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Rethinking Class Activation Maps for Segmentation: Revealing Semantic Information in Shallow Layers by Reducing Noise
A major limitation to the performance of the class activation maps is the small spatial resolution of the feature maps in the last layer of the convolutional neural network.
SAL-CNN: Estimate the Remaining Useful Life of Bearings Using Time-frequency Information
In modern industrial production, the prediction ability of the remaining useful life (RUL) of bearings directly affects the safety and stability of the system.
Training Neural Networks for Solving 1-D Optimal Piecewise Linear Approximation
Our main contributions are that we propose the theorems to characterize the optimal solution of the PWLA problem and present the LNN method for solving it.
How to Explain Neural Networks: an Approximation Perspective
The lack of interpretability has hindered the large-scale adoption of AI technologies.
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