Comparison of state-of-the-art deep learning APIs for image multi-label classification using semantic metrics

@article{Kubany2020ComparisonOS,
  title={Comparison of state-of-the-art deep learning APIs for image multi-label classification using semantic metrics},
  author={Adam Kubany and Shimon Ben Ishay and Ruben-sacha Ohayon and Armin Shmilovici and Lior Rokach and Tomer Doitshman},
  journal={Expert Syst. Appl.},
  year={2020},
  volume={161},
  pages={113656}
}
Abstract Image understanding heavily relies on accurate multi-label classification. In recent years, deep learning algorithms have become very successful for such tasks, and various commercial and open-source APIs have been released for public use. However, these APIs are often trained on different datasets, which, besides affecting their performance, might pose a challenge to their performance evaluation. This challenge concerns the different object-class dictionaries of the APIs’ training… 
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