An Enhanced Framework of Generative Adversarial Networks (EF-GANs) for Environmental Microorganism Image Augmentation With Limited Rotation-Invariant Training Data

An Enhanced Framework of Generative Adversarial Networks (EF-GANs) for Environmental Microorganism Image Augmentation With Limited Rotation-Invariant Training Data

The main obstacle to image augmentation with Generative Adversarial Networks (GANs) is the need for a large amount of training data, but this is difficult for small datasets like Environmental Microorganisms (EMs). EM image analysis plays a vital role in environmental monitoring and protection, but...

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Bibliographic Details
Main Authors: Hao Xu, Chen Li, Md Mamunur Rahaman, Yudong Yao, Zihan Li, Jinghua Zhang, Frank Kulwa, Xin Zhao, Shouliang Qi, Yueyang Teng
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Access
Subjects:
Image augmentation
environmental microorganism
microscopic image
small dataset
generative adversarial networks
image analysis
Online Access:https://ieeexplore.ieee.org/document/9223631/

Internet

https://ieeexplore.ieee.org/document/9223631/

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