Checkerboard Dropout: A Structured Dropout With Checkerboard Pattern for Convolutional Neural Networks

Checkerboard Dropout: A Structured Dropout With Checkerboard Pattern for Convolutional Neural Networks

Dropout is adopted in many state-of-the-art Deep Neural Networks (DNNs) to ease the overfitting problem by randomly removing features from feature maps. However, previous studies show the limitations of dropout application to Convolutional Neural Networks (CNNs) due to an increase in spatial correla...

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Detaylı Bibliyografya
Asıl Yazarlar: Khanh-Binh Nguyen, Jaehyuk Choi, Joon-Sung Yang
Materyal Türü: Makale
Dil:English
Baskı/Yayın Bilgisi: IEEE 2022-01-01
Seri Bilgileri:IEEE Access
Konular:
Checkerboard
deep neural networks
dropout
overfitting
spatial correlation
computer vision
Online Erişim:https://ieeexplore.ieee.org/document/9828384/

Internet

https://ieeexplore.ieee.org/document/9828384/

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