Concepedia

Author

Jing Li

Nanjing Audit UniversityORCID

Also Known As

Jing Li, Li Jing

27

Publications

1.2K

Citations

8

H-Index

37

Concepts

All Affiliations

Nanjing Audit UniversitySoutheast UniversityChina University of Mining and TechnologyMassachusetts Institute of Technology
JL

About

Jing Li is an author at Nanjing Audit University specializing in engineering, pattern recognition, and image analysis.

Top Concepts

#ConceptH-IndexPublicationsCitations

1

Engineering

6

6

1.1K

2

Data Science

3

3

194

3

Computer Science

2

2

146

4

Applied Physics

1

1

891

5

Civil Engineering

1

1

48

Jing Li

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8

Publications

1.2K

Citations

8

H-Index

YearCitations

Nanophotonic particle simulation and inverse design using artificial neural networks

John Peurifoy, Yichen Shen, Jing Li,

Science Advances

2018

891

Multisource domain factorization network for cross-domain fault diagnosis of rotating machinery: An unsupervised multisource domain adaptation method

Yaowei Shi, Aidong Deng, Xue Ding,

Mechanical Systems and Signal Processing

2021

74

Domain Transferability-Based Deep Domain Generalization Method Towards Actual Fault Diagnosis Scenarios

Yaowei Shi, Aidong Deng, Minqiang Deng,

IEEE Transactions on Industrial Informatics

2022

72

Multi-Resolution Feature Fusion model for coal rock burst hazard recognition based on Acoustic Emission data

Jing Li, Jianhua Yue, Yong Yang,

Measurement

2017

48

Mine Water Inrush Sources Online Discrimination Model Using Fluorescence Spectrum and CNN

Yong Yang, Jianhua Yue, Jing Li,

IEEE Access

2018

28

On-Line Seam Detection in Rolling Processes Using Snake Projection and Discrete Wavelet Transform

Jing Li, Jianjun Shi, Tzyy-Shuh Chang

Journal of Manufacturing Science and Engineering

2007

24

Transforming the Open Set Into a Pseudo-Closed Set: A Regularized GAN for Domain Adaptation in Open-Set Fault Diagnosis

Yang Liu, Aidong Deng, Minqiang Deng,

IEEE Transactions on Instrumentation and Measurement

2023

18

Integration of Neural Network-Based Symbolic Regression in Deep Learning for Scientific Discovery

Samuel Kim, Peter Y. Lu, Srijon Mukherjee,

IEEE Transactions on Neural Networks and Learning Systems

2020

17

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