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344 results on '"Kim, Hyun K."'

1. Can You Spot the AI-Generated Images? Distinguishing Fake Images Using Signal Detection Theory

Author

Park, Hayun, Kim, Gayoung, Lee, Danbi, Kim, Hyun K., Goos, Gerhard, Series Editor, Hartmanis, Juris, Founding Editor, van Leeuwen, Jan, Series Editor, Hutchison, David, Editorial Board Member, Kanade, Takeo, Editorial Board Member, Kittler, Josef, Editorial Board Member, Kleinberg, Jon M., Editorial Board Member, Kobsa, Alfred, Series Editor, Mattern, Friedemann, Editorial Board Member, Mitchell, John C., Editorial Board Member, Naor, Moni, Editorial Board Member, Nierstrasz, Oscar, Series Editor, Pandu Rangan, C., Editorial Board Member, Sudan, Madhu, Series Editor, Terzopoulos, Demetri, Editorial Board Member, Tygar, Doug, Editorial Board Member, Weikum, Gerhard, Series Editor, Vardi, Moshe Y, Series Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, and Rau, Pei-Luen Patrick, editor

Published
2024
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5. Understanding User Experience with AI-Assisted Writing Service

Author

Kim, Gayoung, Kim, Jiyeon, Kim, Hyun K., Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Degen, Helmut, editor, and Ntoa, Stavroula, editor

Published
2023
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7. High Resolution, Deep Imaging Using Confocal Time-of-flight Diffuse Optical Tomography

Author

Zhao, Yongyi, Raghuram, Ankit, Kim, Hyun K., Hielscher, Andreas H., Robinson, Jacob T., and Veeraraghavan, Ashok

Subjects
Electrical Engineering and Systems Science - Image and Video Processing, Physics - Optics
Abstract

Light scattering by tissue severely limits how deep beneath the surface one can image, and the spatial resolution one can obtain from these images. Diffuse optical tomography (DOT) is one of the most powerful techniques for imaging deep within tissue -- well beyond the conventional $\sim$10-15 mean scattering lengths tolerated by ballistic imaging techniques such as confocal and two-photon microscopy. Unfortunately, existing DOT systems are limited, achieving only centimeter-scale resolution. Furthermore, they suffer from slow acquisition times and slow reconstruction speeds making real-time imaging infeasible. We show that time-of-flight diffuse optical tomography (ToF-DOT) and its confocal variant (CToF-DOT), by exploiting the photon travel time information, allow us to achieve millimeter spatial resolution in the highly scattered diffusion regime ($> 50 $ mean free paths). In addition, we demonstrate two additional innovations: focusing on confocal measurements, and multiplexing the illumination sources allow us to significantly reduce the measurement acquisition time. Finally, we rely on a novel convolutional approximation that allows us to develop a fast reconstruction algorithm, achieving a 100$\times$ speedup in reconstruction time compared to traditional DOT reconstruction techniques. Together, we believe that these technical advances serve as the first step towards real-time, millimeter resolution, deep tissue imaging using DOT., Comment: The updated version includes edits made to our paper in response to suggestions from reviewers. These changes include: updated 3D image reconstruction results, additional comments on prior work, and further explanations of the linear model. In addition, we made a correction to figure 9, relabeling the x-axis to the correct scale. Finally, we also updated our acknowledgements

Published
2021
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9. User Experience Design for Defense Systems with AI

Author

Park, Sunyoung, Kim, Hyun K., Lee, Yuryeon, Park, Gyuwon, Lee, Danbi, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Kim, Jong-Hoon, editor, Singh, Madhusudan, editor, Khan, Javed, editor, Tiwary, Uma Shanker, editor, Sur, Marigankar, editor, and Singh, Dhananjay, editor

Published
2022
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10. Comparison of Tutorial Methods in Virtual Reality Games for a Better User Experience.

Author

Lee, Yuryeon, Kim, Guyeop, Lee, Kang Hoon, Park, Jaehyun, and Kim, Hyun K.

Abstract

The commercialisation of virtual reality (VR) headsets has made them more affordable and popular in gaming and entertainment. The natural interaction between the VR environment and users can maximise immersion and is crucial to VR gaming. Despite their growing popularity, educational VR games prioritise learning over immersion and require users to learn to interact with and play games using tutorials. Herein, we developed a game named Numverse with an accompanying tutorial. After selecting the tutorial content, we programmed the user interface and proposed a delivery method for the tutorial. We evaluated the user experience based on the effects of the presence or absence of the tutorial and its mode of delivery. The tutorials were of three types: no tutorial, instruction-screen tutorial, and context-sensitive tutorial, with the latter being the most preferred. The evaluation results show that presence, ability to learn controls, intrinsic motivation, and learning effectiveness are higher for the instruction-screen and context-sensitive tutorials than for no tutorial. On average, users experienced more motion sickness in the no-tutorial case, with a significant difference in nausea items. This study asserts the importance of tutorials in VR games, and its findings could improve user experience in future VR games. [ABSTRACT FROM AUTHOR]

Published
2024
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21. Effects of button colour and background on augmented reality interfaces.

Author

Yamin, Putra A. R., Park, Jaehyun, Kim, Hyun K., and Hussain, Muhammad

Subjects
COLLEGE students, USER-centered system design, COMPUTER software, STATISTICS, AUGMENTED reality, ANALYSIS of variance, TASK performance, OPTICAL head-mounted displays, SURVEYS, DESCRIPTIVE statistics, RESEARCH funding, DATA analysis, COLOR, GRAPHICAL user interfaces
Abstract

This study aims to understand the usability of common button colours and background choices in the existing augmented reality (AR) interface. AR is increasingly used in dynamic situations, such as driving using an AR head-up display. However, studies regarding the usability of AR interfaces, especially about the colours, are scarce. Twenty-four participants performed button selection tasks in an experiment using Microsoft HoloLens. Three measures (task completion time, the number of errors, and button colour visibility were collected for the 12 experimental conditions (3 backgrounds by 4 button colours). Significant differences were found in completion time between backgrounds and blue button visibility. On a moving background, the most effective button colour is orange, and the most minor effective button colour is blue. The results of this study can be used for colour choices in designing AR applications and devices. [ABSTRACT FROM AUTHOR]

Published
2024
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27. Contributors

Author

Alfano, Robert R., primary, Altoé, Mirella L., additional, Anand, Suresh, additional, Anderson, Afrouz, additional, Aram, Siamak, additional, Artemyev, Dmitry N., additional, Bajakian, Danielle R., additional, Bi, Renzhe, additional, Bratchenko, Ivan A., additional, Camp, Charles H., additional, Cao, Rui, additional, Chen, Jun, additional, Cheng, Ji-Xin, additional, Chowdhry, Fatima, additional, Cicchi, Riccardo, additional, Cicerone, Marcus T., additional, Condy, Emma, additional, Craddock, Travis J.A., additional, Dashtestani, Hadis, additional, Dholakia, Kishan, additional, Dong, Jing, additional, Duarte, F.J., additional, Fantini, Sergio, additional, Gandjbakhche, Amir, additional, Hameroff, Stuart R., additional, Hershman, Dawn L., additional, Hielscher, Andreas H., additional, Hu, Song, additional, Iftimia, Nicusor V., additional, Kainerstorfer, Jana M., additional, Kalinsky, Kevin, additional, Karamzadeh, Nader Shahni, additional, Kermanian, Riley, additional, Kim, Hyun K., additional, Kozlov, Sergey V., additional, Kurian, Philip, additional, Lee, Hyeon Jeong, additional, Lee, Martin, additional, Li, Jun, additional, Liu, Cheng-hui, additional, Ma, Qinglei, additional, Marone, Alessandro, additional, Miguel, Helga, additional, Mo, Haiding, additional, Moryatov, Alexander A., additional, Myakinin, Oleg O., additional, Nylk, Jonathan, additional, Olivo, Malini, additional, Orlov, Andrey E., additional, Pandey, Prabodh Kumar, additional, Pavone, Francesco S., additional, Pradhan, Asima, additional, Pu, Yang, additional, Ruesch, Alexander, additional, Shi, Lingyan, additional, Singh, Pankaj, additional, Sordillo, Laura A., additional, Sordillo, Peter P., additional, Tearney, Gary, additional, Tipping, William J., additional, Tuszynski, Jack A., additional, Wang, Wubao, additional, Wu, Binlin, additional, Xu, Min, additional, Yasuda, Ryohei, additional, Yu, Xinguang, additional, Zakharov, Valery P., additional, Zaragoza, Rachel, additional, Zhao, Youbo, additional, Zhou, Yan, additional, Zhu, Ke, additional, and Zuo, Zhiyi, additional

Published
2019
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29. Table S1 from Changes in Diffuse Optical Tomography Images During Early Stages of Neoadjuvant Chemotherapy Correlate with Tumor Response in Different Breast Cancer Subtypes

Author

Altoe, Mirella L., primary, Kalinsky, Kevin, primary, Marone, Alessandro, primary, Kim, Hyun K., primary, Guo, Hua, primary, Hibshoosh, Hanina, primary, Tejada, Mariella, primary, Crew, Katherine D., primary, Accordino, Melissa K., primary, Trivedi, Meghna S., primary, Hershman, Dawn L., primary, and Hielscher, Andreas H., primary

Published
2023
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30. Figure S2 from Changes in Diffuse Optical Tomography Images During Early Stages of Neoadjuvant Chemotherapy Correlate with Tumor Response in Different Breast Cancer Subtypes

Author

Altoe, Mirella L., primary, Kalinsky, Kevin, primary, Marone, Alessandro, primary, Kim, Hyun K., primary, Guo, Hua, primary, Hibshoosh, Hanina, primary, Tejada, Mariella, primary, Crew, Katherine D., primary, Accordino, Melissa K., primary, Trivedi, Meghna S., primary, Hershman, Dawn L., primary, and Hielscher, Andreas H., primary

Published
2023
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45. Early treatment window for predicting breast cancer response to neoadjuvant chemotherapy in the HR+/HER2- subgroup using diffuse optical tomography

Author

Altoé, Mirella L., primary, Marone, Alessandro, additional, Kim, Hyun K., additional, Tejada, Mariella, additional, Hibshoosh, Hanina, additional, Guo, Hua, additional, Crew, Katherine, additional, Accordino, Melissa K., additional, Trivedi, Meghna S., additional, Kalinsky, Kevin, additional, Hershman, Dawn L., additional, and Hielscher, Andreas H., additional

Published
2022
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46. Evidence for early prediction of pathologic complete response in breast cancer neoadjuvant chemotherapy based on pretreatment data obtained with dynamic diffuse optical tomography

Author

Ghosh, Shreyoshi, primary, Altoe, Mirella L., additional, Marone, Alessandro, additional, Kim, Hyun K., additional, Kalinsky, Kevin, additional, Guo, Hua, additional, Hibshoosh, Hanina, additional, Tejada, Mariella, additional, Crew, Katherine, additional, Accordino, M. K., additional, Trivedi, M. S., additional, Hershman, Dawn L., additional, and Hielscher, Andreas H., additional

Published
2022
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50. Abstract P3-02-04: Prediction of breast cancer response to neoadjuvant chemotherapy in different biological breast cancer subtypes using diffuse optical tomography

Author

Altoe, Mirella L, primary, Kalinsky, Kevin M, additional, Guo, Hua, additional, Hibshoosh, Hanina, additional, Tejada, Mariella, additional, Crew, Katherine D, additional, Accordino, Melissa K, additional, Trivedi, Meghna S, additional, Marone, Alessandro, additional, Kim, Hyun K, additional, Hielscher, Andreas H, additional, and Hershman, Dawn L, additional

Published
2022
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