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Journal articles on the topic 'AI image generators'

Author: Grafiati

Published: 7 June 2025

Last updated: 2 August 2025

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1

Lee, Hyun Seung, and Manman Luo. "Transforming Creative Process: A Systematic Literature Review of Discourse on AI Image Generators." Proceedings of the Association for Information Science and Technology 61, no. 1 (2024): 986–88. http://dx.doi.org/10.1002/pra2.1162.

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ABSTRACTAI image generator, also known as Text‐to‐image generation (TTIG) technology, allows users to generate images based on natural language input. With advancements in AI, debates related to its application in the creative field have flourished. A systematic literature review was conducted to examine discourse that addresses the perception of people in the creative industry towards AI image generators and the impact of AI image generators on these individuals. The analysis of discourse revealed four major categories: 1) Evaluation of product or outcome of AI; 2) Impact of AI on practitione

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Hong, Yan, Jianming Feng, Haoxing Chen, et al. "WildFake: A Large-Scale and Hierarchical Dataset for AI-Generated Images Detection." Proceedings of the AAAI Conference on Artificial Intelligence 39, no. 4 (2025): 3500–3508. https://doi.org/10.1609/aaai.v39i4.32363.

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The development of text-to-image generative models has enabled the creation of images so realistic that distinguishing between AI-generated images and real photos is becoming a challenge. This progress offers new possibilities but also raises concerns over privacy, authenticity, and security. Detecting AI-generated images is crucial to prevent misuse. To assess the generalizability and robustness of AI-generated image detection, we present a large-scale dataset, referred to as WildFake. This dataset features cutting-edge image generators, a wide variety of generator categories, and generators

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Malevé, Nicolas. "Lost in Compression." Media Theory 8, no. 1 (2024): 205–28. http://dx.doi.org/10.70064/mt.v8i1.1074.

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Recent developments of image generators have introduced a new point of contention in the already contested field of artificial intelligence: the ownership of images. In 2023 Getty Images sued the company Stability AI, accusing it of illegally appropriating photographs for the purpose of training its models. Analysing image generators and stock agencies as probabilistic systems, this text argues that their significant difference lies in their model of appropriation. Where Stability AI proceeds through direct appropriation, the stock agency proceeds through contractual appropriation using its do

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Mahajan, Mr S. K. "AI IMAGE GENERATOR THROUGH TEXT PROMT." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 08, no. 03 (2024): 1–13. http://dx.doi.org/10.55041/ijsrem28932.

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In the era of digital content creation, the Text-to- Image Generator has emerged as a powerful and innovative tool that transforms textual descriptions into captivating visual representations. This website leverages advanced deep learning techniques to bridge the gap between imagination and reality, enabling users to effortlessly generate stunning images from their written words. Our Text-to-Image Generator website provides a user- friendly interface where individuals can input textual prompts, whether they are vivid descriptions, imaginative stories, or abstract concepts. Behind the scenes, s

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Fareed, Mohamed W., Ali Bou Nassif, and Eslam Nofal. "Exploring the Potentials of Artificial Intelligence Image Generators for Educating the History of Architecture." Heritage 7, no. 3 (2024): 1727–53. http://dx.doi.org/10.3390/heritage7030081.

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The rapid integration of Artificial Intelligence (AI) tools, specifically text-to-image generators, across various domains has had a profound impact on numerous fields. Despite this, the potential applications of AI image generators in architectural education, particularly in teaching the history of architecture, remain underexplored. This research aims to uncover the possibilities of utilizing AI image generators, with a specific focus on the capabilities of Leonardo AI, to enhance communication and engagement. This study employed an experimental methodology to investigate how the integration

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Enjellina, Eleonora Vilgia Putri Beyan, and Anastasya Gisela Cinintya Rossy. "Review of AI Image Generator: Influences, Challenges, and Future Prospects for Architectural Field." Journal of Artificial Intelligence in Architecture 2, no. 1 (2023): 53–65. http://dx.doi.org/10.24002/jarina.v2i1.6662.

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Recently, the topic of text-to-image-based GAI (Generative Artificial Intelligence) or AI Image Generators became so popular because of its sophistication in creating images based on human natural language messages in a short time. On the other hand, the presence of the AI Image Generator is enough to reap various opinions, including in the field of architecture. Therefore, the purpose of this paper is to present a review of the influences, challenges, and prospects of AI Image Generator technology in the architectural design process. The research method used is a systematic literature review

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Hilles, Stefanie. "ARTificial Intelligence: opportunities for art librarians to engage students’ critical thinking with AI image generators." Art Libraries Journal 50, no. 1 (2025): 2–5. https://doi.org/10.1017/alj.2025.3.

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Art librarians work with images. It’s one of the things that separates us from many of our fellow subject librarians. As the academy continues to grapple with the benefits, drawbacks, and effects of AI, art librarians are uniquely positioned to teach students how to critically engage with AI image generators. Considerations concerning copyright, bias in datasets, formal analysis, and AI image generators’ potential as an art medium are some examples of topics that art librarians have at their disposal.

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Jonek, Michael, Malte Bast, and Martin Manns. "Manual assembly planning with AI Image Generators." Procedia CIRP 130 (2024): 139–44. http://dx.doi.org/10.1016/j.procir.2024.10.068.

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Rouhullah, Jauhara Albar. "Dampak Buruk Artificial Intelligence (AI) Image Generators terhadap Proses Pendidikan Pelajaran Agama Islam." IJITECH : Indonesian Journal of Information Technology 3, no. 1 (2025): 42–50. https://doi.org/10.71155/kbercz02.

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Perkembangan Artificial Intelligence (AI) khususnya yang berkaitan dengan image generators memudahkan guru dalam menyampaikan ilmu kepada siswa. Tidak hanya pada pelajaran umum, tapi juga pada pelajaran Pendidikan Agama Islam (PAI). Namun, terdapat pula dampak negatif yang dihasilkan dari image generators. Penelitian ini bertujuan untuk menyampaikan dampak negatif yang perlu diperhatikan saat menggunakannya pada PAI. Dengan menggunakan sudut pandang etika Islam, ada beberapa negatif yang dihasilkan image generators: (1) penggambaran wajah Nabi Muhammad, (2) kemudahan mengakses gambar sugestif,

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Ananto, Muhammad Mizan. "Legal Position Artificial Intelligence Art Generator in Copyright Law." JISIP (Jurnal Ilmu Sosial dan Pendidikan) 7, no. 4 (2023): 2938. http://dx.doi.org/10.58258/jisip.v7i4.5520.

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Artificial Intelligence (AI) art generators are disrupting the meaning of creating an artwork that has long been known. The AI art generator has features that make it easy for users to create images, simply by entering text descriptions, then the AI will produce the desired image. This creation process then raises questions about the legal position of AI on copyright contained in the image. This study discusses the legal position of AI in intellectual property law by dividing it into two options: First, how is the prospect of recognizing AI as a legal subject of copyright law, and secondly how

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Sikandar, Ayesha, and Hafiza Moatter Bahar. "A comparative analysis to assess anatomical illustrations via three AI-Driven Text-to-Image generators." European Journal of Anatomy 28, no. 5 (2024): 631–34. http://dx.doi.org/10.52083/dlqj8889.

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In recent years the popularity of artificial intelligence (AI) has increased rapidly. While the machine itself can be built for deep learning in order to enhance its own efficiency through sophisticated networks, artificial intelligence (AI) uses machine-learning models to store, calculate, analyze, and even enhance extensive volumes of data that have to be retrieved whenever needed. Text-to-image AI models like Midjourney, Microsoft Bing Image Creator Powered by DALL- E, and Craiyon can generate artistic and impressive images. In this study, anatomical representations of the human ribs, brain

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Saravanan, Muniraj. "Enhancing AI-Generated Image Accessibility Challenges and Solutions." International Journal for Research Trends and Innovation 9, no. 8 (2024): 145–50. https://doi.org/10.5281/zenodo.13293092.

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This research examined accessibility issues with AI-created images and assessed current solutions for improving inclusivity. Key problems identified include insufficient alt text, with 45% of AI images lacking proper descriptions, challenges in differentiating AI images from real ones (38.7% misclassification by people), and ethical worries about representation and bias in image descriptions. The study analyzed solutions like AI-based description generators, which can boost accuracy by up to 60%, and better image detection methods. Results show that while progress has been made in making AI im

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Pirovski, Nikola. "The Role of AI for Teaching Anatomy in Medicine." Filosofiya-Philosophy 53, no. 3 (2014): 274–85. http://dx.doi.org/10.53656/phil2024-03-05.

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The purpose of this report is to systematize the role of artificial intelligence for the teaching of anatomy in medicine. Experience of teachers in using new technologies (Google Classroom, 3D atlases, WordPress, Facebook, Virtual Reality, etc.) in teaching human anatomy to students of various health specialties for the last 4 years is described. Currently available tools such as ChatGPT 4, Google Gemini, Microsoft Bing Copilot, are not designed for this purpose and fail to generate anatomically correct training images. This situation attends professional attention as well as needs some philos

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Kurakina, N. A., and D. S. Filippova. "Artificial Intelligence and Art: Opportunities and Challenges." SibScript 26, no. 4 (2024): 548–56. http://dx.doi.org/10.21603/sibscript-2024-26-4-548-556.

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Linguistic studies of art discourse are gaining more and more relevance in the context of rapidly developing artificial intelligence. This research featured the impact of art discourse on the audience and their interpretation of images generated by AI image generators based on text queries. AI image generators open up new opportunities for research and understanding of art and art discourse, which is interpretive and dualistic in nature. Anna Andrzhievskaya’s FV and Dawn from the catalogue of Heavenly Wasteland exhibition were tested using Shedevrum and Bing Image Creator. Expressive vocabular

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Derenne, Nicole, Lindsey Martens, Nicole Virgin, et al. "DIGITAL AGEISM PERSISTS IN ARTIFICIAL INTELLIGENCE-GENERATED IMAGES." Innovation in Aging 8, Supplement_1 (2024): 1302–3. https://doi.org/10.1093/geroni/igae098.4162.

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Abstract Artificial intelligence systems (AI), including text-to-image models, often reflect and amplify societal age-related biases, a phenomenon known as digital ageism. This study examines if instances of digital ageism in AI-generated representations of older adults lessen over time. Examining how digital ageism evolves in AI-image generation can provide insight into the interplay between technology advancements, societal attitudes toward aging, and the well-being of older adults interacting with the dynamic digital landscape. This mixed methods project compared 164 images generated by Ope

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Allen, Laura, Wenqian Xu, Mariko Nishikitani, Vaishnavi Atul Patil, and Dana Bradley. "AGE BIAS IN ARTIFICIAL INTELLIGENCE (AI): A VISUAL PROPERTIES ANALYSIS OF AI IMAGES OF OLDER VERSUS YOUNGER PEOPLE." Innovation in Aging 7, Supplement_1 (2023): 986. http://dx.doi.org/10.1093/geroni/igad104.3168.

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Abstract Concerns about age-related biases in Artificial Intelligence (AI)’s design, development, and data generation raise alarms for potential social inequalities. AI art-generators like MidJourney, known for creating distinctive and artistic images, have gained attention recently. However, the critical examination of their potential biases remains limited. Our study aims to investigate age-related bias in MidJourney by comparing how older and younger individuals are visually depicted. Using 19 keywords (as text prompts) tied to domains of potential social exclusion for older adults, we auto

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Hanna, Dena. "Testing AI Text to Image Generators for Advertising Applications." Journal of Design Sciences and Applied Arts 6, no. 2 (2025): 1–2. https://doi.org/10.21608/jdsaa.2025.330069.1431.

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Pandit,, Ashwini. "Image Caption Generator." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 08, no. 05 (2024): 1–5. http://dx.doi.org/10.55041/ijsrem34949.

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An Image Caption Generator is a sophisticated AI system that combines computer vision and natural language processing to automatically create descriptive textual captions for images. This technology utilizes deep learning, particularly Convolutional Neural Networks (CNNs), to analyze and extract meaningful visual features from the input image. These features capture details about the objects, scenes, and elements within the image. Subsequently, a natural language processing model, often built on Recurrent Neural Networks (RNNs) or Transformers, processes these visual features and generates coh

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KJ, Karthik. "A SURVEY ON AI-CONTENT GENERATOR." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 09, no. 01 (2025): 1–9. https://doi.org/10.55041/ijsrem41078.

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This survey provides an in-depth exploration of AI-driven content generation, covering key areas such as text creation, image synthesis, video generation, and automated coding. By examining advancements in technologies like Large Language Models (LLMs), GANs, and diffusion models, the study highlights AI's role in transforming diverse fields. Text generation technologies are enabling structured, creative, and conversational outputs, while image and video synthesis models like Imagen and Phenaki are setting new benchmarks for visual quality and realism. In code generation, tools like ChatGPT an

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Taubayev, Zharas, Yertay Sultan, and G. Dautova. "THE ROLE OF ARTIFICIAL INTELLIGENCE IN FORMING STEREOTYPES IN INTERCULTURAL COMMUNICATION." Bulletin of the Eurasian Humanities Institute, Philology Series, no. 1 (March 30, 2025): 185–95. https://doi.org/10.55808/1999-4214.2025-1.18.

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Technological innovations, globalization, the political and economic environment, as well as socio-cultural features have a noticeable impact on the structure, content and orientation of media communications. Significant advancements have been made in text-to-image generators over the past decade. AI opens up new possibilities, enabling anyone to effortlessly generate visually stunning images without the need for artistic skills. However, it also leads to the creation of more stereotypes when using large amounts of data. Consequently, stereotypes are becoming more prevalent and serious than ev

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Kapadnis, Trushna, Anuja Modhave, Akanksha Narwade, Umesh Wagh, and Prof Dr Deepali Sale. "Automatic Intelligence Caption Generator." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 07, no. 11 (2023): 1–11. http://dx.doi.org/10.55041/ijsrem26789.

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An Image Caption Generator is a sophisticated AI system that combines computer vision and natural language processing to automatically create descriptive textual captions for images. This technology utilizes deep learning, particularly Convolutional Neural Networks (CNNs), to analyze and extract meaningful visual features from the input image. These features capture details about the objects, scenes, and elements within the image. Subsequently, a natural language processing model, often built on Recurrent Neural Networks (RNNs) or Transformers, processes these visual features and generates coh

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Fathoni, Ahmad Faisal Choiril Anam. "Leveraging Generative AI Solutions in Art and Design Education: Bridging Sustainable Creativity and Fostering Academic Integrity for Innovative Society." E3S Web of Conferences 426 (2023): 01102. http://dx.doi.org/10.1051/e3sconf/202342601102.

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Artificial intelligence (AI) has transformed art and design education, giving students new ways to create, explore, and learn. Unfortunately, there is fear among academicians that students will use AI, especially text-to-image generators like Midjourney or Dall-E, as an illegal shortcut in creating their work. This article examines how generative AI solutions, such as text-to-image generators, can help students create innovative and sustainable designs while promoting academic integrity. The article shows how AI in art and design education can equip students with the skills and knowledge to su

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Srivastava, Ananya. "Advancements in Text-to-Image Generation through Generative AI." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 08, no. 05 (2024): 1–5. http://dx.doi.org/10.55041/ijsrem33569.

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Text-to-image generation, a fascinating intersection of natural language processing and computer vision, has witnessed remarkable progress in recent years. This research paper provides a comprehensive review of the state-of-the-art techniques, challenges, and applications in the field of text-to-image generation. The paper aims to analyze various approaches, discuss their strengths and limitations, and highlight potential directions for future research. Generative Artificial Intelligence (Generative AI) has revolutionized the fusion of textual information and visual content, giving rise to sop

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Darmawan, Andreas James, I. Made Gede Arimbawa, Anita Heptariza, and Hosea Brayen. "HARNESSING AI IMAGE GENERATOR PROMPT ENGINEERING FOR ACADEMIC EXCELLENCE." Proceeding Bali-Bhuwana Waskita: Global Art Creativity Conference 4 (December 29, 2024): 192–202. https://doi.org/10.31091/bbwp.v4i1.478.

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This study explores the role of prompt engineering in visual communication design education, specifically examining its application with AI image generators. With the rise of AI technologies, prompt engineering has become an essential skill for creative professionals to maximize the potential of AI tools in generating high-quality visuals. The purpose of this research is to assess the effectiveness of prompt engineering skills among visual communication design students and identify factors that contribute to successful prompt formulation. Research methods include case study analysis, surveys,

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Chen, Yueqiao. "Pandoras Pixel Box: The Rise of AI Art and the Ethical Dilemma of Creativity." Lecture Notes in Education Psychology and Public Media 28, no. 1 (2023): 135–43. http://dx.doi.org/10.54254/2753-7048/28/20231315.

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The emergence of AI-generated art has sparked a debate on the ethical considerations and social impacts of this new form of creativity. This paper explores the current approaches to AI (Artificial Intelligence) art generators, including the ongoing debate on AI arts creativity and the issues of copyright, ownership, and fair use. Meanwhile, it systematically examines the standard procedures of AI art generators, including machine learning models such as GANs (Generative Adversarial Networks) and text-to-image models. Moreover, the psychological views of art are explored, highlighting the impor

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Vismay Vora, Et al. "A Multimodal Approach for Detecting AI Generated Content using BERT and CNN." International Journal on Recent and Innovation Trends in Computing and Communication 11, no. 9 (2023): 691–701. http://dx.doi.org/10.17762/ijritcc.v11i9.8861.

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With the advent of Generative AI technologies like LLMs and image generators, there will be an unprecedented rise in synthetic information which requires detection. While deepfake content can be identified by considering biological cues, this article proposes a technique for the detection of AI generated text using vocabulary, syntactic, semantic and stylistic features of the input data and detecting AI generated images through the use of a CNN model. The performance of these models is also evaluated and benchmarked with other comparative models. The ML Olympiad Competition dataset from Kaggle

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Kumar, Loveleen, and Manish Jain. "A Novel Image Super-Resolution Reconstruction Framework Using the AI Technique of Dual Generator Generative Adversarial Network (GAN)." JUCS - Journal of Universal Computer Science 28, no. 9 (2022): 967–83. http://dx.doi.org/10.3897/jucs.94134.

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Image superresolution (SR) is the process of enlarging and enhancing a low-resolution image. Image superresolution helps in industrial image enhancement, classification, detection, pattern recognition, surveillance, satellite imaging, medical diagnosis, image analytics, etc. It is of utmost importance to keep the features of the low-resolution image intact while enlarging and enhancing it. In this research paper, a framework is proposed that works in three phases and generates superresolution images while keeping low-resolution image features intact and reducing image blurring and artifacts. I

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Kumar, Loveleen, and Manish Jain. "A Novel Image Super-Resolution Reconstruction Framework Using the AI Technique of Dual Generator Generative Adversarial Network (GAN)." JUCS - Journal of Universal Computer Science 28, no. (9) (2022): 967–83. https://doi.org/10.3897/jucs.94134.

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Image superresolution (SR) is the process of enlarging and enhancing a low-resolution image. Image superresolution helps in industrial image enhancement, classification, detection, pattern recognition, surveillance, satellite imaging, medical diagnosis, image analytics, etc. It is of utmost importance to keep the features of the low-resolution image intact while enlarging and enhancing it. In this research paper, a framework is proposed that works in three phases and generates superresolution images while keeping low-resolution image features intact and reducing image blurring and artifacts. I

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Monferrer Palmer, Aina. "Reflexiones sobre el impacto de la inteligencia artificial en la enseñanza de idiomas. La revolución de ChatGPT." Semas 5, no. 9 (2024): 101–19. https://doi.org/10.61820/semas.2683-3301.v5n9.140.

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This article presents initial reflections on the educational implications of chatbot technologies, made available partially free by the end of 2022. These artificial intelligences in chat format, but also image generators or audio transcribers, will suppose a revolution in basic educational concepts such as cognitive development in childhood and the notion of original writing. In particular, chatbot technologies, and other artificial intelligence resources such as image generators, offer tools for language learning dynamics and the development of multilingual awareness that are the prelude to

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Lasker, Archit. "EXPLORING ETHICAL CONSIDERATIONS IN GENERATIVE AI." International Journal of Advanced Research 12, no. 04 (2024): 531–35. http://dx.doi.org/10.21474/ijar01/18578.

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Generative AI, which encompasses a range of technologies such as generative adversarial networks (GANs), language models, and image generators, has shown remarkable progress in recent years. These technologies have the potential to revolutionize various fields, from art and entertainment to healthcare and education. However, along with these advancements come ethical considerations that must be carefully addressed. This research paper examines the ethical challenges posed by generative AI, including issues related to bias, privacy, misinformation, and intellectual property. It also discusses s

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Elran, Sharan R., and Amit R. Zoran. "Probabilistic Craft- Materialization of generated images using digital and traditional craft." Proceedings of the ACM on Computer Graphics and Interactive Techniques 7, no. 4 (2024): 1–10. http://dx.doi.org/10.1145/3664209.

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This paper explores innovative integration of generative AI with digital and traditional craft practice. It presents a theoretical analysis of the nature of these new tools and interactions with digital agents as well as a practical workflow utilizing image generators for artistic creation, emphasizing the transformation of digital images into tangible objects through digital and traditional craft techniques. The paper presents three projects in ceramic, woodcut prints, and relief - each illustrating an optional material interpretation of generated images. The paper shows how materialization r

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Deepak, N. R., Jannat Al Firdaus Shaik, Shaikh Shayan, and Tajamul Shah Syed. "A Survey on Generation of Graphic Design Models using Stable Diffusion Models." Recent Trends in Computer Graphics and Multimedia Technology 5, no. 2 (2023): 7–12. https://doi.org/10.5281/zenodo.7970565.

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<em>AI image generation has grown significantly more accessible over the past few months and is expanding into other industries where the creation of assets is involved. AI picture generators may produce breath-taking photorealistic images from challenging challenges, albeit their capabilities are currently fairly limited. Diffusion models can take in some user input, and some noise, and create content similar to what it’s been trained on. In this case, these models were trained on images, meaning you can pass in a prompt, and have the model produce an image related to that prompt. Funda

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Chang, Hao-Yu, and Jo-Yu Kuo. "Exploring metacognitive processes in design ideation with text-to-image AI tools." Proceedings of the Design Society 4 (May 2024): 915–24. http://dx.doi.org/10.1017/pds.2024.94.

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AbstractThis research aims to explore the existence of metacognition during the use of text-to-image generators in the design ideation stage. We recruited five participants with a design background to use Midjourney as an ideation tool and to produce three sketches at the end of their task. Through semi-structured interviews and retrospective verbalization, we collected data on their thought processes. The qualitative analysis revealed clear indications of metacognitive engagement, such as monitoring and evaluating, which opens the path for future research into the impact of AI on design cogni

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Bezerra, Emili Silva, Quefren Oliveira Leher, Uendel Diego da Silva Alves, Thuanne Paixão, and Ana Beatriz Alvarez. "Deep Generative AI Based on Denoising Diffusion Probabilistic Models for Applications in Image Processing." Interfases, no. 020 (December 26, 2024): 69–91. https://doi.org/10.26439/interfases2024.n020.7389.

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Denoising diffusion probabilistic models (DDPMs) have demonstrated significant potential in addressing complex image processing challenges. This paper explores the application of DDPMs in three different areas: reconstruction of remote sensing imagery affected by cloud cover, reconstruction of facial images with occluded areas, and segmentation of bodies of water from remote sensing imagery. Inpainting involves filling in missing regions in images, while DDPMs act as data generators capable of synthesizing information that alings coherently with the context of the original data. Inspired by th

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Lyu, Yanru, Minghong Shi, Yanbo Zhang, and Rungtai Lin. "From Image to Imagination: Exploring the Impact of Generative AI on Cultural Translation in Jewelry Design." Sustainability 16, no. 1 (2023): 65. http://dx.doi.org/10.3390/su16010065.

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The current proliferation of artificial intelligence (AI) is prominently shaping the design industry. Generative AI, such as text-to-image and image-to-image models, has gained widespread use, notably for its efficiency and quality improvements. However, their potential to aid in cultural translation within creative design is underexplored. To address the existing gap, this study aims to assess the impact of generative AI on cultural translation within jewelry design. Specifically, a comprehensive study was conducted through a design-action experiment, collecting 46 student designers’ design-a

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Teodorine, Michelle, Genoveva Brigitta Indrawan, Michael Manuel, and Agung Stefanus Kembau. "Strategic Use of AI Image Generators for Product Development and Market Expansion In The Bakery Business." Journal of Accounting and Finance Management 5, no. 3 (2024): 297–313. https://doi.org/10.38035/jafm.v5i3.664.

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The evolution of Society 5.0, characterized by advanced technological integration, presents new opportunities for businesses to enhance operations and customer engagement. This study proposes the development of a comprehensive e-commerce website for Olson’s Patisserie, integrated with AI Image Generator technology, to improve digital sales and expand market reach. The proposal is informed by strategic insights from Porter's Five Forces, Fishbone analysis, and the VRIO framework, highlighting the need for enhanced digital marketing, technological integration, and operational efficiency. The web

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Tansri, Farrah Faustine, Nadine Monem, and Lee Weinberg. "Authenticity in Biased Diversity: Investigating the Language of Prompt Performances in AI Image Generators." Journal of Aesthetics, Creativity and Art Management 4, no. 1 (2025): 75–101. https://doi.org/10.59997/jacam.v4i1.5414.

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This paper reanalysis discriminatory biasness and ethicality in effects of artificial intelligent productions over the last decade of associated news reports. The rise of AI generators and generated contents has been increasing since the last two years after text-to-image models in deep learning machineries were reintroduced in 2015. This significantly brought volumes of positive public responses to the new discoveries, but this study however focuses more on evaluating overlooked biased problems interlinking the endangerment of the human positionality within artificial production. Performing u

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George, Babu, and Anupama Peter Mattathil. "Empowering African American Tourism Entrepreneurs with Generative AI: Bridging Innovation and Cultural Heritage." Societies 15, no. 2 (2025): 34. https://doi.org/10.3390/soc15020034.

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Generative artificial intelligence (AI) present opportunities and challenges for African American tourism entrepreneurs. This paper conceptually explores how tools like language models, image generators, and creative assistants can be used for content creation, personalized marketing, and deeper customer connections. Drawing on relevant innovation- and resource-related theories, this paper examines factors influencing the adoption of generative AI among African American tourism entrepreneurs. The analysis highlights the potential to address tourism-specific needs like virtual tours, multilingu

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Davis, Jason. "In a Digital World With Generative AI Detection Will Not be Enough." Newhouse Impact Journal 1, no. 1 (2024): 9–12. http://dx.doi.org/10.14305/jn.29960819.2024.1.1.01.

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Recent and dramatic improvements in AI driven large language models (LLMs), image generators, audio and video have fed an exponential growth in Generative AI applications and accessibility. The disruptive ripples of this rapid evolution have already begun to fundamentally impact how we create and consume content on a global scale. While the use of Generative AI has and will continue to enable massive increases in the speed and efficiency of content creation, it has come at the cost of uncomfortable conversations about transparency and the erosion of digital trust. To have any chance at actuall

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KRZYSZTOF, TRĘBSKI, MILOŠ LICHNER, MÁRIA NEMČÍKOVÁ, EVA CHOVANČÍK, TOMASZ PRAJZENDANC, and GABRIEL BENKA-RYBÁR. "A EUROPEAN VIEW ON THE ETHICAL USE OF ARTIFICIAL INTELLIGENCE (AI)." AD ALTA: Journal of Interdisciplinary Research 14, no. 2 (2024): 380–84. https://doi.org/10.33543/j.1402.380384.

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Artificial intelligence (AI) is one of the most exciting technology topics of recent years. It has the potential to fundamentally change the way we work, study, and use modern technologies in many areas, such as text and image generators. However, as the use of AI becomes more widespread, it is also worth being aware of the potential problems it brings. Given the increasing dependence of our systems on AI, how we address these dilemmas could have a key impact on the future of society. Among AI industry specialists, China (Taiwan) is said to produce the components for AI development, the United

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Nisha M V and J. Chriso Ricky Gill. "English Reading and Writing Enhancement for Deaf and Hard of Hearing (DHH) Students with Skybox AI: Utilization of AI Image Generators." Forum for Linguistic Studies 6, no. 6 (2024): 184–93. https://doi.org/10.30564/fls.v6i6.7745.

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The current study aims to evaluate the effectiveness of incorporating Artificial Intelligence (AI) for the instruction of reading and writing skills in the English language for students who are deaf and hard of hearing (DHH). The researcher employed Skybox AI, a three-dimensional artificial intelligence (AI) tool developed by Blockade Labs, enabling to independently generate sentences for the purpose of obtaining visual representations, for the study. The sample for the study comprised a total of 36 students at the higher secondary level, who were enrolled in two separate higher secondary inst

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Kuo, Michelle, and Pamela M. Lee. "Generative and Adversarial: Art and the Prospects of AI." October, no. 189 (2024): 3–5. http://dx.doi.org/10.1162/octo_a_00525.

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Abstract This essay serves as an introduction to the Questionnaire on Art and Machine Learning. It opens with the testimony of Sam Altman before the US Senate Judiciary Committee on Privacy, Technology and the Law in May 2023, following the launch of ChatGPT a year earlier. ChatGPT is part of a wave of generative AI: AI that not only classifies or analyzes information but also generates it. Media responses to ChatGPT and a range of other text-to-image and text-to-video generators—including Dall-E, Stable Diffusion, MidJourney, Deep AI, and Sora—tend to divide between “Boosterism” and “Doomeris

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Chen, Yirui, Xudong Huang, Quan Zhang, et al. "GIM: A Million-scale Benchmark for Generative Image Manipulation Detection and Localization." Proceedings of the AAAI Conference on Artificial Intelligence 39, no. 2 (2025): 2311–19. https://doi.org/10.1609/aaai.v39i2.32231.

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The extraordinary ability of generative models emerges as a new trend in image editing and generating realistic images, posing a serious threat to the trustworthiness of multimedia data and driving the research of image manipulation detection and location (IMDL). However, the lack of a large-scale data foundation makes the IMDL task unattainable. In this paper, we build a local manipulation data generation pipeline that integrates the powerful capabilities of SAM, LLM, and generative models. Upon this basis, we propose the GIM dataset, which has the following advantages: 1) Large scale, GIM in

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Carpino, Krista, and James Hutson. "A new canvas of learning: Enhancing formal analysis skills in AP art history through AI-generated Islamic art." Forum for Education Studies 2, no. 2 (2024): 1228. http://dx.doi.org/10.59400/fes.v2i2.1228.

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This study explores the use of AI art generators to enhance formal analysis skills in AP Art History students, with a focus on Islamic Art and Architecture. Students, often entering the course with high academic achievements, find the unique challenge of articulating detailed visual descriptions of artworks. The study’s approach involves using AI image-generation websites, like wepik.com, where students create AI images resembling Islamic artworks studied in class. This method aims to refine their descriptive skills, focusing on visual evidence rather than relying on identifying details. The c

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Abdulwadood, Isra, Meeti Mehta, Kassandra Carrion, et al. "AI Text-to-Image Generators and the Lack of Diversity in Hand Surgeon Demographic Representation." Plastic and Reconstructive Surgery - Global Open 12, S8 (2024): 4–5. https://doi.org/10.1097/01.gox.0001063832.89291.0d.

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Parekh, Aaditya, Suditi Mukadam, Tanvi Alawani, and Apoorva Dwivedi. "In the era of AI art, what is a designer's future? A Comparative Study of the Perception of AI Art among Indian Graphic Design Students and Graphic Design Professionals." International Journal of Design and Allied Sciences 3, no. 2 (2024): 30–38. https://doi.org/10.5281/zenodo.14580696.

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<strong>Abstract: </strong>This paper explores the "phygital" reality where digital and physical realms merge in liminal spaces, blurring boundaries such as those between work and leisure, as well as the ones between constructivist Design Research and automated foresight. Therefore, this paper aims to update the "Phygital" Matrix, a formerly co-designed tool, to project the post-pandemic future of business events, proposing automated foresight-generated scenarios. The authors do so through a novel, automated data collection method, including Large Language Models (LLMs). Therefore, t

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Sousa, Ana Elisa, and Paula Cardoso. "Use of Generative AI by Higher Education Students." Electronics 14, no. 7 (2025): 1258. https://doi.org/10.3390/electronics14071258.

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This research aims to explore the use, perceptions, and challenges associated with generative AI (GenAI) among higher education students. As GenAI technologies, such as language models, image generators, and code assistants, become increasingly prevalent in academic settings, it is essential to understand how students engage with these tools and their impact on their learning process. The study investigates students’ awareness, adoption patterns, and perceptions of generative AI’s role in academic tasks, alongside the benefits they identify and the challenges they face, including ethical conce

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Victoria Kujore, Aderonke Adebayo, Oluwabukola Sambakiu, and Balogun Segun Segbenu. "Transformative role of generative AI in marketing content creation and brand engagement strategies." GSC Advanced Research and Reviews 23, no. 3 (2025): 001–11. https://doi.org/10.30574/gscarr.2025.23.3.0145.

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Generative AI has emerged as a pivotal force reshaping the marketing landscape by revolutionizing content creation and customer engagement mechanisms. This research article examines how AI-driven tools are transforming traditional marketing approaches by enabling personalization at scale, enhancing creative workflows, and redefining brand-consumer interactions. The integration of generative AI technologies like large language models, image generators, and predictive analytics has fundamentally altered how marketers conceptualize, create, and distribute content across digital channels. Our anal

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Behar Villegas, Erick, Zhen Goh, and Gregory Scott Horowitt. "Designing a good story for better policies: Entrepreneurship at the crossroads of AI-powered visual storytelling and sensemaking." Human Technology 20, no. 3 (2024): 420–45. https://doi.org/10.14254/1795-6889.2024.20-3.1.

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Sensemaking and AI image generators can contribute as visual storytelling tools to a better comprehension of the life-worlds of entrepreneurs in policymaking. There is doubt about whether policymakers productively understand entrepreneurial realities for the sake of implementing decisions that help startups. Using entrepreneurial journeys of 18 startups in six countries, weak-signal triads and image prompts were derived from shared stories in order to visualize entrepreneurial realities. The advantage of visual storytelling materializes in the cognitive ease that narrative schemas yield. Resul

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Koswara, Asep, and Lina Herlina. "The Ethical Deviations of AI in Marketing Practices: A Critical Review from Halal Perspectives." Research of Islamic Economics 2, no. 2 (2025): 105–16. https://doi.org/10.58777/rie.v2i2.393.

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This paper critically examines the ethical deviations in Artificial Intelligence (AI) tools used for marketing practices from a halal perspective, focusing on Islamic ethical principles. The research highlights risks associated with AI technologies like generative AI (e.g., ChatGPT), image generators, face-swapping tools, and voice cloning, which can lead to misinformation, manipulation, and exploitation. These issues contradict Islamic values of justice (‘adl), integrity (amanah), and harm avoidance (mafsadah). Using a qualitative, exploratory approach, this study identifies key ethical viola

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