- Path:
-
Fünfter Abschnitt. Verzeichniß der vorzüglichsten Gasthöfe und ihrer Besitzer
Periodical
- Title:
- Paladyn
- Publication:
-
Warsaw: De Gruyter
- Note:
- Gesehen am 03.01.22
- Open Access
- Namensnennung 4.0 International
- Archivierung/Langzeitarchivierung gewährleistet
- Scope:
- Online-Ressource
- ISSN:
- 2081-4836
- ZDB-ID:
-
2550006-5
- VÖBB-Katalog:
- 35326634
- Keywords:
- Zeitschrift
- Classification:
- Informatik
- Collection:
- Informatik
- Copyright:
- Rights reserved
- Accessibility:
- Eingeschränkter Zugang mit Nutzungsbeschränkungen
- Title:
- Paladyn
- Publication:
-
Warsaw: De Gruyter
- Note:
- Gesehen am 03.01.22
- Open Access
- Namensnennung 4.0 International
- Archivierung/Langzeitarchivierung gewährleistet
- Scope:
- Online-Ressource
- ISSN:
- 2081-4836
- ZDB-ID:
-
2550006-5
- VÖBB-Katalog:
- 35326634
- Keywords:
- Zeitschrift
- Classification:
- Informatik
- Collection:
- Informatik
- Copyright:
- Rights reserved
- Accessibility:
- Eingeschränkter Zugang mit Nutzungsbeschränkungen
Article
- Title:
- Creative design of digital media art based on computer visual aids
- Publication:
-
Warsaw: De Gruyter, 2025
- Language:
- English
- Information:
- Abstract: In the digital age, artistic creation needs to strike a balance between automation and personalization. This study proposes an innovative model that integrates generative adversarial networks, computer vision, and personalized adjustment technology. Through multistage iterative optimization, efficient art generation and personalized style customization are achieved. The model uses an automated generation module to generate a draft and guides the conditional vector to achieve fine-grained adjustment of the image so that the work maintains both technical innovation and the artist’s unique style. The model performance is optimized in four stages: data preparation, model training, personalized adjustment, and evaluation feedback. The actual art project “Echoes in the Mirror” is used as a case to verify the actual application effect of the model. The evaluation shows that the work receives high scores in clarity, color accuracy, style coherence, and innovation (the average score is close to 9 points). Audience feedback shows that the model performs well in enhancing immersive experience, emotional resonance, and interactive satisfaction, whereas technical acceptance also highlights room for optimization. The research results not only demonstrate the potential of automated and personalized models in artistic creation but also provide practical guidance for the deep integration of art and technology in the future and promote artistic creation to move toward the two-way improvement of innovation and audience experience.
- Scope:
- Online-Ressource
- Note:
- Open Access
- Archivierung/Langzeitarchivierung gewährleistet
- Keywords:
- computer vision ; digital media ; art creation design ; generative adversarial networks ; conditional generative models
- Classification:
- Informatik
- Sonstiges
- Collection:
- Informatik
- Sonstiges
- Copyright:
- CC BY
- Accessibility:
- Free Access
- Title:
- Creative design of digital media art based on computer visual aids
- Publication:
-
Warsaw: De Gruyter, 2025
- Language:
- English
- Information:
- Abstract: In the digital age, artistic creation needs to strike a balance between automation and personalization. This study proposes an innovative model that integrates generative adversarial networks, computer vision, and personalized adjustment technology. Through multistage iterative optimization, efficient art generation and personalized style customization are achieved. The model uses an automated generation module to generate a draft and guides the conditional vector to achieve fine-grained adjustment of the image so that the work maintains both technical innovation and the artist’s unique style. The model performance is optimized in four stages: data preparation, model training, personalized adjustment, and evaluation feedback. The actual art project “Echoes in the Mirror” is used as a case to verify the actual application effect of the model. The evaluation shows that the work receives high scores in clarity, color accuracy, style coherence, and innovation (the average score is close to 9 points). Audience feedback shows that the model performs well in enhancing immersive experience, emotional resonance, and interactive satisfaction, whereas technical acceptance also highlights room for optimization. The research results not only demonstrate the potential of automated and personalized models in artistic creation but also provide practical guidance for the deep integration of art and technology in the future and promote artistic creation to move toward the two-way improvement of innovation and audience experience.
- Scope:
- Online-Ressource
- Note:
- Open Access
- Archivierung/Langzeitarchivierung gewährleistet
- Keywords:
- computer vision ; digital media ; art creation design ; generative adversarial networks ; conditional generative models
- Classification:
- Informatik
- Sonstiges
- Collection:
- Informatik
- Sonstiges
- Copyright:
- CC BY
- Accessibility:
- Free Access
