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MSWNet: A visual deep machine learning method adopting transfer learning based upon ResNet 50 for municipal

Frontiers of Environmental Science & Engineering 2023, Volume 17, Issue 6, doi: 10.1007/s11783-023-1677-1

Abstract:

● MSWNet was proposed to classify municipal solid waste.

Keywords： Municipal solid waste sorting     Deep residual network     Transfer learning     Cyclic learning rate     Visualization    

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Modeling of oil near-infrared spectroscopy based on similarity and transfer learning algorithm

Yifei Wang, Kai Wang, Zhao Zhou, Wenli Du

Frontiers of Chemical Science and Engineering 2019, Volume 13, Issue 3,   Pages 599-607 doi: 10.1007/s11705-019-1807-2

Abstract: under different detection conditions, this paper discusses about the feasibility of the application of transferlearning algorithm and makes it possible that transfer learning can assist in rapid modeling using certainIn consideration of the requirement of transfer learning for certain similarity of different datasets, a transfer learning method based on local similarity feature selection is proposed.The effectiveness and application scope of the transfer modeling method under different similarity conditions

Keywords： near-infrared spectroscopy     transfer learning     similarity     modeling    

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A Robust Transfer Dictionary Learning Algorithm for Industrial Process Monitoring Article

Chunhua Yang, Huiping Liang, Keke Huang, Yonggang Li, Weihua Gui

Engineering 2021, Volume 7, Issue 9,   Pages 1262-1273 doi: 10.1016/j.eng.2020.08.028

Abstract: training data and online testing data that is induced by changeable operation environments, a robust transferdictionary learning (RTDL) algorithm is proposed in this paper for industrial process monitoring.The RTDL is a synergy of representative learning and domain adaptive transfer learning.training data and online testing data as the source domain and the target domain, respectively, in the transferlearning problem.

Keywords： Process monitoring     Multimode process     Dictionary learning     Transfer learning    

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Dynamic simulation of gas turbines via feature similarity-based transfer learning

Dengji ZHOU, Jiarui HAO, Dawen HUANG, Xingyun JIA, Huisheng ZHANG

Frontiers in Energy 2020, Volume 14, Issue 4,   Pages 817-835 doi: 10.1007/s11708-020-0709-9

Abstract: To tackle the issue, a novel transfer learning framework is proposed to transfer the knowledge from thewith steep slope signals is created based on physics equations and then a feature similarity-based learningMoreover, compared with the other classical transfer learning modes, the method proposed has the bestthe hyper parameters indicates that the method proposed is able to adaptively balance the weight of learning

Keywords： gas turbine     dynamic simulation     data-driven     transfer learning     feature similarity    

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A software defect prediction method with metric compensation based on feature selection and transferlearning Research Article

Jinfu CHEN, Xiaoli WANG, Saihua CAI, Jiaping XU, Jingyi CHEN, Haibo CHEN,caisaih@ujs.edu.cn

Frontiers of Information Technology & Electronic Engineering 2022, Volume 23, Issue 5,   Pages 715-731 doi: 10.1631/FITEE.2100468

Abstract: Cross-project software solves the problem of insufficient training data for traditional , and overcomes the challenge of applying models learned from multiple different source projects to target project. At the same time, two new problems emerge: (1) too many irrelevant and redundant features in the model training process will affect the training efficiency and thus decrease the prediction accuracy of the model; (2) the distribution of metric values will vary greatly from project to project due to the development environment and other factors, resulting in lower prediction accuracy when the model achieves cross-project prediction. In the proposed method, the Pearson method is introduced to address data redundancy, and the based technique is used to address the problem of large differences in data distribution between the source project and target project. In this paper, we propose a software method with based on and . The experimental results show that the model constructed with this method achieves better results on area under the receiver operating characteristic curve (AUC) value and F1-measure metric.

Keywords： Defect prediction     Feature selection     Transfer learning     Metric compensation    

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Two-level hierarchical feature learning for image classification Article

Guang-hui SONG,Xiao-gang JIN,Gen-lang CHEN,Yan NIE

Frontiers of Information Technology & Electronic Engineering 2016, Volume 17, Issue 9,   Pages 897-906 doi: 10.1631/FITEE.1500346

Abstract: In this paper, we propose a novel two-level hierarchical feature learning framework based on the deepFirst, the deep feature extractors of different levels are trained using the transfer learning methoddemonstrate that the expression ability of the deep features resulting from two-level hierarchical feature learning

Keywords： Transfer learning     Feature learning     Deep convolutional neural network     Hierarchical classification    

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Deep convolutional neural network for multi-level non-invasive tunnel lining assessment

Frontiers of Structural and Civil Engineering 2022, Volume 16, Issue 2,   Pages 214-223 doi: 10.1007/s11709-021-0800-2

Abstract: In a supervised learning framework, Ground Penetrating Radar (GPR) profiles and the revealed structural

Keywords： concrete structure     GPR     damage classification     convolutional neural network     transfer learning    

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Ensemble-transfer-learning-based channel parameter prediction in asymmetric massive MIMO systems Research Article

Zunwen HE, Yue LI, Yan ZHANG, Wancheng ZHANG, Kaien ZHANG, Liu GUO, Haiming WANG

Frontiers of Information Technology & Electronic Engineering 2023, Volume 24, Issue 2,   Pages 275-288 doi: 10.1631/FITEE.2200169

Abstract: In this paper we propose an ensemble-transfer-learning-based channel method for asymmetric massive MIMOAdditionally, the proposed instance-transfer-based method outperforms the method without transfer learning

Keywords： Asymmetric massive multiple-input multiple-output (MIMO) system     Channel model     Ensemble learning     Instancetransfer     Parameter prediction    

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Quantum security analysis of a lattice-basedoblivious transfer protocol Article

Mo-meng LIU, Juliane KRÄMER, Yu-pu HU, Johannes BUCHMANN

Frontiers of Information Technology & Electronic Engineering 2017, Volume 18, Issue 9,   Pages 1348-1369 doi: 10.1631/FITEE.1700039

Abstract: Because of the concise functionality of oblivious transfer (OT)protocols, they have been widely used(CRYPTO, 2008), which is universally composably secure under theassumption of learning with errors hardness

Keywords： Oblivious transfer     Post-quantum     Lattice-based     Learning with errors     Universally composable    

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Multi-View Point-Based Registration for Native Knee Kinematics Measurement with Feature Transfer Learning Article

Cong Wang, Shuaining Xie, Kang Li, Chongyang Wang, Xudong Liu, Liang Zhao, Tsung-Yuan Tsai

Engineering 2021, Volume 7, Issue 6,   Pages 881-888 doi: 10.1016/j.eng.2020.03.016

Abstract:

Deep-learning methods provide a promising approach for measuring in-vivoWe propose a feature-based transfer-learning method to extract features from fluoroscopic images.The proposed method provides a promising solution, using a learning-based registration method when only

Keywords： 2D–3D registration     Machine learning     Domain adaption     Point correspondence    

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Augmentation of natural convective heat transfer by acoustic cavitation

Jun CAI, Xiulan HUAI, Shiqiang LIANG, Xunfeng LI,

Frontiers in Energy 2010, Volume 4, Issue 3,   Pages 313-318 doi: 10.1007/s11708-009-0064-3

Abstract: experimental study was conducted to investigate the effects of acoustic cavitation on natural convective heat transferThe experimental results indicated that heat transfer could be enhanced by acoustic cavitation and had

Keywords： heat transfer enhancement     augmentation     acoustic cavitation     acoustic streaming     convective heat transfer    

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Effect of heat transfer space non-uniformity of combustion chamber components on in-cylinder heat transfer

Jizu LV, Minli BAI, Long ZHOU, Jian ZHOU,

Frontiers in Energy 2010, Volume 4, Issue 3,   Pages 392-401 doi: 10.1007/s11708-009-0066-1

Abstract: Based on the three-dimensional numerical simulation of the heat transfer of the coupled body, a coupledThe model was applied in the investigation of the influence of space non-uniformity in heat transferamong combustion chamber components on in-cylinder heat transfer.effect of wall temperature space non-uniform distribution of combustion chamber components on heat transferwall temperature space non-uniform distribution of combustion chamber components would influence heat transfer

Keywords： heat transfer     space non-uniformity     soot emission     in-cylinder     diesel    

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Experimental study of heat transfer coefficient with rectangular baffle fin of solar air heater

Foued CHABANE,Nesrine HATRAF,Noureddine MOUMMI

Frontiers in Energy 2014, Volume 8, Issue 2,   Pages 160-172 doi: 10.1007/s11708-014-0321-y

Abstract: The heat transfer coefficient between the absorber plate and air can be considerably increased by usingexperimental study has been conducted to investigate the effect of roughness and operating parameters on heat transferTo determine the enhancement in heat transfer and increment in thermal efficiency, the values of Nusselt

Keywords： Nusselt number     flow rate     heat transfer     heat transfer coefficient     thermal efficiency     forced convection    

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Heat transfer coefficient of wheel rim of large capacity steam turbines

SHI Jinyuan, DENG Zhicheng, YANG Yu, JUN Ganwen

Frontiers in Energy 2008, Volume 2, Issue 1,   Pages 20-24 doi: 10.1007/s11708-008-0015-4

Abstract: A way of calculating the overall equivalent heat transfer coefficient of wheel rims of large capacityThe method and formula to calculate the mean forced convection heat-transfer coefficient of the surfaceA fin heat transfer model was then used to calculate the equivalent heat transfer coefficient of theThe overall equivalent heat transfer coefficient of the wheel rim was then calculated using a cylindricalThe proposed method helps determine the heat transfer boundary conditions in finite element analyses

Keywords： convection heat-transfer     capacity     heat-transfer coefficient     bottom     transmission    

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A new heat transfer correlation for supercritical fluids

Yanhua YANG, Xu CHENG, Shanfang HUANG

Frontiers in Energy 2009, Volume 3, Issue 2,   Pages 226-232 doi: 10.1007/s11708-009-0022-0

Abstract: A new method of heat transfer prediction in supercritical fluids is presented.Assessment of qualitative behaviour of heat transfer is conducted based on existing test data and experiencesingle dimensionless number, the acceleration number, is introduced to correct the deviation of heat transferThe new correlation structure excludes direct dependence of heat transfer coefficient on wall surfaceComparison of various heat transfer correlations with the selected test data shows that the new correlation

Keywords： super critical fluids     heat transfer     circular tubes     prediction method    

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Title Author Date Type Operation

MSWNet: A visual deep machine learning method adopting transfer learning based upon ResNet 50 for municipal

Journal Article

Modeling of oil near-infrared spectroscopy based on similarity and transfer learning algorithm

Yifei Wang, Kai Wang, Zhao Zhou, Wenli Du

Journal Article

A Robust Transfer Dictionary Learning Algorithm for Industrial Process Monitoring

Chunhua Yang, Huiping Liang, Keke Huang, Yonggang Li, Weihua Gui

Journal Article

Dynamic simulation of gas turbines via feature similarity-based transfer learning

Dengji ZHOU, Jiarui HAO, Dawen HUANG, Xingyun JIA, Huisheng ZHANG

Journal Article

A software defect prediction method with metric compensation based on feature selection and transferlearning

Jinfu CHEN, Xiaoli WANG, Saihua CAI, Jiaping XU, Jingyi CHEN, Haibo CHEN,caisaih@ujs.edu.cn

Journal Article

Two-level hierarchical feature learning for image classification

Guang-hui SONG,Xiao-gang JIN,Gen-lang CHEN,Yan NIE

Journal Article

Deep convolutional neural network for multi-level non-invasive tunnel lining assessment

Journal Article

Ensemble-transfer-learning-based channel parameter prediction in asymmetric massive MIMO systems

Zunwen HE, Yue LI, Yan ZHANG, Wancheng ZHANG, Kaien ZHANG, Liu GUO, Haiming WANG

Journal Article

Quantum security analysis of a lattice-basedoblivious transfer protocol

Mo-meng LIU, Juliane KRÄMER, Yu-pu HU, Johannes BUCHMANN

Journal Article

Multi-View Point-Based Registration for Native Knee Kinematics Measurement with Feature Transfer Learning

Cong Wang, Shuaining Xie, Kang Li, Chongyang Wang, Xudong Liu, Liang Zhao, Tsung-Yuan Tsai

Journal Article

Augmentation of natural convective heat transfer by acoustic cavitation

Jun CAI, Xiulan HUAI, Shiqiang LIANG, Xunfeng LI,

Journal Article

Effect of heat transfer space non-uniformity of combustion chamber components on in-cylinder heat transfer

Jizu LV, Minli BAI, Long ZHOU, Jian ZHOU,

Journal Article

Experimental study of heat transfer coefficient with rectangular baffle fin of solar air heater

Foued CHABANE,Nesrine HATRAF,Noureddine MOUMMI

Journal Article

Heat transfer coefficient of wheel rim of large capacity steam turbines

SHI Jinyuan, DENG Zhicheng, YANG Yu, JUN Ganwen

Journal Article

A new heat transfer correlation for supercritical fluids

Yanhua YANG, Xu CHENG, Shanfang HUANG

Journal Article