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A Deep Forest-Based Fault Diagnosis Scheme for Electronics-Rich Analog Circuit Systems Journal article
Jia, Z., Liu, Z.B., Gan, Y.F., Vong, C. M.. A Deep Forest-Based Fault Diagnosis Scheme for Electronics-Rich Analog Circuit Systems[J]. IEEE Transactions on Industrial Electronics (SCI-E), 2021, 10087-10096.
Authors:  Jia, Z.;  Liu, Z.B.;  Gan, Y.F.;  Vong, C. M.
Favorite |   IF:7.5/8.0 | Submit date：2022/08/09
Analog circuits  deep forest (DF)  diagnosis  failure  fault  
An Inverse-Free and Scalable Sparse Bayesian Extreme Learning Machine for Classification Problems Journal article
Luo, J.H., Vong, C. M., Liu, Z.B., Chen, C.Q.. An Inverse-Free and Scalable Sparse Bayesian Extreme Learning Machine for Classification Problems[J]. IEEE Acess (SCI-E), 2021, 1-9.
Authors:  Luo, J.H.;  Vong, C. M.;  Liu, Z.B.;  Chen, C.Q.
Favorite |   IF:3.4/3.7 | Submit date：2022/08/09
Inverse-free  quasi-Newton method  sparse Bayesian extreme learning machine  large classification  sparse model  
Supervised Extreme Learning Machine-Based Auto-Encoder for Discriminative Feature Learning Journal article
Du, J., Vong, C. M., Chen, C.Q., Liu, P., Liu, Z.B.. Supervised Extreme Learning Machine-Based Auto-Encoder for Discriminative Feature Learning[J]. IEEE Access (SCI-E), 2019, 11700-11709.
Authors:  Du, J.;  Vong, C. M.;  Chen, C.Q.;  Liu, P.;  Liu, Z.B.
Favorite |   IF:3.4/3.7 | Submit date：2022/08/09
Extreme Learning Machine  Elm Based Auto-encoder  Supervised Elm-ae  Discriminative Data Representation  Multi-layer Perceptron  
3D2SeqViews: Aggregating Sequential Views for 3D Global Feature Learning by CNN With Hierarchical Attention Aggregation Journal article
Han, Z.Z., Lu, H.L., Liu, Z.B., Vong, C. M., Liu, Y.S., Zwicker, M., Han, J.W., Chen, C. L. P.. 3D2SeqViews: Aggregating Sequential Views for 3D Global Feature Learning by CNN With Hierarchical Attention Aggregation[J]. IEEE Transactions on Image Processing (SCI-E), 2019, 3986-3999.
Authors:  Han, Z.Z.;  Lu, H.L.;  Liu, Z.B.;  Vong, C. M.;  Liu, Y.S.; et al.
Favorite |   IF:10.8/12.1 | Submit date：2022/08/09
3D global feature learning  view aggregation  sequential views  hierarchical attention aggregation  CNN  
Real-Time Response-Based Fault Analysis and Prognostics Techniques of Nonisolated DC–DC Converters Journal article
Jia, Z., Liu, Z.B., Vong, C. M., Liu, X.. Real-Time Response-Based Fault Analysis and Prognostics Techniques of Nonisolated DC–DC Converters[J]. IEEE Access (SCI-E), 2019, 67996-68009.
Authors:  Jia, Z.;  Liu, Z.B.;  Vong, C. M.;  Liu, X.
Favorite |   IF:3.4/3.7 | Submit date：2022/08/09
DC-DC converter  fault analysis  fault identi fication  failure prognosis  exemplar-based conditional particle filter  
Capturing High-Discriminative Fault Features for Electronics-Rich Analog System via Deep Learning Journal article
Liu, Z.B., Jia, Z., Vong, C. M., Bu, S.H., Han, J.W., Tang, X.J.. Capturing High-Discriminative Fault Features for Electronics-Rich Analog System via Deep Learning[J]. IEEE Transactions on Industrial Informatics (SCI-E), 2017, 1213-1226.
Authors:  Liu, Z.B.;  Jia, Z.;  Vong, C. M.;  Bu, S.H.;  Han, J.W.; et al.
Favorite |   IF:11.7/11.4 | Submit date：2022/08/09
Analog circuits  deep belief network  deep learning  diagnosis  failure  fault  restricted Boltzmann machines.  
BoSCC: Bag of Spatial Context Correlations for Spatially Enhanced 3D Shape Representation Journal article
Han, Z.H., Liu, Z.B., Vong, C. M., Liu, Y.S., Bu, S.H., Han, J.W., Chen, C. L.. BoSCC: Bag of Spatial Context Correlations for Spatially Enhanced 3D Shape Representation[J]. IEEE Transactions on Image Processing (SCI-E), 2017, 3707-3720.
Authors:  Han, Z.H.;  Liu, Z.B.;  Vong, C. M.;  Liu, Y.S.;  Bu, S.H.; et al.
Favorite |   IF:10.8/12.1 | Submit date：2022/08/09
Bag of spatial context correlations  Spatial context correlation  Spatial context  3D shape representations.  
Fast discharge and high energy density of nanocomposite capacitors using Ba0.6Sr0.4TiO3 nanofibers Journal article
Pan Z.B., Yao L.M., Zhai J.W., Liu S.H., Yang K., Wang H.T., Liu J.H.. Fast discharge and high energy density of nanocomposite capacitors using Ba0.6Sr0.4TiO3 nanofibers[J]. Ceramics International, 2016, 42(13), 14667.
Authors:  Pan Z.B.;  Yao L.M.;  Zhai J.W.;  Liu S.H.;  Yang K.; et al.
Favorite | TC[WOS]:97 TC[Scopus]:99 | Submit date：2018/10/30
Ba0.6sr0.4tio3 Nanofibers  Capacitor  Energy Density  Nanocomposites  Poly(Vinylidene Fluoride)