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Minimum-risk training for semi-Markov conditional random fields with application to handwritten Chinese/Japanese text recognition.

, , , , и . Pattern Recognit., 47 (5): 1904-1916 (2014)

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Другие публикации лиц с тем же именем

A Robust Model for On-line Handwritten Japanese Text Recognition., , , и . DRR, том 7247 из SPIE Proceedings, стр. 72470B. SPIE, (2009)Landmark perturbation-based data augmentation for unconstrained face recognition., , , , и . Signal Process. Image Commun., (2016)Spatio-Temporal Attention Graph for Monocular 3d Human Pose Estimation., , , , и . ICIP, стр. 1231-1235. IEEE, (2022)Temporal Pyramid Transformer with Multimodal Interaction for Video Question Answering., , , , и . CoRR, (2021)Effect of Improved Path Evaluation for On-line Handwritten Japanese Text Recognition., , , и . ICDAR, стр. 516-520. IEEE Computer Society, (2009)Online Handwritten Japanese Character String Recognition Incorporating Geometric Context., , , , и . ICDAR, стр. 48-52. IEEE Computer Society, (2007)Handwritten Chinese/Japanese Text Recognition Using Semi-Markov Conditional Random Fields., , , , и . IEEE Trans. Pattern Anal. Mach. Intell., 35 (10): 2413-2426 (2013)Bootstrapping Joint Bayesian model for robust face verification., , , , и . ICB, стр. 1-6. IEEE, (2016)Keyword spotting in handwritten chinese documents using semi-markov conditional random fields., , и . Eng. Appl. Artif. Intell., (2017)An approach for real-time recognition of online Chinese handwritten sentences., , и . Pattern Recognit., 45 (10): 3661-3675 (2012)