• Title/Summary/Keyword: model image

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Parameter Calibration of Laser Scan Camera for Measuring the Impact Point of Arrow (화살 탄착점 측정을 위한 레이저 스캔 카메라 파라미터 보정)

  • Baek, Gyeong-Dong;Cheon, Seong-Pyo;Lee, In-Seong;Kim, Sung-Shin
    • Journal of the Korean Society of Manufacturing Technology Engineers
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    • v.21 no.1
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    • pp.76-84
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    • 2012
  • This paper presents the measurement system of arrow's point of impact using laser scan camera and describes the image calibration method. The calibration process of distorted image is primarily divided into explicit and implicit method. Explicit method focuses on direct optical property using physical camera and its parameter adjustment functionality, while implicit method relies on a calibration plate which assumed relations between image pixels and target positions. To find the relations of image and target position in implicit method, we proposed the performance criteria based polynomial theorem model that overcome some limitations of conventional image calibration model such as over-fitting problem. The proposed method can be verified with 2D position of arrow that were taken by SICK Ranger-D50 laser scan camera.

Image Classification Model using web crawling and transfer learning (웹 크롤링과 전이학습을 활용한 이미지 분류 모델)

  • Lee, JuHyeok;Kim, Mi Hui
    • Journal of IKEEE
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    • v.26 no.4
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    • pp.639-646
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    • 2022
  • In this paper, to solve the large dataset problem, we collect images through an image collection method called web crawling and build datasets for use in image classification models through a data preprocessing process. We also propose a lightweight model that can automatically classify images by adding category values by incorporating transfer learning into the image classification model and an image classification model that reduces training time and achieves high accuracy.

Model Creation Algorithm for Multiple Moving Objects Tracking (다중이동물체 추적을 위한 모델생성 알고리즘)

  • 조남형;김하식;이명길;이주신
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2001.05a
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    • pp.633-637
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    • 2001
  • In this paper, we proposed model creation algorithm for multiple moving objects tracking. The proposed algorithm is divided that the initial model creation step as moving objects are entered into background image and the model reformation step in the moving objects tracking step. In the initial model creation step, the initial model is created by AND operating division image, divided using difference image and clustering method, and edge image of the current image. In the model reformation step, a new model was reformed in the every frame to adapt appearance change of moving objects using Hausdorff Distance and 2D-Logarithmic searching algorithm. We simulated for driving cart in the road. In the result, model was created over 98% in case of irregular approach direction of cars and tracking objects number.

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The Study on image correction of geometric distortion in digital radiography image (방사선투과영상의 기하학적 왜곡 보정에 관한 연구)

  • Park, S.K.;Ahn, Y.S.;Gil, D.S.
    • Journal of Power System Engineering
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    • v.15 no.4
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    • pp.25-30
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    • 2011
  • This study is made to provide with a method for correcting the geometric distortion of the digital radiography image by analytical approach based upon the inverse square law and Beer's law. This study is aimed to find out and improve a mathematic model of nonlinear type. Variations in the alignment of the X-ray source, the object, and imaging plate affect digital radiography images. A model which is expressed in parameter values; e.g, angle, position, absorption coefficient, length, width and pixel account of radiography source, is developed so as to match the sample image. For the best correction of the digital image that is the most similar to the model image, a correction technique based upon tangent is developed; then applied to the digital radiography images of steel tubes. As a result, the image correction is confirmed to be made successfully.

Analysis of Voter's Acceptance to Female Politician's Appearance

  • Kwon, Tae-Soon;Yang, Cheui-Kyung
    • Journal of Fashion Business
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    • v.8 no.6
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    • pp.103-112
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    • 2004
  • A Politician Appearance Acceptance Model (PAAM model) was formed and designed based on an analysis of how the electorate would accept a female politician. The PAAM model evaluated factors which influenced the voter's view of the female politician based on appearance. Causative factors were assessed that impacted acceptance based on appearance and analyzed whether voting was influenced by the appearance image; appearance image preferences for a female politician included the classic, dramatic, romantic and natural images. Through validations, the appearance image and competency had a causative factor that contributed to the acceptance of the politician image. The Classic Image demonstrated the strongest and most important image among the appearance images. As voters were more interested in the appearance image of a female politician, more emphasis and weight was on the appearance image during the voting selection process.

The Combined Effect and Therapeutic Effects of Color (변환학습을 이용한 장면 분류)

  • Shin, Seong-Yoon;Shin, Kwang-Seong;Nam, Soo-Tai
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2021.05a
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    • pp.338-339
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    • 2021
  • In this paper, we proposed a multiclass image scene classification method based on transform learning. The method using the Residual Network (ResNet) model which pre-trained on the large image dataset ImageNet for image classification. Compared with the image classification method of the CNN model, it can greatly improve the classification accuracy and efficiency

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Investigation of the Validity of the Image Model for the Analysis of Spherical Wave Reflection

  • Suh, Jin-Sung;Cheung, Wan-Sup
    • The Journal of the Acoustical Society of Korea
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    • v.17 no.3E
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    • pp.27-34
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    • 1998
  • The validity of the image model is investigated both analytically and experimentally in a half space with an infinite single reflecting surface present. This paper exploits the Sommerfeld integral that represents the exact solution for the reflected field in the half space. The solution is shown to be obtained by direct numerical integration which yields more accurate and stable results. The predicted results from the image model are compared to those from the direct numerical integration of the Sommerfeld integral. It is also experimentally demonstrated that the image model gives acceptably accurate results. It is of significance that this paper reveals analytical and experimental validation of using the image model except near-grazing incidence.

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Injection of Cultural-based Subjects into Stable Diffusion Image Generative Model

  • Amirah Alharbi;Reem Alluhibi;Maryam Saif;Nada Altalhi;Yara Alharthi
    • International Journal of Computer Science & Network Security
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    • v.24 no.2
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    • pp.1-14
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    • 2024
  • While text-to-image models have made remarkable progress in image synthesis, certain models, particularly generative diffusion models, have exhibited a noticeable bias to- wards generating images related to the culture of some developing countries. This paper introduces an empirical investigation aimed at mitigating the bias of image generative model. We achieve this by incorporating symbols representing Saudi culture into a stable diffusion model using the Dreambooth technique. CLIP score metric is used to assess the outcomes in this study. This paper also explores the impact of varying parameters for instance the quantity of training images and the learning rate. The findings reveal a substantial reduction in bias-related concerns and propose an innovative metric for evaluating cultural relevance.

Image classification and captioning model considering a CAM-based disagreement loss

  • Yoon, Yeo Chan;Park, So Young;Park, Soo Myoung;Lim, Heuiseok
    • ETRI Journal
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    • v.42 no.1
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    • pp.67-77
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    • 2020
  • Image captioning has received significant interest in recent years, and notable results have been achieved. Most previous approaches have focused on generating visual descriptions from images, whereas a few approaches have exploited visual descriptions for image classification. This study demonstrates that a good performance can be achieved for both description generation and image classification through an end-to-end joint learning approach with a loss function, which encourages each task to reach a consensus. When given images and visual descriptions, the proposed model learns a multimodal intermediate embedding, which can represent both the textual and visual characteristics of an object. The performance can be improved for both tasks by sharing the multimodal embedding. Through a novel loss function based on class activation mapping, which localizes the discriminative image region of a model, we achieve a higher score when the captioning and classification model reaches a consensus on the key parts of the object. Using the proposed model, we established a substantially improved performance for each task on the UCSD Birds and Oxford Flowers datasets.

Marketing Strategies for Improving Customer Attitude Using Airline Advertising Model: Focusing on Corporate Image and Brand Loyalty

  • OH, Ah-Hyun;PARK, Hye-Yoon
    • Journal of Distribution Science
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    • v.18 no.4
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    • pp.13-26
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    • 2020
  • Purpose: In this study, we will explore how the attributes of the airline's advertising model affect the corporate image and brand loyalty and the medium effect of the corporate image. Research design, data and methodology: Data collection for empirical analysis of this study was conducted online for about seven months from Jan. 2 to July 12, 2019, and was confirmed as part 292 of the final effective sample and used for demonstration analysis. Results: The property of the advertising model shown to have a significant impact in corporate image and brand loyalty. The property of the advertising, reliability and professionalism shown to have an impact in the social responsibility, but attractiveness is its responsibility and brand loyalty. Corporate images have been shown to play a meaningful role in the impact of advertising models on brand loyalty. Conclusions: The attributes of the airline's advertising model are divided into four categories, and reliability has the most influence on the image of a company and the formation of brand loyalty. The impact of the attributes of the advertising model on the relationship between corporate image and brand loyalty was investigated through an empirical analysis, and several implications were derived.