Fast environmental sound classification based on resource adaptive convolutional neural network

HIGHLIGHTS

• who: Zheng Fang from the CollegeOcean University have published the research: Fast environmental sound classification based on resource adaptive convolutional neural network, in the Journal: Scientific Reports Scientific Reports of 17/09/2021
• what: The authors propose a lightweight resource adaptive convolutional neural_network (RACNN). The authors propose the RAC module. Although the RAC module can simply upgrade the existing CNN, to better extract abstract features for classification operations, the authors propose an efficient feature extraction block-RAC block based on the RAC module, and build RACNN by simply stacking RAC block.
• how: | 1 . . .
  

   

  

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