Chinese Character Image Clustering and Classification Based on Object Embedding Model (Student Abstract)

AAAI 2021 pp. 15913-15914

doi:10.1609/AAAI.V35I18.17953 /aaai/2021/wang2021aaai-chinese/

Abstract

We proposed Image2Vec, an unsupervised algorithm that learns feature representations for variable-size pieces of Chinese character images.

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Cite

Text

Wang et al. "Chinese Character Image Clustering and Classification Based on Object Embedding Model (Student Abstract)." AAAI Conference on Artificial Intelligence, 2021. doi:10.1609/AAAI.V35I18.17953

Markdown

[Wang et al. "Chinese Character Image Clustering and Classification Based on Object Embedding Model (Student Abstract)." AAAI Conference on Artificial Intelligence, 2021.](https://mlanthology.org/aaai/2021/wang2021aaai-chinese/) doi:10.1609/AAAI.V35I18.17953

BibTeX

@inproceedings{wang2021aaai-chinese,
  title     = {{Chinese Character Image Clustering and Classification Based on Object Embedding Model (Student Abstract)}},
  author    = {Wang, Mengting and Liang, Xun and Xue, Yang},
  booktitle = {AAAI Conference on Artificial Intelligence},
  year      = {2021},
  pages     = {15913-15914},
  doi       = {10.1609/AAAI.V35I18.17953},
  url       = {https://mlanthology.org/aaai/2021/wang2021aaai-chinese/}
}