Titlebook: Document Analysis and Recognition - ICDAR 2024; 18th International C Elisa H. Barney Smith,Marcus Liwicki,Liangrui Peng Conference proceedi

召喚

書目名稱Document Analysis and Recognition - ICDAR 2024影響因子(影響力)




書目名稱Document Analysis and Recognition - ICDAR 2024影響因子(影響力)學(xué)科排名




書目名稱Document Analysis and Recognition - ICDAR 2024網(wǎng)絡(luò)公開度




書目名稱Document Analysis and Recognition - ICDAR 2024網(wǎng)絡(luò)公開度學(xué)科排名




書目名稱Document Analysis and Recognition - ICDAR 2024被引頻次




書目名稱Document Analysis and Recognition - ICDAR 2024被引頻次學(xué)科排名




書目名稱Document Analysis and Recognition - ICDAR 2024年度引用




書目名稱Document Analysis and Recognition - ICDAR 2024年度引用學(xué)科排名




書目名稱Document Analysis and Recognition - ICDAR 2024讀者反饋




書目名稱Document Analysis and Recognition - ICDAR 2024讀者反饋學(xué)科排名

SLUMP

Geometric-Aware Control in?Diffusion Model for?Handwritten Chinese Font Generatione control process. Third, the geometric information such as the corner points of a target character is utilized to weight the image reconstruction loss function for better control of character shape. The effectiveness of the proposed method for handwritten Chinese font generation is validated on the

巨碩

Learning to?Kern: Set-Wise Estimation of?Optimal Letter Spaceertain font. Among the two models, the set-wise model is not only more efficient but also more accurate because its internal self-attention mechanism allows for more consistent kerning for all letters. Experimental results on about 2500 Google fonts and their quantitative and qualitative analyses sh

LURE

KEGEL

信條

信條

Handwritten Document Recognition Using Pre-trained Vision Transformersearch, implementing freezing strategies, utilizing gradient accumulation, and employing hard negative mining techniques. This analysis demonstrates that our proposed efficient fine-tuning workflow significantly mitigates error rates and enhances inference speed, surpassing state-of-the-art results a

BLUSH

Janus-Faced Handwritten Signature Attack: A?Clash Between a?Handwritten Signature Duplicator and?a?Whe test stage. These profiles advance the threat level to the SigmML verifier by refining the output of the duplicator with a quality control mechanism which intuitively adapts the a-priori knowledge?of the intra-variability of each writer. In our experiments,?we considered signatures written in var

Irrigate

Lumbar-Spine