Nov. 15, 2022, 2:11 a.m. | Hyebin Kwon, Joungbin An, Dongwoo Lee, Won-Yong Shin

cs.LG updates on arXiv.org arxiv.org

Considerable research attention has been paid to table detection by
developing not only rule-based approaches reliant on hand-crafted heuristics
but also deep learning approaches. Although recent studies successfully perform
table detection with enhanced results, they often experience performance
degradation when they are used for transferred domains whose table layout
features might differ from the source domain in which the underlying model has
been trained. To overcome this problem, we present DATa, a novel Domain
Adaptation-aided deep Table detection method that …

arxiv data detection domain adaptation table table detection

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