A generative model of calligraphy based on image and human motion

Kobayashi, Ryotaro; Katsura, Seiichiro

doi:10.1016/j.precisioneng.2022.06.006

Cited by 4 publications

(1 citation statement)

References 12 publications

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“…Huda S proposed a calligraphy learning assistant system based on projection mapping to improve students' calligraphy learning efficiency and improve their calligraphy level [11]. Kobayashi et al based on DL, combined with image and human motion, then proposed a calligraphy generation method to realize automatic calligraphy writing [12]. Based on aesthetic psychology, Jin and others combined calligraphy and painting elements with cultural and creative products.…”

Section: Related Workmentioning

confidence: 99%

The Application of Intelligent Evaluation Method with Deep Learning in Calligraphy Teaching

Wang¹

2023

IJACSA

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Scientific and effective teaching quality evaluation (QE) is helpful to improve teaching mode and improve teaching quality. At present, calligraphy teaching (CT) QE methods are few in number and have poor evaluation effect. Aiming at these problems, deep learning (DL) is introduced to realize intelligent evaluation of CT quality. First, based on relevant research, the CTQE indicator system is constructed. Secondly, rough set and the principal component analysis (PCA) are used to reduce the dimension of the CTQE index system and extract four common factors. Then, the corresponding index data is input into the BP neural network (BPNN) model optimized by the improved sparrow search algorithm for fitting. Finally, combining the above contents, the improved sparrow search algorithm (ISSA) BPNN model is built to realize the intelligent evaluation of CT quality. The experimental results show that the loss value of ISSA-BPN model is 0.21, and the fitting degree of CT data is 0.953. The evaluation Accuracy is 95%, Precision is 0.945, Recall is 0.923, F1 is 0.942, and AUC is 0.967. These values are superior to the most advanced teaching QE model available. The SSA-BPNNCTQE model proposed in the study has excellent performance in CTQE. This is of positive significance to the improvement of teaching quality and students' calligraphy level.

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Section: Related Workmentioning

confidence: 99%