ViaLab Member

Member:Anthony

2023-02-10T10:41:44+09:00

Back Anthony Kyung Guzman Leguel Graduated Student Department of Electrical Engineering Pusan National University Busan, 609-735, Republic of Korea Lab: Vehicle Intelligence and Autonomy Lab Tel: +82-51-510-7443 Email: kyung.guzman@gmail.com Research Interests *

Member:Brili

2023-02-10T10:41:51+09:00

Back Brilian Putra Amiruddin Graduated Student Department of Electrical Engineering Pusan National University Busan, 609-735, Republic of Korea Lab: Vehicle Intelligence and Autonomy Lab Tel: +82-51-510-7443 Email: brilianpamiruddin@gmail.com Research Interests *

Member:Minji

2026-03-30T14:32:38+09:00

Back Min-Ji Kim Graduated Student Department of Electronic Engineering Pusan National University Busan, 609-735, Republic of Korea Lab: Vehicle Intelligence and Autonomy Lab Tel: +82-51-510-7443 Email: minji3169@naver.com Research Interests *

Member:Minwoo

2026-03-13T15:38:39+09:00

Back Minwoo Chee Graduated Student Department of Electrical Engineering Pusan National University Busan, 609-735, Republic of Korea Lab: Vehicle Intelligence and Autonomy Lab Tel: +82-51-510-7443 Email: michael1998@naver.com Currently Engineer @ Kia Motors Research Interests * Multi-Agent Path Finding

Member:SoonjaeKim

2023-02-10T10:41:25+09:00

Back Soonjae kim Graduated Student Department of Electrical Engineering Pusan National University Busan, 609-735, Republic of Korea Lab: Vehicle Intelligence and Autonomy Lab Tel: +82-51-510-7443 Email: soonjae7379@pusan.ac.kr Research Interests * Control and Autonomous Driving

Member:SungilKim

2026-03-13T15:48:03+09:00

Back Sungil Kim Graduated Student Department of Electrical Engineering Pusan National University Busan, 609-735, Republic of Korea Lab: Vehicle Intelligence and Autonomy Lab Tel: +82-51-510-7443 Email: sungil0615@gmail.com Research Interests *

Member:Sungwook

2026-03-13T15:49:49+09:00

Back Seong-Wook Hwang Graduated Student Department of Electrical Engineering Pusan National University Busan, 609-735, Republic of Korea Lab: Vehicle Intelligence and Autonomy Lab Tel: +82-51-510-7443 Email: Research Interests *

Member:howonjung

2020-11-13T17:19:58+09:00

Back Howon Jung Graduate Student Department of Electrical Engineering Pusan National University Busan, 609-735, Republic of Korea Lab: Networked Smart Systems Lab Tel: +82-51-510-7443 Research Interests *

Member:hyjeong

2026-03-04T15:15:33+09:00

Back Prof. Han-You Jeong Professor School of Electrical and Electronics Engineering Pusan National University Busan, 609-735, Republic of Korea Lab: Vehicle Intelligence and Autonomy Lab Office: Room # 10417, Engineering building #10 (Bldg. 207) Tel: +82-51-510-7332 Email: hyjeong@pusan.ac.kr

Member:jaehyunpark

2023-02-10T10:41:15+09:00

Back Jae-Hyun Park Master Department of Electrical Engineering Pusan National University Busan, 609-735, Republic of Korea Lab: Vehicle Intelligence and Autonomy Lab Tel: +82-51-510-7443 Email: popwogus@gmail.com Research Interests *

Member:joonunPark

2021-12-29T18:12:50+09:00

Back Joonun Park Graduated Student Department of Electrical and Electronic Engineering Pusan National University Busan, 609-735, Republic of Korea Lab: Networked Smart Systems Lab Tel: +82-51-510-7443 Research Interests *

Member:nguyenhoahung

2023-02-09T15:37:05+09:00

Back Dr. Hoa-Hung Nguyen Ph.D. Department of Electrical Engineering Pusan National University Busan, 609-735, Republic of Korea Lab: Vehicle Intelligence and Autonomy Lab Tel: +82-51-510-7443 Email: nguyenhoahungit@gmail.com Research Interests * Cooperative Driver Assistance Systems

Member:sungbeanJo

2022-01-06T16:11:58+09:00

Back Sungbean Jo Graduated Student Department of Electrical Engineering Pusan National University Busan, 609-735, Republic of Korea Lab: Networked Smart Systems Lab Tel: +82-51-510-7443 Research Interests * Reinforcement Learniing for Autonomous Driving

Member:sungbeanJo_GG

2020-11-24T20:25:55+09:00

The trial has successfully demonstrated ROSEN’s methodology to estimate the depth of cover over pipelines. This includes producing an accurate pipeline centreline from data obtained during a routine internal inspection, combined with ground elevation data available from the Environment Agency (EA) to calculate depth of cover. • The results of the calculation have been validated against infield depth of cover measurements obtained using a pipe and cable locator. The accuracy of the depth of cover…

Member:sungbeanJo_anaconda

2021-01-08T11:44:20+09:00

아나콘다 설치 * 다운로드 페이지 * * 윈도우의 경우 환경변수 설정 필요, 설치 시 체크해주면 자동으로 완료. 아나콘다 가상환경 생성 및 tensorflow용 세팅 * 가상환경 생성 *

Member:sungbeanJo_gg

2020-11-24T21:57:38+09:00

TomTom as a world leader in HD Map technologies and Elektrobit as a leading supplier of automotive software and development solutions have jointly been offering map-based vehicle horizon solutions since 2017. ADASIS v2 vehicle horizons based on TomTom’s ADAS Map are industry standard today and can be found in many implementations in the marketplace. TomTom and Elektrobit work on the next-generation OTA-based stand-alone ADASIS v2 product. ADASIS v3 provides a standardized way to supply and distr…

Member:sungbeanJo_paper

2021-04-21T22:08:38+09:00

get_config_param active timestamp_mode TIME_FROM_INTERNAL_OSC get_config_param active multipurpose_io_mode OUTPUT_OFF get_config_param active sync_pulse_in_polarity ACTIVE_LOW get_config_param active nmea_in_polarity ACTIVE_HIGH get_config_param active nmea_baud_rate

Member:sungbeanJo_pdf

2021-01-05T14:28:05+09:00

We present a method for detecting objects in images using a single deep neural network. Our approach, named SSD, discretizes the output space of bounding boxes into a set of default boxes over different aspect ratios and scales per feature map location. At prediction time, the network generates scores for the presence of each object category in each default box and produces adjustments to the box to better match the object shape. Additionally, the network combines predictions from multiple featu…

Member:sungbeanJo_tran

2021-01-18T16:21:54+09:00

Choosing scales and aspect ratios for default boxes To handle different object scales, some methods [4,9] suggest processing the image at different sizes and combining the results afterwards. However, by utilizing feature maps from several different layers in a single network for prediction we can mimic the same effect, while also sharing parameters across all object scales. Previous works [10,11] have shown that using feature maps from the lower layers can improve semantic segmentation quality …

Member:vialab

2026-03-19T05:33:07+09:00

Faculty * Prof. Han-You Jeong Ph. D. Students * Jae-Hyun Park * Sungil Kim M. S. Students * Minwoo Chee * Sung-Wook Hwang (Combined Bachelor/Master Degree) * Min-Ji Kim Alumni Ph. D. * Hoa-Hung Nguyen (2020) Master * Brilian Putra Amiruddin (2025) - Engineer @ Daewoong Pharmaceutical * Anthony Kyung Guzman Leguel (2024) - Ph. D. @ University of Zaragoza * Sungbean Jo (2022) - Engineer @ Hyundai MOBIS * Howon Jung (2021) - Researcher @