JOURNAL ARTICLE

Personalized Font Generation using Deep Learning Neural Networks

Chirag S. DesaiDarsh PandyaAnsh KhatriNarayan Prajapati

Year: 2023 Journal:   International Journal for Research in Applied Science and Engineering Technology Vol: 11 (7)Pages: 1524-1533   Publisher: International Journal for Research in Applied Science and Engineering Technology (IJRASET)

Abstract

Abstract: Personalized font generation is an emerging technology that aims to create unique and customized fonts based on an individual’s preferences and characteristics. This process involves designing a font from scratch, including selecting the appropriate style, weight, and size. Personalized features such as letter shapes, ligatures, and kerning are then implemented to create a font that is unique to the individual. Personalized font generation has the potential to revolutionize the way we think about typography. By creating fonts that are tailored to an individual’s preferences, we can enhance the user experience and create more engaging and personalized content. This technology is particularly relevant in today’s digital age, where the use of typography is increasingly important in everything from social media posts to marketing materials. In summary, personalized font generation is a promising new technology that offers a unique and tailored typography experience. By combining traditional font design techniques with advanced technologies such as machine learning and artificial intelligence, we can create fonts that are truly one-of-a-kind and help to elevate our communication efforts.

Keywords:
Font Typography Computer science Process (computing) Personalization Multimedia Human–computer interaction Typeface Artificial intelligence World Wide Web Art

Metrics

1
Cited By
0.62
FWCI (Field Weighted Citation Impact)
10
Refs
0.68
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Web Data Mining and Analysis
Physical Sciences →  Computer Science →  Information Systems
Human Motion and Animation
Physical Sciences →  Engineering →  Control and Systems Engineering
Augmented Reality Applications
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
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