Titlebook: Document Analysis and Recognition – ICDAR 2021; 16th International C Josep Lladós,Daniel Lopresti,Seiichi Uchida Conference proceedings 202

畸齒矯正學(xué)

書目名稱Document Analysis and Recognition – ICDAR 2021影響因子(影響力)




書目名稱Document Analysis and Recognition – ICDAR 2021影響因子(影響力)學(xué)科排名




書目名稱Document Analysis and Recognition – ICDAR 2021網(wǎng)絡(luò)公開度




書目名稱Document Analysis and Recognition – ICDAR 2021網(wǎng)絡(luò)公開度學(xué)科排名




書目名稱Document Analysis and Recognition – ICDAR 2021被引頻次




書目名稱Document Analysis and Recognition – ICDAR 2021被引頻次學(xué)科排名




書目名稱Document Analysis and Recognition – ICDAR 2021年度引用




書目名稱Document Analysis and Recognition – ICDAR 2021年度引用學(xué)科排名




書目名稱Document Analysis and Recognition – ICDAR 2021讀者反饋




書目名稱Document Analysis and Recognition – ICDAR 2021讀者反饋學(xué)科排名

血友病

Document Analysis and Recognition – ICDAR 2021978-3-030-86337-1Series ISSN 0302-9743 Series E-ISSN 1611-3349

頭腦冷靜

光滑

Theranostics for Breast Cancer Stem Cellss, as encountered in social networks, for detection and recognition of scene text. The proposed classifier efficiently removes non-text images from consideration, thus allowing to apply the potentially computationally heavy scene text detection and OCR on only a fraction of the images..The proposed

Palate

vector

Translational Medicine Researchifficult to use rectangular bounding boxes to detect text locations accurately. To detect multi-oriented text, rotated bounding box-based methods have been explored as an alternative. However, they are not as accurate for scene text detection as rectangular bounding box-based methods. In this paper,

vector

Translational Research in Strokebased on abundant labeled data for model training. Obtaining text images is a relatively easy process, but labeling them is quite expensive. To alleviate the dependence on labeled data, semi-supervised learning which combines labeled and unlabeled data seems to be a reasonable solution, and is prove

音樂學(xué)者

口音在加重

Meager