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First Power Linear Unit with Sign

arXiv 2111.14349 ↗First posted 29 Nov 2021cs.CVcited by 0

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Abstract (arXiv)

This paper proposes a novel and insightful activation method termed FPLUS, which exploits mathematical power function with polar signs in form. It is enlightened by common inverse operation while endowed with an intuitive meaning of bionics. The formulation is derived theoretically under conditions of some prior knowledge and anticipative properties, and then its feasibility is verified through a series of experiments using typical benchmark datasets, whose results indicate our approach owns superior competitiveness among numerous activation functions, as well as compatible stability across many CNN architectures. Furthermore, we extend the function presented to a more generalized type called PFPLUS with two parameters that can be fixed or learnable, so as to augment its expressive capacity, and outcomes of identical tests validate this improvement.

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References · 25

  1. 2015Deep Residual Learning for Image Recognitioncited by 51,809
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  12. 2015BinaryConnect: Training Deep Neural Networks with binary weights during propagationscited by 571
13 more
  1. 2015Empirical Evaluation of Rectified Activations in Convolutional Networkcited by 515
  2. 2013Maxout Networkscited by 186
  3. 2017Searching for Activation Functionscited by 158
  4. 2019Mish: A Self Regularized Non-Monotonic Activation Functioncited by 141
  5. 2016Understanding and Improving Convolutional Neural Networks via Concatenated Rectified Linear Unitscited by 86
  6. 2017Continuously Differentiable Exponential Linear Unitscited by 73
  7. 2020Dynamic ReLUcited by 55
  8. 2016Noisy Activation Functionscited by 53
  9. 2016Parametric Exponential Linear Unit for Deep Convolutional Neural Networkscited by 32
  10. 2020Activate or Not: Learning Customized Activationcited by 21
  11. 2018The Quest for the Golden Activation Functioncited by 14
  12. 2020Funnel Activation for Visual Recognitioncited by 9
  13. 2018Deep learning improved by biological activation functionscited by 3

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