• Journal of the Institute of Convergence Signal Processing
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• v.23 no.2
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• pp.97-106
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• 2022

In this study, H&E staining is necessary to distinguish cells. However, dyeing directly requires a lot of money and time. The purpose is to convert the phase image of unstained cells to the amplitude image of stained cells. Image data taken with FPM was created with Phase image and Amplitude image using Matlab's parameters. Through normalization, a visually identifiable image was obtained. Through normalization, a visually distinguishable image was obtained. Using the GAN algorithm, a Fake Amplitude image similar to the Real Amplitude image was created based on the Phase image, and cells were distinguished by objectification using MASK R-CNN with the Fake Amplitude image As a result of the study, D loss max is 3.3e-1, min is 6.8e-2, G loss max is 6.9e-2, min is 2.9e-2, A loss max is 5.8e-1, min is 1.2e-1, Mask R-CNN max is 1.9e0, and min is 3.2e-1.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.42 no.2
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• pp.249-256
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• 2022

Various studies are being actively conducted to show that the real-time visualization technology that combines BIM (Building Information Modeling) and AR (Augmented Reality) helps to increase construction management decision-making and processing efficiency. However, when large-capacity BIM data is projected into AR, there are various limitations such as data transmission and connection problems and the image cut-off issue. To improve the high efficiency of visualizing, a mesh optimization algorithm based on the k-nearest neighbors (KNN) classification framework to reconstruct BIM data is proposed in place of existing mesh optimization methods that are complicated and cannot adequately handle meshes with numerous boundaries of the 3D models. In the proposed algorithm, our target BIM model is optimized with the Unity C# code based on triangle centroid concepts and classified using the KNN. As a result, the algorithm can check the number of mesh vertices and triangles before and after optimization of the entire model and each structure. In addition, it is able to optimize the mesh vertices of the original model by approximately 56 % and the triangles by about 42 %. Moreover, compared to the original model, the optimized model shows no visual differences in the model elements and information, meaning that high-performance visualization can be expected when using AR devices.

• Industry Promotion Research
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• v.8 no.3
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• pp.181-199
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• 2023

E-commerce is gradually upgrading from traditional text and image formats to short video and livestreaming formats. Livestreaming e-commerce enriches the content and forms of information dissemination and product display, enhances the consumer's shopping experience, and gradually becomes the mainstream new consumer scene. However, there are many negative phenomena in the development of livestreaming e-commerce, such as false propaganda, counterfeit goods, and various negative events, which seriously affect the level of consumer trust in livestreaming e-commerce. Trust is the core competitive factor of livestreaming e-commerce. Based on previous research on trust theory and combined with the characteristic elements of "people, goods, and scenes" of livestreaming e-commerce, this article constructs a trust model for livestreaming e-commerce, proposes hypotheses, and proves through empirical research that factors such as store characteristics, livestream host characteristics, brand image, product information, platform reputation, livestreaming situation, and trust tendency have a significant positive impact on consumer trust. Based on the research conclusions, this article provides insights and management suggestions, such as emphasizing the construction of store characteristic indicators, creating desirable livestream host characteristics, focusing on product brand building and selection, maintaining the display of product information, selecting suitable livestreaming platforms, and creating rich content for livestreaming situations.

• The Journal of Bigdata
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• v.6 no.2
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• pp.71-84
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• 2021

Since small and medium-sized enterprises fell short of the securement of technological competitiveness in the field of big data and artificial intelligence (AI) field-core technologies of the Fourth Industrial Revolution, it is important to strengthen the competitiveness of the overall industry through technology commercialization. In this study, we aimed to propose a priority related to technology transfer and commercialization for practical use of public research results. We utilized public research performance information, improving missing values of 6T classification by deep learning model with an ensemble method. Then, we conducted topic modeling to derive the converging fields of big data and AI. We classified the technology fields into four different segments in the technology portfolio based on technology activity and technology efficiency, estimating the potential of technology commercialization for those fields. We proposed a priority of technology commercialization for 10 detailed technology fields that require long-term investment. Through systematic analysis, active utilization of technology, and efficient technology transfer and commercialization can be promoted.

• Convergence Security Journal
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• v.22 no.3
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• pp.25-32
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• 2022

Recently, the image processing industry has been activated as deep learning-based technology is introduced in the image recognition and detection field. With the development of deep learning technology, learning model vulnerabilities for adversarial attacks continue to be reported. However, studies on countermeasures against poisoning attacks that inject malicious data during learning are insufficient. The conventional countermeasure against poisoning attacks has a limitation in that it is necessary to perform a separate detection and removal operation by examining the training data each time. Therefore, in this paper, we propose a technique for reducing the attack success rate by applying modifications to the training data and inference data without a separate detection and removal process for the poison data. The One-shot kill poison attack, a clean label poison attack proposed in previous studies, was used as an attack model. The attack performance was confirmed by dividing it into a general attacker and an intelligent attacker according to the attacker's attack strategy. According to the experimental results, when the proposed defense mechanism is applied, the attack success rate can be reduced by up to 65% compared to the conventional method.

• Journal of Korea Entertainment Industry Association
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• v.13 no.6
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• pp.135-142
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• 2019

This study explores the ways in which depaysement and its dreams function as a hallucinative allegory on the basis of the spiritual freedom of surrealism in Luis Bunuel's films: "The Discreet Charm of the Bourgeoisie" and "The Phantom of Liberty". In order to grasp the appearances of the sign in the scene of these films, it examines how he uses surrealism's dépaysement techniques such as the disposition of floating object, bipolarity, and physical contradictions of images. These emerging aesthetic views are as follows: the antipathy to reason, the critique of law and order, the aversion to ideology, and state apparatus. These finally aim at criticizing fundamental irrationality, thus paving a path for opening the possibility of liberation. He laid the foundation for a surrealist film by appropriatizing surrealist techniques to spread his claims. Therefore, this study argues that filmic scenes of dreams and hallucinations for a hallucinative allegory are closely related with the technique of depaysement network which summons the significance of surrealistic freedom in these films.

• Journal of Practical Agriculture & Fisheries Research
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• v.18 no.1
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• pp.101-112
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• 2016

Monitoring and control of the greenhouse environment play a decisive role in greenhouse crop production processes. The network system for greenhouse control was developed by using recent technologies of networking and wireless communications. In this paper, a remote monitoring and control system for greenhouse using a smartphone and a computer with internet has been developed. The system provides real-time remote greenhouse integrated management service which collects greenhouse environment information and controls greenhouse facilities based on sensors and equipments network. Graphical user interface for an integrated management system was designed with bases on the HMI and the experimental results showed that a sensor data and device status were collected by integrated management in real-time. Because the sensor data and device status can be displayed on a web page, transmitted using the server program to remote computer and mobile smartphone at the same time. The monitored-data can be downloaded, analyzed and saved from server program in real-time via mobile phone or internet at a remote place. Performance test results of the greenhouse control system has confirmed that all work successfully in accordance with the operating conditions. And data collections and display conditions, event actions, crops and equipments monitoring showed reliable results.

• Journal of Practical Engineering Education
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• v.14 no.3
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• pp.593-600
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• 2022

Various sensors such as lidar, radar, and camera are fused and used in autonomous vehicles. Rider and radar sensors are difficult to popularize because they are expensive equipment. In order to popularize autonomous vehicles, research that can replace expensive equipment is continuously being conducted. In this paper, we use a single camera that is inexpensive and can be easily mounted. We propose a method for detecting the wheels and adjacent lanes of a front-side vehicle of a driving vehicle and estimating distances. Our proposed method detects lanes and wheels from frame images after frame extraction via input images. In addition, the distance is measured and compared with the actual distance measured in the actual road environment. The distance could be calculated relatively accurately within the error range of ± 3 cm. Through this, it is expected that the camera can be used as an alternative means when the cost of autonomous vehicles is reduced or when the lidar or radar sensor fails.

• Korean Journal of Remote Sensing
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• v.40 no.1
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• pp.71-80
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• 2024

In this study, a proposed ensemble learning technique aims to enhance the semantic segmentation performance of images captured by Unmanned Aerial Vehicles (UAVs). With the increasing use of UAVs in fields such as urban planning, there has been active development of techniques utilizing deep learning segmentation methods for land cover segmentation. The study suggests a method that utilizes prominent segmentation models, namely U-Net, DeepLabV3, and Fully Convolutional Network (FCN), to improve segmentation prediction performance. The proposed approach integrates training loss, validation accuracy, and class score of the three segmentation models to enhance overall prediction performance. The method was applied and evaluated on a land cover segmentation problem involving seven classes: buildings,roads, parking lots, fields, trees, empty spaces, and areas with unspecified labels, using images captured by UAVs. The performance of the ensemble model was evaluated by mean Intersection over Union (mIoU), and the results of comparing the proposed ensemble model with the three existing segmentation methods showed that mIoU performance was improved. Consequently, the study confirms that the proposed technique can enhance the performance of semantic segmentation models.

• Information Systems Review
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• v.22 no.2
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• pp.167-199
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• 2020

The ICT-based curation as a series of experiences with the mobile exhibition-guide applications or guide programs in art galleries helps visitors fully immersed in the exhibition and allows them to have more informative and convenient guide experience at art galleries. This study aims to verify how the factors of ICT-based curation affects the commitment and satisfaction of visitors at art galleries, figure out whether the visitors' commitment has effects on their satisfaction, and then finally test the impact of their commitment and satisfaction on their revisit intention. In order to validate the cause-and-effect relationships between these factors, the ICT-based curation in this paper is categorized into five factors - gamification, quality of image/video information, quality of sound/text information, contextual offer, and instant connectivity. The main results of the study are as follows. First, only the gamification has significantly positive effects on the commitment of art gallery visitors, while other two factors - the instant connectivity, and the quality of sound/text information - have significantly positive effects on the satisfaction of visitors. Second, the commitment of visitors also has significantly positive effects on their satisfaction. Third, the commitment of the visitors don't have significantly positive relationship with their intention of revisit, but the satisfaction of the visitors have significantly positive relationship with their intention of revisit.