Jia Yan
Orcid: 0000-0001-8012-5097
According to our database1,
Jia Yan
authored at least 29 papers
between 2012 and 2025.
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Bibliography
2025
Improving E-Nose Performance: A Novel ELM-Based Dual-Level Joint Domain Adaptation Method for Sensor Drift Data.
IEEE Trans. Instrum. Meas., 2025
LRCTNet: A lightweight rectal cancer T-staging network based on knowledge distillation via a pretrained swin transformer.
Biomed. Signal Process. Control., 2025
2024
Performance Improvement of Multisensor Systems Using Autocompensation Strategy-Based LSTM.
IEEE Trans. Instrum. Meas., 2024
A novel twin-center intuitionistic fuzzy large margin classifier with unified pinball loss for improving the performance of E-noses system.
Expert Syst. Appl., 2024
A multilevel interleaved group attention-based convolutional network for gas detection via an electronic nose system.
Eng. Appl. Artif. Intell., 2024
Identification of Varieties of Agricultural Products Based on a Machine Olfactory System and a Lightweight Multiscale Convolutional Neural Network.
Proceedings of the 2024 IEEE SENSORS, Kobe, Japan, October 20-23, 2024, 2024
2023
IEEE Trans. Syst. Man Cybern. Syst., December, 2023
M<sup>2</sup>FL-CCC: Multibranch Multilayer Feature Leaning and Comprehensive Classification Criterion for Gas Sensor Drift Compensation.
IEEE Trans. Instrum. Meas., 2023
A convolutional neural network model for T-stage prediction of rectal cancer using CT images.
Proceedings of the IEEE International Symposium on Medical Measurements and Applications, 2023
A Double-Level Interleaved Group Convolutional Network in the Frequency Domain for E-Nose Gas Recognition.
Proceedings of the 2023 IEEE SENSORS, Vienna, Austria, October 29 - Nov. 1, 2023, 2023
2022
Subspace alignment based on an extreme learning machine for electronic nose drift compensation.
Knowl. Based Syst., 2022
2021
Local Manifold Embedding Cross-Domain Subspace Learning for Drift Compensation of Electronic Nose Data.
IEEE Trans. Instrum. Meas., 2021
TDACNN: Target-domain-free Domain Adaptation Convolutional Neural Network for Drift Compensation in Gas Sensors.
CoRR, 2021
2020
A Drift-Compensating Novel Deep Belief Classification Network to Improve Gas Recognition of Electronic Noses.
IEEE Access, 2020
2018
Feature Extraction of Electronic Nose Signals Using QPSO-Based Multiple KFDA Signal Processing.
Sensors, 2018
Enhancing the Discrimination Ability of a Gas Sensor Array Based on a Novel Feature Selection and Fusion Framework.
Sensors, 2018
Proceedings of the Advances in Neural Networks - ISNN 2018, 2018
2017
A Novel Extreme Learning Machine Classification Model for e-Nose Application Based on the Multiple Kernel Approach.
Sensors, 2017
Feature extraction of electronic nose for classification of indoor pollution gases based on kernel entropy component analysis.
Int. J. Intell. Syst. Technol. Appl., 2017
2016
A Novel Optimization Technique to Improve Gas Recognition by Electronic Noses Based on the Enhanced Krill Herd Algorithm.
Sensors, 2016
Sensors, 2016
A Novel Pre-Processing Technique for Original Feature Matrix of Electronic Nose Based on Supervised Locality Preserving Projections.
Sensors, 2016
Sensors, 2016
A Novel Semi-Supervised Method of Electronic Nose for Indoor Pollution Detection Trained by M-S4VMs.
Sensors, 2016
2015
A Novel Feature Extraction Approach Using Window Function Capturing and QPSO-SVM for Enhancing Electronic Nose Performance.
Sensors, 2015
An Enhanced Quantum-Behaved Particle Swarm Optimization Based on a Novel Computing Way of Local Attractor.
Inf., 2015
2012
A PSO-SVM Method for Parameters and Sensor Array Optimization in Wound Infection Detection based on Electronic Nose.
J. Comput., 2012
Classification of Electronic Nose Data in Wound Infection Detection Based on PSO-SVM Combined with Wavelet Transform.
Intell. Autom. Soft Comput., 2012