Visual attentional-driven deep learning method for flower recognition

DOI10.3934/MBE.2021103zbMath1471.92221OpenAlexW3133682783MaRDI QIDQ1981181

Shuai Cao, Biao Song

Publication date: 10 September 2021

Published in: Mathematical Biosciences and Engineering (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.3934/mbe.2021103

zbMATH Keywords

feature extractiondeep learningattention learningflower recognition

Mathematics Subject Classification ID

Artificial neural networks and deep learning (68T07) Machine vision and scene understanding (68T45) Plant biology (92C80)

Uses Software

• Kaldi
• PyTorch
• PyTorch-Kaldi

Cites Work

• Improved multi-view GEPSVM via inter-view difference maximization and intra-view agreement minimization

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