In the digital transformation era, the application of deep learning in image style conversion has opened new avenues for creative expression and business innovation. This article explores advanced deep learning techniques to achieve efficient and accurate image style conversion in different image datasets. The method has been validated through comprehensive experiments on the Microsoft Common Objects in Context dataset, and compared to existing methods, this article's method demonstrates outstanding performance metrics including peak signal-to-noise ratio, structural similarity, and user satisfaction. In addition, the impact of different hardware configurations on processing efficiency was analyzed, providing insights into optimizing computing resources for real-time applications. The results of this case study not only contribute to the theoretical advancement of image processing but also provide practical solutions for the visual content creation industry.

Curug Silawe in Magelang Regency has promising natural tourism potential, but still faces problems with cleanliness and suboptimal digital promotion. These conditions have an impact on the instability of tourist visitation numbers, so community empowerment activities that are in line with field needs are required. This initiative aims to assist managers in improving the cleanliness of the area while strengthening promotion through social media to increase awareness and interest in Curug Silawe. The program was implemented in collaboration with managers as key partners, beginning with observation and discussion, followed by cleanup activities and the creation of visual content for publication on social media. The results of the activities showed significant changes, marked by a reduction in trash, a tidier area, and positive responses to promotional posts on Instagram. These findings indicate that simple collaboration with managers can improve environmental conditions and the image of the destination, and therefore needs to be supported on an ongoing basis.

The utilization of digital technology in the Industry 4.0 era has become crucial for vocational high school (SMK) students to build economic independence. However, partners at SMKN 1 Selo still face obstacles in optimizing social media and digital platforms as effective promotional tools for student work and self-development. This community service activity aims to enhance students' understanding and skills in using social media (Instagram, TikTok) and other digital platforms as creative marketing instruments. The method employed is a descriptive qualitative approach through participatory training, which includes material presentation on digital branding strategies, visual content creation practices, and copywriting techniques. The results of the activity indicate a significant improvement in students' technical abilities, where they demonstrated the capacity to produce engaging promotional content and understand social media algorithms to reach a wider audience. This study aims to describe the process and impact of utilizing social media and digital platforms as promotional tools for SMKN 1 Selo students. The primary focus of this activity is to provide a deep understanding of personal branding strategies and creative product marketing in the digital age. Through this program, it is expected that SMKN 1 Selo students will possess higher digital competitiveness and the ability to leverage the digital ecosystem to support the promotion of vocational products and their professional profiles in the future.

The article provides a comprehensive analysis of the prospects for integrating generative artificial intelligence (AI) into the educational process of higher education institutions (HEIs) to support student learning activities. The study addresses the urgent need for a scientifically grounded strategy that maximizes the didactic potential of AI while mitigating associated risks. The research methodology involves a systematic review of contemporary literature, identifying key challenges such as the lack of validated pedagogical approaches, threats to academic integrity, and ethical concerns like data privacy and algorithmic bias. Based on this analysis, the paper introduces a functional classification of generative AI services, categorizing them into four key groups: large language models and chatbots (e.g., ChatGPT, Perplexity AI), tools for visual content creation (e.g., Midjourney, DALL-E 3), specialized academic assistants (e.g., Scite, Elicit), and AI-powered programming tools (e.g., GitHub Copilot). This classification is a practical framework for educators and students to select the most appropriate tools for specific educational objectives. A core contribution of this work is developing a detailed set of criteria for the effective and safe use of generative AI. These criteria are divided into two main categories: effectiveness criteria, which include relevance to the learning task, accuracy and reliability of information, depth of analysis, and pedagogical appropriateness; and safety criteria, which cover data confidentiality, academic integrity, source transparency, and awareness of potential biases. The study systematically evaluates the pedagogical benefits and risks. Key advantages include enhanced personalization of learning paths, increased student engagement through interactive tools, significant time savings on routine tasks, and the development of crucial digital literacy skills. Conversely, the primary risks identified are the potential decline in students' critical thinking, the rise of academic dishonesty, the spread of misinformation due to AI "hallucinations," and the exacerbation of digital inequality. To address these challenges, the article formulates a set of actionable recommendations for three stakeholder groups. For students, it emphasizes using AI as a brainstorming partner, critically verifying all generated information, mastering prompt engineering, and maintaining transparency in their work. For educators, integrating AI into assignments, shifting assessment focus from the final product to the research process, and teaching information hygiene. For HEI administrators, the recommendations include developing clear institutional policies, providing professional development for faculty, and fostering international collaboration to share best practices. The paper concludes that the strategic integration of generative AI is not merely a technological upgrade but a fundamental shift towards a more personalized, efficient, and interactive educational paradigm. The key to success lies not in prohibiting these technologies but in their thoughtful and ethical incorporation into the academic culture, preparing students with the future-ready competencies required in the modern world.

Micro, Small, and Medium Enterprises (MSMEs) serve as a cornerstone of the national economy, yet they continue to face significant challenges in terms of promotion and digital transformation. Kaloris Herbal Beverage MSME, as a producer of natural-based products, holds substantial potential in line with the growing trend of healthy lifestyles. However, its marketing practices remain largely conventional, relying primarily on word-of-mouth promotion. The major obstacles encountered include weak branding efforts, limited digital content management, and underutilization of social media and online marketplaces. To address these issues, this community engagement program applied a Participatory Action Research (PAR) approach, emphasizing training in digital marketing strategies such as social media optimization, visual content creation, and marketplace management. The outcomes demonstrate that Kaloris MSME successfully established a more consistent digital identity, reflected in a significant increase in social media followers, engagement rates, and local consumer orders. This surge in digital interaction was also accompanied by positive consumer responses regarding product quality and packaging. Thus, strengthening digital marketing strategies has proven effective in expanding local market reach, enhancing brand awareness, and improving the competitiveness of herbal beverage MSMEs in the digital economy era.

This article explores the use of AI tools in the DIY production of a music video through a practice-led case study involving Midjourney, Runway and Plask. The project demonstrates how AI enables faster and more stylistically ambitious visual content creation, especially for music producers without formal visual training, while also reshaping the artistic challenges for the maker. Through critical reflection, public feedback and an industry interview, the study examines how AI functions as an incubator and technical executor, aiding in the preparation and elaboration stages of the creative process. Drawing on creativity theory, this article argues that while AI can produce novel and valuable outputs, it lacks intentionality and must be guided, interpreted and curated by humans. The research supports emerging concepts of AI co-creativity, suggesting that the future of content production lies not in AI replacing humans, but in augmenting human direction through collaborative frameworks.

Bali, a global tourism icon, faces significant challenges in distributing tourist visits to local destinations at the rural level due to the digital divide. This community service article aims to describe the implementation of digital-based tourism creativity development training for local destination managers in Bali to increase their attractiveness and competitiveness. The main problems identified among partners (Pokdarwis in Bali) were reliance on traditional marketing and the low quality of digital content capable of representing the uniqueness of local culture and nature. The community service method was carried out using an Asset-Based Community Development (ABCD) approach, which included visual content creation workshops, cultural narrative-based copywriting training ( storytelling ), and social media algorithm optimization. The community service results showed a significant increase in participants' creative capacity in producing aesthetic and informative content, as well as increased interaction on partner destinations' social media channels. The conclusion of this activity emphasizes that the digitalization of local tourism in Bali must be rooted in the creative packaging of local wisdom, so as to attract quality tourist segments and support the sustainable recovery of the creative economy post-pandemic.

This community service program aims to improve the competitiveness of vegetable product MSMEs through Content Marketing training. The activity is designed to help business actors understand relevant digital marketing strategies in the modern era. The implementation method includes four stages, namely preparation, training, mentoring, and evaluation, which lasts for one month. The training covers visual content creation, caption writing, social media management, and content calendar preparation. The program results show an increase in participants' knowledge, technical skills in content creation, and consistency in digital promotion. In addition, there has been an increase in social media interaction and audience reach. This program has positive implications for strengthening branding and the competitiveness of MSMEs in the digital era.

Artificial Intelligence (AI) has significantly transformed the landscape of digital media by enhancing the processes of visual content creation and media management. AI-driven technologies such as machine learning, computer vision, and deep learning enable the automated generation, editing, and optimization of visual media including images, videos, and graphics. Digital media platforms increasingly rely on AI tools to improve production efficiency, personalize content, and enhance audience engagement. AI-based systems can analyse user preferences, generate creative visuals, and automate repetitive production tasks, allowing media professionals to focus on strategic and creative aspects of content development. Despite these advantages, the integration of AI in visual content creation also raises concerns related to ethical issues, originality, algorithmic bias, and the potential impact on creative employment. This study explores the role of AI-driven technologies in visual content creation across digital media platforms and examines their influence on media production, content management, and audience engagement. The findings highlight that AI has the potential to revolutionize digital media workflows by improving productivity, creativity, and datadriven decision-making in modern media organizations.

Social media has rapidly transformed how micro and small enterprises (MSEs) engage customers and access markets, yet many MSEs in Lagos State continue to struggle with leveraging these platforms effectively for business growth. This study therefore examined the effect of social media usage on the performance of MSEs in Lagos State, Nigeria, responding to the need for empirical clarity on how different platform types shape revenue growth. The objective was to assess the combined effect of social media, involving visual-centric, professional networking, real-time engagement, and community-driven platforms on MSE performance, particularly revenue growth among MSEs in the area. A descriptive survey design was adopted, and data were collected using a structured questionnaire administered to 781 respondents drawn from a population of 3,337,198 MSE owners using Taro Yamane’s formula, with reliability established through pilot testing and Cronbach’s alpha values above acceptable thresholds. Multiple regression analysis showed that all four platform dimensions significantly enhanced revenue growth, with visual-centric platforms (1.921) exerting the strongest effect, followed by professional networking (1.835), real-time engagement (1.817), and community-driven (1.763) platforms. The study concluded that social media is a critical performance-enhancing tool for MSEs, supporting revenue expansion and customer engagement across Lagos State. It recommended strategic investment in visual content creation, deeper participation in professional and community networks, and increased use of real-time platforms to strengthen responsiveness.

In animation generation combining paintings and live-action footage, the core challenge for cross-modal visual content creation lies in effectively coordinating feature discrepancies across multimodal data while achieving adaptive enhancement of key information. This study proposes a deep learning model based on the channel attention mechanism (CAM). It systematically addresses cross-modal fusion difficulties between artistic semantic features and live-action visual information through a dual-path feature fusion framework and dynamic weight allocation strategy. The study employs an encoder-decoder architecture where Residual Network-50 (ResNet-50) extracts multimodal features, channel attention modules perform importance weighting on feature channels, and Transformer decoders generate animation sequences. The framework incorporates feature alignment loss functions and dynamic weight ablation experiments to strengthen cross-modal feature integration capabilities. Experimental results demonstrate that the model achieves an 11.0% improvement in peak signal-to-noise ratio and an 8.8% enhancement in structural similarity index on the custom test set. This confirms high reconstruction accuracy at both pixel and structural levels. The Fréchet Inception Distance decreases by 23.4%. Meanwhile, multimodal fusion degree and cross-modal feature dynamic coupling index increase by 21.9% and 42.3% respectively, significantly optimizing feature distribution consistency and modal interaction efficiency. Ablation studies reveal that the CAM improves model performance by approximately 15%, and the dynamic weight strategy effectively enhances robustness against parameter perturbations. This study provides both theoretical foundations and technical solutions for virtual-real fusion in digital art creation, advancing animation generation toward intelligent and artistic development.

Abstract: The “AI-Powered Image Generation System using AI” is designed to transform textual descriptions into visually compelling images using advanced artificial intelligence techniques. By leveraging AIstate-of-the-art models, such as DALL•E, the system interprets user provided prompts and generates high-quality, realistic, and creative images in real-time. This approach demonstrates how AI can bridge human imagination and machine intelligence, making creative content generation faster and more accessible. The system architecture consists of a user-friendly interface for inputting prompts, a backend module that communicates with the AI API, and an image rendering component that delivers generated images to the user. The platform allows both technical and non-technical users to create visuals efficiently, supporting applications in digital art, marketing, education, and entertainment. By integrating AI into the creative workflow, the project highlights the potential of prompt-based image generation in modern content creation. In addition, the project addresses challenges such as handling ambiguous or inappropriate prompts, ensuring image quality and resolution, and promoting ethical use of AI-generated content. Future developments may include multi-modal input, style customization, and integration with other creative tools. Overall, this project illustrates the transformative capabilities of AI in visual content creation and provides a scalable framework for innovative applications across various domains..

Purpose of research. The objective of this study is to develop a software solution for automated presentation generation, focused on integrating principles of cognitive psychology and aesthetics. The research aims to create an intelligent platform capable of generating presentations that not only convey information but also ensure its effective visual perception, capturing and retaining audience attention. In an era of rapidly increasing data volumes and decreasing time resources, there is a growing need for tools that can automate the creation of visual content without compromising its quality. The proposed solution takes into account the specific characteristics of human information perception by relying on cognitive principles such as cognitive load theory, Gestalt laws, and visual emphasis. In addition, it applies aesthetic design techniques to create a balanced and expressive visual structure.Methods. The study combines various approaches and methods, including cognitive and aesthetic aspects, objectoriented programming, and integration with artificial intelligence technologies. This allows the system to automatically generate both textual and visual content, adapting it to the predefined structure of the presentation.Results. The developed software solution demonstrated advantages over existing tools across several key parameters: reduced presentation creation time, improved visual quality, adaptability, and alignment with cognitive strategies of information perception. Experimental results involving users confirmed the high efficiency of the proposed approach in terms of usability, design quality, and content perception.Conclusion. The proposed solution, based on the cognitive-aesthetic paradigm, represents a promising direction in the field of automated visual communication. It demonstrates potential for scalability and integration across various domains that require the creation of presentation content combining informativeness, visual expressiveness, and a human-centered design approach.

The development of digital technology has changed the way students interact with learning media, including in the creation of visual content. One of the most widely used applications among students is Canva Mobile, which offers convenience in designing various academic needs practically through mobile devices. This research aims to explore the experiences of second-semester students of the Communication Science Study Program at the University of Boyolali in using the Canva Mobile interface as a supporting medium for completing academic assignments. This study uses a descriptive qualitative approach with data collection techniques through in-depth interviews and observation. Informants were selected using purposive sampling, followed by snowball sampling. The collected data were analyzed through data reduction, data presentation, and conclusion drawing. The results show that the majority of students feel comfortable and find it easy to use Canva Mobile. Its user-friendly interface, diverse features, and flexible access are the main reasons for its popularity. Canva Mobile has been proven to improve the quality of students' visual assignments and support creativity development in the field of visual communication. However, there are some obstacles, such as the limited features in the mobile version compared to the desktop version, as well as restricted access to premium elements. This study concludes that Canva Mobile is an effective, adaptive, and relevant learning medium that aligns with the needs of today’s digital-native students. Students' positive experiences in using this application serve as evidence that mobile technology can be optimally integrated into higher education.

In the context of the modern information war, the development of effective methods to counter disinformation and hostile propaganda has become critically important. The amount of false information and the speed of its dissemination necessitated the implementation of automated systems involving artificial intelligence to optimise the processes of creating visual counter-propaganda content. This research aimed to develop a methodology for the integration of artificial intelligence technologies into the processes of creating effective visual tools for countering disinformation, taking into account the principles of graphic design and the psychology of visual information perception. The research was based on a comprehensive approach that combined theoretical analysis of scientific literature, comparative analysis of the neural networks Midjourney, Stable Diffusion, and DALL-E, semiotic analysis of visual materials, as well as experimental implementation of the developed system for the automated creation of counter-propaganda visual content. A comprehensive approach has been developed for the creation of visual tools to counter disinformation, which combines the capabilities of automated information collection systems, artificial intelligence algorithms for generating graphic content, and the principles of effective graphic design. It has been found that the use of artificial intelligence in graphic design has optimised up to 20% of routine tasks in the creation of visual content, allowing designers to focus on the strategic and creative aspects of development. The developed recommendations for the use of artificial intelligence in graphic design may be implemented by state institutions, media, and public organisations to respond promptly to information threats

Artificial Intelligence (AI) technologies are developing, diversifying and increasing their impact on learning-teaching environments. Higher education, with its various disciplines and their instructional applications, is also significantly influenced by these developments. However, despite all this development, lecturers’ tendency to use AI for educational purposes is transforming depending on their thoughts and intentions on this issue. From this point of view, this study examines the views of lecturers on the possible effects of AI technologies on their teaching-learning processes. The participants were selected voluntarily from among the lecturers working at universities in Turkey with different positions and titles, taking into account the balance of experience, title and gender. The data collection package included an 8-question semi-structured data collection form developed by the researcher. The collected data were analyzed using inductive content analysis, enabling the identification of themes based on common concepts. The themes were evaluated in terms of the opportunities offered by AI in the field of higher education today with their strengths and aspects open to improvement. The findings revealed that faculty members use AI technologies especially in language models, visual content creation tools and automated assessment systems; these technologies offer advantages such as time saving, individualized learning opportunities and content enrichment. However, challenges such as ethical issues and academic integrity risks were also identified. The research provides insights into the future role of AI technologies in higher education and lays the groundwork for recommendations for educational policies.

Tegowangi Temple is one of the important relics of the Majapahit Kingdom era, which not only holds historical and architectural value but also has great potential as a medium for local cultural education. However, the low awareness of the surrounding community regarding the importance of preserving this cultural heritage site poses a challenge that needs to be addressed through a contextual and communicative educational approach. This community service activity aims to strengthen the cultural literacy of the community in Tegowangi Village, Plemahan Sub-district, Kediri Regency, through the development of educational leaflets as an attractive and easily accessible medium for socialization. The leaflets are designed with content based on scientific literature and popular historical narratives, containing information about the location, history, and architecture of Tegowangi Temple. The implementation methods include field observations, limited interviews with local figures, literature reviews, the creation of visual content based on participatory graphic design, and the distribution of leaflets to the community and visitors. This activity involved collaboration between faculty members, students, and village officials as active partners. The results of the activity demonstrated that the leaflet played a significant role in enhancing the community's knowledge of local cultural heritage, fostering a sense of ownership toward the historical site, and encouraging community participation in long-term conservation efforts. This program is recommended as a community-based visual education model that can be replicated at other cultural sites using a similar approach.

This theoretical paper explores the role of critical visual literacy in arts-based research methodologies and knowledge translation, emphasizing relevance in addressing issues of equity and societal impact. Arts-based engagements—including those intended to empower communities—emerge as potentially bringing inadvertent risks given existing evidence base on critical visual literacy. A review of literature identifies an operational definition of principles related to (1) safeguarding marginalized groups; (2) acknowledging diverse interpretation amidst dominant narratives and rule-making by mass-producers of visual media; and (3) analyzing political or other social norms embedded within imagery to prioritize community consent. In response, AI image-generation may support the fostering and application of critical visual literacy in academic settings if the digital divide and historic dataset of visual grammar can be addressed. Under the context of critical visual literacy and participatory engagement, a preliminary framework of machine learning is conceptualized. Integration may offer significant shifts in visual content creation towards critique, with increased capacity for larger-scale production potentially offering opportunities for disseminating new, community-based perspectives on visual grammar. Implications related to co-revision and dignifying the emotional attachment towards art and its critical evaluation conclude the paper.

This study aims to describe and analyze strategies branding conducted by Waecicu Bakery via Instagram. The approach used is descriptive qualitative with data collection techniques in the form of interviews, observations, and documentation. Research informants consist of business owners, social media managers, and consumers as triangulation of source data. Data analysis uses the interactive model of Miles, Huberman, and Saldana which includes the stages of data collection, data reduction, data presentation, and drawing conclusions. The results show that the strategy branding implemented in three main stages, namely planning (brand positioning,brand identity,brand personality), implementation (visual content creation, consumer interaction, and collaboration), and digital performance evaluation. The evaluation shows the achievement engagement rate by 3.4%, and an average of 92,120 views per upload.Branding through Instagram has proven to be effective in increasing followers (followers), involvement audience, and brand awareness. Recommendations include improving content consistency and management, optimizing Instagram features, and adding a management team.

With the rapid development of short video platforms, content creation has become an important factor in attracting users and increasing platform activity. However, creators face multiple challenges in creativity, efficiency, and quality in video production. The introduction of artificial intelligence (AI) technology provides a new solution for short video creation, especially in the creation and optimization of visual content. This paper studies the AI-assisted visual content creation process and optimization practice for short video platforms, and explores the application of AI in video editing, image processing, personalized recommendation and other fields and its optimization effect. Through the analysis of the AI-assisted creation technology framework, this paper reveals how AI can improve creation efficiency, optimize video quality, and promote the personalized and intelligent development of short video creation. In addition, this paper also analyzes the technical challenges, ethical and legal issues faced by AI-assisted creation, as well as the collaborative relationship between creators and AI. Finally, this paper looks forward to the future development trend of AI and short video creation, and puts forward relevant practical suggestions, providing theoretical guidance and technical support for creators and platforms.