Data Augmentation using Adversarial Networks for Tea Diseases Detection
نویسندگان
چکیده
منابع مشابه
Data Augmentation Generative Adversarial Networks
Effective training of neural networks requires much data. In the low-data regime, parameters are underdetermined, and learnt networks generalise poorly. Data Augmentation (Krizhevsky et al., 2012) alleviates this by using existing data more effectively. However standard data augmentation produces only limited plausible alternative data. Given there is potential to generate a much broader set of...
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ژورنال
عنوان ژورنال: Jurnal Elektronika dan Telekomunikasi
سال: 2020
ISSN: 2527-9955,1411-8289
DOI: 10.14203/jet.v20.29-35