• International Journal of Advanced Culture Technology
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• v.11 no.1
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• pp.283-289
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• 2023

AI is bringing about drastic changes not only in the aspect of technologies but also in society and culture. Medical AI based on deep learning have developed rapidly. Especially, the field of medical image analysis has been proven that AI can identify the characteristics of medical images more accurately and quickly than clinicians. Evaluating the latest results of the AI-based medical image processing is important for the implication for the development direction of medical AI. In this paper, we analyze and evaluate the latest trends in AI-based medical image analysis, which is showing great achievements in the field of medical AI in the healthcare industry. We analyze deep learning models for medical image analysis and AI-based medical image segmentation for quantitative analysis. Also, we evaluate the future development direction in terms of marketability as well as the size and characteristics of the medical AI market and the restrictions to market growth. For evaluating the latest trend in the deep learning-based medical image processing, we analyze the latest research results on the deep learning-based medical image processing and data of medical AI market. The analyzed trends provide the overall views and implication for the developing deep learning in the medical fields.

• International Journal of Internet, Broadcasting and Communication
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• v.14 no.2
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• pp.212-218
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• 2022

In this paper, the necessity of AI video interview arises when conducting an interview for acquisition of excellent talent in a non-face-to-face situation due to similar situations such as Covid-19. As a matter to be supplemented in general AI interviews, it is difficult to evaluate the reliability and qualitative factors. In addition, the AI interview is conducted not in a two-way Q&A, rather in a one-sided Q&A process. This paper intends to fuse the advantages of existing AI interviews and video interviews. When conducting an interview using AI image analysis technology, it supplements subjective information that evaluates interview management and provides quantitative analysis data and HR expert data. In this paper, image-based multi-modal AI image analysis technology, bioanalysis-based HR analysis technology, and web RTC-based P2P image communication technology are applied. The goal of applying this technology is to propose a method in which biological analysis results (gaze, posture, voice, gesture, landmark) and HR information (opinions or features based on user propensity) can be processed on a single screen to select the right person for the hire.

• International Journal of Advanced Culture Technology
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• v.11 no.2
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• pp.403-408
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• 2023

The widespread discussion of AI-generated content, fueled by the emergence of consumer applications like ChatGPT and Midjourney, has attracted significant attention. Among various AI applications, AI painting has gained popularity due to its mature technology, user-friendly nature, and excellent output quality, resulting in a rapid growth in user numbers. Midjourney and Stable Diffusion are two of the most widely used AI painting tools by users. In this study, the author adopts a perspective that represents the general public and utilizes case studies and comparative analysis to summarize the distinctive features and differences between Midjourney and Stable Diffusion in the context of AI character illustration. The aim is to provide informative material forthose interested in AI painting and lay a solid foundation for further in-depth research on AI-generated content. The research findings indicate that both software can generate excellent character images but with distinct features.

• Journal of Information Technology Applications and Management
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• v.31 no.4
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• pp.99-119
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• 2024

Focusing on the rapid progress of image generation AI, this study examines the changes in talent required according to changes in the production process of the content industry, and proposes an educational management plan for the subject and comparative department of the university's animation major. First, through environmental analysis, the trend of the animation content industry is analyzed in three stages, and the necessity of producing AI-adapted content talent is derived by re-establishing the talent image of the university's animation major and introducing it into rapid education. Next, we present a case designed by applying teaching methods to improve technology convergence capabilities and project-oriented capabilities by presenting subject and non-curricular cases operated in the animation department of the researcher's university. Through this, we propose the necessity of education to cultivate animation content talent who can play technical and administrative roles by utilizing various AI systems in the future. The goal of this study is to establish a cornerstone study by presenting application cases and having the status of a university as a talent supplier that can lead the content industry beyond the era of AI content production that breaks the boundaries of genres between contents. In conclusion, it is intended to propose the application of education to create value through technology convergence capabilities and project-oriented capabilities to cultivate AI-adapted content talents.

• The Journal of the Convergence on Culture Technology
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• v.9 no.4
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• pp.667-679
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• 2023

The advent of image generative AI has made it possible for people who are not experts in art and design to create finished artworks through text input. With the increasing availability of generated images and their impact on the art industry, there is a need for research on how users perceive the process of co-creating with AI. In this study, we conducted an experimental study to investigate the expected and experienced processes of image generative AI creation among general users and to find out which processes affect users' sense of creative agency. The results showed that there was a gap between the expected and experienced creative process, and users tended to perceive a low sense of creative agency. We recommend eight ways that AI can act as an enabler to support users' creative intentions so that they can experience a higher sense of creative agency. This study can contribute to the future development of image-generating AI by considering user-centered creative experiences.

• Journal of the Korean Society of Radiology
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• v.83 no.6
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• pp.1229-1239
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• 2022

Recently, artificial intelligence (AI) technology has shown potential clinical utility in a wide range of MRI fields. In particular, AI models for improving the efficiency of the image acquisition process and the quality of reconstructed images are being actively developed by the MR research community. AI is expected to further reduce acquisition times in various MRI protocols used in clinical practice when compared to current parallel imaging techniques. Additionally, AI can help with tasks such as planning, parameter optimization, artifact reduction, and quality assessment. Furthermore, AI is being actively applied to automate MR image analysis such as image registration, segmentation, and object detection. For this reason, it is important to consider the effects of protocols or devices in MR image analysis. In this review article, we briefly introduced issues related to AI application of MR image acquisition and reconstruction.

• Journal of Bio-Environment Control
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• v.33 no.1
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• pp.1-11
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• 2024

In this study, five artificial intelligence (AI) models: Inception v3, SqueezeNet (local), VGG-16, Painters, and DeepLoc were used to classify tea leaf diseases. Eight image categories were used: healthy, algal leaf spot, anthracnose, bird's eye spot, brown blight, gray blight, red leaf spot, and white spot. Software used in this study was Orange 3 which functions as a Python library for visual programming, that operates through an interface that generates workflows to visually manipulate and analyze the data. The precision of each AI model was recorded to select the ideal AI model. All models were trained using the Adam solver, rectified linear unit activation function, 100 neurons in the hidden layers, 200 maximum number of iterations in the neural network, and 0.0001 regularizations. To extend the functionality of Orange 3, new add-ons can be installed and, this study image analytics add-on was newly added which is required for image analysis. For the training model, the import image, image embedding, neural network, test and score, and confusion matrix widgets were used, whereas the import images, image embedding, predictions, and image viewer widgets were used for the prediction. Precisions of the neural networks of the five AI models (Inception v3, SqueezeNet (local), VGG-16, Painters, and DeepLoc) were 0.807, 0.901, 0.780, 0.800, and 0.771, respectively. Finally, the SqueezeNet (local) model was selected as the optimal AI model for the detection of tea diseases using tea leaf images owing to its high precision and good performance throughout the confusion matrix.

• International Journal of Computer Science & Network Security
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• v.24 no.1
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• pp.9-16
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• 2024

AI or Artificial Intelligence has been a significant tool used in the organisational backgrounds for an effective improvement in the management methods. The processing of the information and the analysis of the data for the further achievement of heightened efficiency can be performed by AI through its data analytics measures. In the medical field, AI has been integrated for an improvement within the management of the medical services and to note a rise in the levels of customer satisfaction. With the benefits of reasoning and problem solving, AI has been able to initiate a range of benefits for both the consumers and the medical personnel. The main benefits which have been noted in the integration of AI would be integrated into the study. The issues which are noted with the integrated AI usage for the medical sector would also be identified in the study. Medical Image Processing has been seen to integrate 3D image datasets with the medical industry, in terms of Computed Tomography (CT) or Magnetic Resonance Imaging (MRI). The usage of such medical devices have occurred in the diagnosis of the patients, the development of guidance towards medical intervention and an overall increase in the medical efficiency. The study would focus on such different tools, adhered with AI for increased medical improvement.

• The Journal of Economics, Marketing and Management
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• v.12 no.1
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• pp.29-38
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• 2024

Purpose: The purpose of this study is to explore the perceptions of millennials and Generation Z regarding AI applications in marketing, an area that has been rarely explored in previous researches. This study formulated research questions how millennials and Generation Z perceive the impact of brand image, AI-assistant customer service, affective factor, immersive experience, cognitive factor social factor and competitiveness of products and brands on overall attitude through the lens of AI applications in marketing. Additionally, this study also explored the influence of overall attitudes on satisfaction, intention to use, and loyalty towards AI applications. Research design, data and methodology: To gather data, this study employed an online survey conducted in collaboration with a reputable research organization. This study utilized factor analysis, ANOVA, and regression analysis for data analysis. Results: The findings revealed that the impact of brand image, AI-assistant customer service, and competitiveness on attitude demonstrated significance in both millennials and generation Z cohorts. The study identified that cognitive and social factors significantly influenced attitudes among millennials, whereas affective and immersive experiences showed significance in influencing attitudes among Generation Z. Conclusions: The findings offer valuable managerial implications, shedding light on the application of AI in marketing with distinct perspectives between millennials and Generation Z.

• International Journal of Advanced Culture Technology
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• v.11 no.2
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• pp.409-414
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• 2023

In recent years, the emergence of a number of AI image generation software represented by [Midjourney] has brought great impetus to the development of the field of AI-assisted art creation. Compared with the traditional hand-painted digital painting with the aid of electronic equipment, broke the traditional sense of animation character creation logic.This paper analyzes the application of AI technology in the field of animation character design through the practice of two-dimensional animation character . This is having a significant impact on the productivity and innovation of animation design and character modeling. The key results of the analysis indicate that AI technology, particularly through the utilization of "Midjourney,"enables the automation of certain design tasks, provides innovative approaches, and generates visually appealing and realistic characters. In conclusion, the integration of AI technology, specifically the application of "Midjourney," brings a new dimension to animation character design. The utilization of AI image generation software facilitates streamlined workflows, sparks creativity, and improves the overall quality of animated characters. As the animation industry continues to evolve, AI-assisted tools like "Midjourney" hold great potential for further advancement and innovation.