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- [Research] Prof. Simon Woo’s DASH Lab won the 3rd place in 2020 National Grand AI Challenge Competition by IITP
- [Data-driven Security HCI Lab(DASH LAB): Won the 3rd plan in 2020 National Grand AI Challenge Competition, Advisor: Prof. Simon Woo] DASH LAB (https://dash-lab.github.io) led by Prof. Simon Woo in Software/Applied Data Science Dept won the 3rd place as well as follow-up research grant in 2020 National Grand AI Challenge occurred in last December 2020, sponsored by IITP. Team members including Hanbeen Lee (MS student in AI dept), JoonHyung Kang (MS student in AI dept), Junyaup Kim (MS student in CS dept), Minha Kim (MS student in CS dept), Jaeju An (MS student in CS dept), Jenongho Kim (Senior in CS dept), Jinbeom Kim (Senior in CS dept), Gunwoo Park (Sophomore in CS dept), and Yoohyun Kim (Sophomore in CS dept) made tremendous efforts to prepare for the national AI competition for several months and finally won the 3rd place. They developed the novel light-weight deep learning-based objection detection mechanism to effectively detect anomalies, ‘fall down events’ in CCTV videos. The competition was very challenging because there were limited number of opportunity to submit the models, and it was required to collect a large amount of training set. Also, the model had to be light enough to run on the GPU inference server. DASH team’s achievement is outstanding given that the majority of participants and winners are from the industries that have a huge computing power as well as manpower. There are very few universities won the competition. DASH team will compete again this year, for the more complex challenge that requires the object detection algorithm to be run on the small edge device such as NVIDA Jetson Nano. Congrats for the hard-working team members!
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- 작성일 2021-01-21
- 조회수 889
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- [Research] Sang-ik Hyun, a Master's Program Student, Publishes a Paper on the ECCV 2020 International Conference
- Sang-ik Hyun, a Master's Program Student in the Research Lab of Prof. Jae-pil Heo, Publishes a Paper on the ECCV 2020 International Conference Hyun Sang-ik (first year of his master's degree program in Artificial Intelligence, Supervisor Jae-pil Heo) published a paper titled "VARSR: Variant Super-Resolution Network for Very Low Resolution Images" in the European Conference on Computer Vision (ECCV) 2020. ECCV is a top-tier academic conference in the field of computer vision, and this paper is the result of research conducted by Hyun Sang-ik when he was an undergraduate researcher. In this study, we presented a deep learning model that performs super-resolution of extremely low resolution images. If existing ultra-resolution technologies assumed a 1:1 low resolution-high resolution image mapping relationship, the VarSR Network in this paper was designed to produce variable results by modeling a 1:N mapping relationship in which a single low-resolution image could correspond to multiple high-resolution images. The proposed model can be used in a variety of real-world applications, including the identification of ultra-low resolution faces and license plate images. Sangeek Hyun and Jae-Pil Heo, “VarSR: Variational Super-Resolution Network for Very Low Resolution Images”, European Conference on Computer Vision (ECCV), 2020. Abstract: As is well known, single image super-resolution (SR) is an ill-posed problem where multiple high resolution (HR) images can be matched to one low resolution (LR) image due to the difference in their representation capabilities. Such many-to-one nature is particularly magnified when super-resolving with large upscaling factors from very low dimensional domains such as 8x8 resolution where detailed information of HR is hardly discovered. Most existing methods are optimized for deterministic generation of SR images under pre-defined objectives such as pixel-level reconstruction and thus limited to the one-to-one correspondence between LR and SR images against the nature. In this paper, we propose VarSR, Variational Super Resolution Network, that matches latent distributions of LR and HR images to recover the missing details. Specifically, we draw samples from the learned common latent distribution of LR and HR to generate diverse SR images as the many-to-one relationship. Experimental results validate that our method can produce more accurate and perceptually plausible SR images from very low resolutions compared to the deterministic techniques.
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- 작성일 2020-10-06
- 조회수 1079
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- [Research] DASH Lab participated in the AI Grand Challenge and won the first place
- A master's degree and undergraduate researchers from the Data-driven AI Security HCI Lab (DASH Lab) participated in the AI Grand Challenge organized by IITP(the Institute for Information and Communication Technology Promotion) and won the first place. AI Grand Challenge is a challenging and competitive R&D competition in which participants compete by developing algorithms that address the challenging project. The "2020 AI Grand Challenge" will be held as four stages for three years until 2022 with four tracks, including various emergency situations (behavioral cognition), violence (voice recognition), classification of daily waste (object recognition), and reduction of power consumption through artificial intelligence optimization. The goal of this challenge is to create a convenient and safe living environment through artificial intelligence technology. Professor Simon Woo’s research team participated in the behavioral recognition track (track 1) and won the first place by developing an algorithm that recognizes abnormal behavior of emergency patients based on image analysis. The AI Grand Challenge, which marks its fourth competition this year, will be held as four stages until 2022. This year, a total of 134 teams, including universities, research institutes, and companies, and 566 people participated in the first stage competition, and five excellent research teams were selected for each track. A total of 20 outstanding research teams will participate in the second stage competition, which will be held offline in November this year, with additional 200 million won (4 billion won in total) research funds. In the second stage of the competition, graduate students from the Department of Computer Engineering (Joon-yeop Jeon, So-won Jeon, etc.) undergraduate researcher (Jung-ho Kim, Gun-woo Park, and Hee-sung Kim, etc.) and students from the Department of Applied Artificial Intelligence and the Department of Data Science will participate. http://www.ai-challenge.kr/sub03/view/id/43
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- 작성일 2020-09-24
- 조회수 845
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- [Research] Graduate School of Convergence Security Track, Building Cyber Security Alliance
- Sungkyunkwan University Graduate School of Convergence Security Track, Building Cyber Security Alliance with 14 Universities Around the World Sungkyunkwan University Graduate School of Convergence Security Track aims to train convergence security experts in digital healthcare. Professor Hyung-kee Choi said, "We will lead the field of medical health convergence security with the objective of Creative N.E.X.T.” Sungkyunkwan University, which boasts a 622-year history, is drawing a vision to become a global leading university through this year's "VISION2020+”. It aims to become a global hub university for knowledge and talent networks that will secure the best reputation domestically and internationally by creating world-class education and research achievements. As part of this, Sungkyunkwan University plans to promote "research and talent training in the cyber security field" more systematically and professionally, as SKKU was selected as the "Convergence Security Core Talent Training Project" in April 2020. Sungkyunkwan University Graduate School of Convergence Security Track is preparing for the 2021 freshman year and curriculum that will foster convergence security professionals in the "digital health field”. We have formed the best teaching staffs for digital healthcare convergence security lectures, research and practice. Details are as below. - Seven full-time professors who specialized in security such as software security, embedded vulnerability analysis, user-centered security, and artificial intelligence security - Three full-time digital healthcare information security professors - Two industry-academic cooperation professors will be in charge of industry-academic cooperation The head professor Hyung-kee Choi said “The global biohealth industry, which was worth 1.9 trillion won in 2015, is expected to grow even more by 3.23 trillion won in 2025, and the digital healthcare sector will be driven as a major industry.” He also explained about digital healthcare field by saying “As seen in the ongoing COVID-19 situation, the untact and on-tack environment are now not an option. The smarting of the medical and health sectors will further be accelerated in addition to the needs of the era of rapid progress in the fourth industrial revolution or aging population.” In addition, Prof. Hyung-kee Choi emphasized that all medical health devices or devices linked to services expanding on top of the 5G connection will eventually face unprecedented security challenges, and the IT infrastructure of medical institutions and homes will desperately need security technologies to protect sensitive medical data. He added, "In order to cultivate professional technologies and talents that will solve security difficulties in the field of critical digital healthcare, SKKU will cooperate with 25 corporations including Cisco and Ahnlab, 14 international universities including Stanford and USC, and 3 research institutes, and medical institutions. Additionally, SKKU will run industrial activities, co-research, and talent exchanges.” Sungkyunkwan University Graduate School of Convergence Security Track, which selects a total of 15 students through regular and occasional recruitment, will operate as a curriculum that reflects the on-site demand of 25 consortia, and plans to cultivate talented people who will lead the medical health convergence security field with the educational goal of "Creative N.E.X.T." In particular, Sungkyunkwan University's Graduate School of Convergence Security Track aims to foster experts in 'Convergence Security Technology Development' so that it aims to improve development capabilities that interpret security needs in digital healthcare domains and develop optimal convergence security technologies to solve problems, rather than simply combining different elements. Moreover, practical education regarding information security will be provided so that they can act as convergence security experts not only in digital healthcare domains but also in other domains. "The Graduate School of Convergence Security Track at Sungkyunkwan University has established Cyber Security Alliance with 14 foreign universities to have a global platform that allows them to research and exchange lectures, and has differentiated strengths that no other graduate school can compete, including collaboration with on-campus graduate schools such as AI, Interaction Science, and Big Data graduate schools, and cooperation with the Samsung Hospital and medical schools." In particular, Professor Hyung-kee Choi emphasized that in line with the era of the 4th Industrial Revolution and the aging population, increasingly smart medical devices are facing unprecedented security problems due to services expanded based on 5G, and thus the IT infrastructure of medical institutions is in dire need of security technologies to protect sensitive data and safety. For this reason, it is necessary to develop core security source technologies in the "un-act" era that can meet the needs of industries that urgently need convergence security and open them with a sense of security. And this is the path for Sungkyunkwan University Graduate School of Convergence Security Track. "We're getting our first freshman year of 2021. To this end, we are gathering the capabilities of our professors in preparation for the selection and development of outstanding freshmen. In addition, we will continue to develop into a graduate school that grows after the completion of the Graduate School of Convergence Security Track Project.” https://www.boannews.com/media/view.asp?idx=90313&kind=
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- 작성일 2020-09-23
- 조회수 1146
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- [Student] 2020 Summer Industrial-Academic Intensive Learning Program Online Final Presentation
- 2020 Summer Industrial-Academic Intensive Learning Program Online Final Presentation The final presentation of the 2020 Summer Industrial-Academic Intensive Learning Program was held online on August 20 (Thu). A total of 18 teams had time to present their project results and receive feedback on the results for the last 8 weeks of summer vacation. 64 students and 10 professors from College of Computing participated online. Thank you to all the professors and students who worked hard during the summer vacation.
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- 작성일 2020-09-22
- 조회수 485
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- [Student] 2020 Summer Industrial-Academic Intensive Learning Program Interim-Presentation
- 2020 Summer Industrial-Academic Intensive Learning Program Interim-Presentation On August 3, the Interim-Presentation of 2020 Summer Industrial-Academic Intensive Learning Program was held online and offline simultaneously. A total of 18 teams presented for about 4.5 hours; the 5th week teams had final presentation and the 8th week teams had interim-presentation. 39 students attended offline and 46 students attended online. A total of eight professors from College of Computing participated.Thanks to all the students and professors who worked hard in preparing for the presentation.
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- 작성일 2020-09-22
- 조회수 523
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- [Research] Professors Park Eun-il and Han Jin-Young’s Research Team at the College of Software Research Way to Diagnose and Respond to Mental Illness Through Social Media
- Professors Park Eun-il and Han Jin-Young’s Research Team at the College of Software Research Way to Diagnose and Respond to Mental Illness Through Social Media Professors Park Eun-il and Han Jin-young research team at the College of Software (with master's course student Kim Ji-na and master’s/doctor integrated course student Lee Ji-eon) announced that they published a paper in the July issue of Scientific Reports entitled “Deep Learning Model for Predicting Mental Diseases through Social Media”. Through their research, the team introduced deep learning-based artificial intelligence models to diagnose mental illness early and respond to it and suggested the direction of future research. The research team developed a deep learning model that identifies various mental illnesses based on posts written by social media users to share their feelings. The artificial intelligence model presented an innovative result in identifying the mental disorders (e.g., depression, anxiety, bipolar disorder, schizophrenia, etc.) the users who wrote the posts were associated with. The research team used 633,385 Reddit posts, one of the largest social media platforms, and utilized deep learning classification models based on convolutional neural networks. Over 96% of those with the Autism Spectrum Disorder and a minimum of 75% with other mental disorders can be detected by the model. Convolutional Neural Network-Based Classification Model Structure The collected posts were expressed as a corpus to vectors using Word2vec, a representative vocabulary embedding technique, and a mental classification model was designed using the convolutional neural network. “Mental illness has recently emerged as a new social problem,” the research team said, “Utilizing the social media data created by users will greatly help us predict and treat mental illness early.” The research was conducted under strict management through IRB approval procedures, in consideration of the recent ethical debate over the utilization of big data in the information age. Based on this research, in the future the research team will develop a deep learning model that predicts potential mental illness using Korean text.
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- 작성일 2020-08-18
- 조회수 831
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- [Research] Professor Simon Woo's Research Laboratory Students Win CISC-S’20 Awards
- Professor Simon Woo's Research Laboratory Students Win Korean Society for Information Protection Awards SKKU students Jeon So-won (author, master's degree in software), Kang Joon-hyung (master's degree in artificial intelligence), and Hwang Jin-hee (doctor's degree in scientific investigation) won the Excellence Award (next-generation female scientist's thesis award) at the Summer Conference of the Korea Information Society(CISC-s'20). The issue of Deepfake pornography, which is used for fake celebrity pornographic videos and individual humiliation, has recently become a social issue in Korea. Deepfake technology is abused through the creation of maliciously crafted voice and images using deep learning technologies. More and more sophisticated Deepfake generation technologies are emerging in line with the development of artificial intelligence. Since Deepfake technologies are being abused for various crimes due to the rapid speed of development and high accessibility, there is a lack of legal regulations and countermeasures to cope with them. In order to respond to recent social issues resulting from Deepfake abuse, the research team analyzed the current status of Deepfake generation and detection technologies, domestic and international legal regulations, and limitations of current laws and presents new roles and countermeasures for individuals and institutions. Research Title: A Study on the State of Deep Fake Technology in Korea and its Institutional Countermeasures Authors: Jeon So-won, Kang Joon-hyung, Hwang Jin-hee, Woo Simon Sung-il (SKKU Department of Software, Artificial Intelligence, Scientific Investigation)
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- 작성일 2020-08-14
- 조회수 768
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- [Research] Professor Simon Woo’s Paper Published by IW3C2
- Professor Simon Woo's Research Laboratory Students Win Korean Society for Information Protection Awards SKKU students Jeon So-won (author, master's degree in software), Kang Joon-hyung (master's degree in artificial intelligence), and Hwang Jin-hee (doctor's degree in scientific investigation) won the Excellence Award (next-generation female scientist's thesis award) at the Summer Conference of the Korea Information Society(CISC-s'20). The issue of Deepfake pornography, which is used for fake celebrity pornographic videos and individual humiliation, has recently become a social issue in Korea. Deepfake technology is abused through the creation of maliciously crafted voice and images using deep learning technologies. More and more sophisticated Deepfake generation technologies are emerging in line with the development of artificial intelligence. Since Deepfake technologies are being abused for various crimes due to the rapid speed of development and high accessibility, there is a lack of legal regulations and countermeasures to cope with them. In order to respond to recent social issues resulting from Deepfake abuse, the research team analyzed the current status of Deepfake generation and detection technologies, domestic and international legal regulations, and limitations of current laws and presents new roles and countermeasures for individuals and institutions. Research Title: A Study on the State of Deep Fake Technology in Korea and its Institutional Countermeasures Authors: Jeon So-won, Kang Joon-hyung, Hwang Jin-hee, Woo Simon Sung-il (SKKU Department of Software, Artificial Intelligence, Scientific Investigation)
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- 작성일 2020-08-14
- 조회수 830
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- [Research] Professors Simon Woo and Hyung-Sik Kim’s Joint Research Team’s Paper Published by IW3C2
- Professor Simon Woo's Research Laboratory Students Win Korean Society for Information Protection Awards SKKU students Jeon So-won (author, master's degree in software), Kang Joon-hyung (master's degree in artificial intelligence), and Hwang Jin-hee (doctor's degree in scientific investigation) won the Excellence Award (next-generation female scientist's thesis award) at the Summer Conference of the Korea Information Society(CISC-s'20). The issue of Deepfake pornography, which is used for fake celebrity pornographic videos and individual humiliation, has recently become a social issue in Korea. Deepfake technology is abused through the creation of maliciously crafted voice and images using deep learning technologies. More and more sophisticated Deepfake generation technologies are emerging in line with the development of artificial intelligence. Since Deepfake technologies are being abused for various crimes due to the rapid speed of development and high accessibility, there is a lack of legal regulations and countermeasures to cope with them. In order to respond to recent social issues resulting from Deepfake abuse, the research team analyzed the current status of Deepfake generation and detection technologies, domestic and international legal regulations, and limitations of current laws and presents new roles and countermeasures for individuals and institutions. Research Title: A Study on the State of Deep Fake Technology in Korea and its Institutional Countermeasures Authors: Jeon So-won, Kang Joon-hyung, Hwang Jin-hee, Woo Simon Sung-il (SKKU Department of Software, Artificial Intelligence, Scientific Investigation)
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- 작성일 2020-08-14
- 조회수 814