.org/article/e224854d86d643978058e2430c63f522

Adaptive Multitask Autoencoder-Based Hyperspectral Unmixing Exploiting Auxiliary Data via Graph Associations

Autoři: Jia Chen Jun Li Paolo Gamba

Zdroj: IEEE Transactions on Geoscience and Remote Sensing. 63:1-13

TWEN: EEG Emotion Recognition Model Based on Weakly Supervised Learning Framework with Two-Phase Multitask Autoencoder

Autoři: Taewan Kim ChangGyun Jin Seong-Eun Kim

Zdroj: 2024 15th International Conference on Information and Communication Technology Convergence (ICTC). :1494-1498

Multitask Autoencoder-Based Two-Phase Framework Using Multilevel Feature Fusion for EEG Emotion Recognition

Autoři: ChangGyun Jin ChanWoo Shin Hanul Kim a další

Zdroj: 2024 International Conference on Electronics, Information, and Communication (ICEIC). :1-3

Corrections to 'Adaptive Multitask Autoencoder-Based Hyperspectral Unmixing Exploiting Auxiliary Data via Graph Associations'

Autoři: Jia Chen Jun Li Paolo Gamba

Zdroj: IEEE Transactions on Geoscience and Remote Sensing. 63:1-1

Multitask Autoencoder Model for Recovering Human Poses

Autoři: Jun Yu Chaoqun Hong Yong Rui a další

Zdroj: IEEE Transactions on Industrial Electronics. 65:5060-5068

Témata: 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology

Přístupová URL adresa: https://dblp.uni-trier.de/db/journals/tie/tie65.html#YuHRT18
http://ieeexplore.ieee.org/document/8010362/
https://ieeexplore.ieee.org/document/8010362/
https://doi.org/10.1109/TIE.2017.2739691
https://opus.lib.uts.edu.au/handle/10453/123848

Multitask Autoencoder Model for Recovering Human Poses

Autoři: Yu, J Hong, C Rui, Y a další

Témata: Journal Article

URL: http://hdl.handle.net/10453/123848
IEEE Transactions on Industrial Electronics
10.1109/TIE.2017.2739691

Multitask Autoencoder Model for Recovering Human Poses.

Autoři: Yu, Jun Hong, Chaoqun Rui, Yong a další

Zdroj: IEEE Transactions on Industrial Electronics; Jun2018, Vol. 65 Issue 6, p5060-5068, 9p

Témata: ENCODING, ARTIFICIAL neural networks, DEEP learning, POSE estimation (Computer vision), PERFORMANCE evaluation

Data from Seoul National University of Science and Technology Update Knowledge in Engineering (Two-Phase Multitask Autoencoder-Based Deep Learning Framework for Subject-Independent EEG Motor Imagery Classification).

Zdroj: Health & Medicine Week. 6/21/2024, p1251-1251. 1p.

Direction-of-Arrival Estimation Based on Deep Neural Networks With Robustness to Array Imperfections.

Autoři: Liu, Zhang-Meng Zhang, Chenwei Yu, Philip S.

Zdroj: IEEE Transactions on Antennas & Propagation; Dec2018, Vol. 66 Issue 12, p7315-7327, 13p

Témata: DIRECTION of arrival estimation, ARTIFICIAL neural networks, SIGNAL processing, SUPERVISED learning, ANTENNA arrays

Deep Learning-Based Time Delay Estimation Using Ground Penetrating Radar.

Autoři: Lin, Feng Sun, Meng Mao, Shiyu a další

Zdroj: Electronics (2079-9292); May2023, Vol. 12 Issue 9, p2141, 10p

Témata: TIME delay estimation, GROUND penetrating radar, CIVIL engineering, NONDESTRUCTIVE testing, ELECTROMAGNETIC waves

A Review of Deep Learning for Biomedical Signals: Current Applications, Advancements, Future Prospects, Interpretation, and Challenges.

Autoři: Alqudah, Ali Mohammad Moussavi, Zahra

Zdroj: Computers, Materials & Continua; 2025, Vol. 83 Issue 3, p3753-3841, 89p

Témata: HEALTH Insurance Portability & Accountability Act, BIOMEDICAL signal processing, DEEP learning, RECURRENT neural networks, RECEIVER operating characteristic curves, ARTIFICIAL intelligence

Advances in Personalized Cancer Vaccine Development: AI Applications from Neoantigen Discovery to mRNA Formulation.

Autoři: Kong, Hyunseung

Zdroj: BioChem; Jun2025, Vol. 5 Issue 2, p5, 15p

Témata: CANCER vaccines, VACCINE development, MACHINE learning, ARTIFICIAL intelligence, GENE expression, T cell receptors, DEEP learning

Direction of Arrival (DOA) Estimation Using a Deep Unfolded Learned Iterative Shrinkage Thresholding Algorithm (LISTA) Network in a Non-Uniform Metasurface.

Autoři: Niu, Xinyi Su, Xiaolong He, Lida a další

Zdroj: Remote Sensing; Apr2025, Vol. 17 Issue 7, p1253, 18p

Témata: THRESHOLDING algorithms, COMPUTATIONAL complexity, ALGORITHMS, LOGIC, GENERALIZATION

Model-Driven Deep Neural Network for Enhancing Direction Finding with Commodity 5G gNodeB.

Autoři: Liu, Shengheng Mao, Zihuan Li, Xingkang a další

Zdroj: ACM Transactions on Sensor Networks; Mar2025, Vol. 21 Issue 2, p1-25, 25p

Témata: ARTIFICIAL neural networks, 5G networks, COMPUTER simulation, CALIBRATION

A comprehensive review of metasurface-assisted direction-of-arrival estimation.

Autoři: Huang, Min Li, Ruichen Zou, Yijun a další

Zdroj: Nanophotonics (21928606); Nov2024, Vol. 13 Issue 24, p4381-4396, 16p

Témata: DIRECTION of arrival estimation, PHASED array antennas, ARTIFICIAL intelligence, SIGNAL processing, ARRAY processing

Two-Dimensional Coherent Polarization–Direction-of-Arrival Estimation Based on Sequence-Embedding Fusion Transformer.

Autoři: Wu, Zihan Wang, Jun Zhou, Zhiquan

Zdroj: Remote Sensing; Nov2024, Vol. 16 Issue 21, p3977, 22p

Témata: CONVOLUTIONAL neural networks, NATURAL language processing, DATA mining, TRANSFORMER models, COVARIANCE matrices

Unsupervised machine learning model for detecting anomalous volumetric modulated arc therapy plans for lung cancer patients.

Autoři: Peng Huang Jiawen Shang Yuhan Fan a další

Zdroj: Frontiers in Big Data; 2024, p1-11, 11p

A combination of deep learning models and type-2 fuzzy for EEG motor imagery classification through spatiotemporal-frequency features.

Autoři: Jiang, Ensong Huang, Tangsen Yin, Xiangdong

Zdroj: Journal of Medical Engineering & Technology; Oct2024, Vol. 48 Issue 7, p262-275, 14p

Témata: BIOMEDICAL signal processing, ARTIFICIAL intelligence, MOTOR imagery (Cognition), OPTIMIZATION algorithms, DATABASES, DEEP learning

Deeply Supervised Multi-Task Autoencoder for Biological Brain Age estimation using three dimensional T$_1$-weighted magnetic resonance imaging

Autoři: Kanwal, Mehreen Son, Yunsik

Témata: FOS: Computer and information sciences, Artificial Intelligence (cs.AI), Artificial Intelligence, Computer Vision and Pattern Recognition (cs.CV), Image and Video Processing (eess.IV), FOS: Electrical engineering, electronic engineering, information engineering, Image and Video Processing, Computer Vision and Pattern Recognition

Přístupová URL adresa: http://arxiv.org/abs/2508.01565