zggg1p / A-Domain-Adaption-Transfer-Learning-Bearing-Fault-Diagnosis-Model-Based-on-Wide-Convolution-Deep-Neu

Inspired by the idea of transfer learning, a combined approach is proposed. In the method, Deep Convolutional Neural Networks with Wide First-layer Kernel is used to extract features to classify the health conditions.

Date Created 2021-10-25 (3 years ago)
Commits 23 (last one 16 days ago)
Stargazers 113 (2 this week)
Watchers 2 (0 this week)
Forks 14
License unknown
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zggg1p/A-Domain-Adaption-Transfer-Learning-Bearing-Fault-Diagnosis-Model-Based-on-Wide-Convolution-Deep-Neu is also tagged with popular topics, for these it's ranked: deep-learning (#4,893/8777)

Other Information

zggg1p/A-Domain-Adaption-Transfer-Learning-Bearing-Fault-Diagnosis-Model-Based-on-Wide-Convolution-Deep-Neu has Github issues enabled, there is 1 open issue and 3 closed issues.

There have been 2 releases, the latest one was published on 2022-03-25 (2 years ago) with the name A Domain Adaption Transfer Learning Bearing Fault Diagnosis Model Based on Wide Convolution Deep Neural Network v2.0.

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The only known language in this repository is Python

PythonPython

updated: 2025-03-15 @ 07:00pm, id: 420853505 / R_kgDOGRW3AQ