권오빈 교수
Oh-Bin Kwon
서울대학교 · 의학
연구실 소개
권오빈 교수의 연구실은 신경생물학과 인공지능 기반 시각적 인식 기술을 융합한 연구를 주도하고 있습니다. 정신질환의 신경생물학적 기반을 밝히는 데 초점을 맞춘 신경전달물질 및 수용체 기반 메커니즘 연구와 동시에, 시각 기반 자율주행 및 환경 인식을 위한 지도 기반 레이더 지도 및 그래프 기반 메모리 구조 설계 등 첨단 시각 인식 기술 개발도 함께 진행하고 있습니다. 특히, 뇌 기능과 인공지능의 상호보완적 접근을 통해 인지 기능 향상과 지능형 로봇 주행 기술의 혁신을 추구하고 있습니다.
연구 현황
연구 성과 추이
표시된 성과는 수집된 데이터 기준으로 산출되며, 일부 차이가 있을 수 있습니다.
주요 논문
15Energy expenditure and energy intake need to be balanced to maintain proper energy homeostasis. Energy homeostasis is tightly regulated by the central nervous system, and the hypothalamus is the primary center for the regulation of energy balance. The hypothalamus exerts its effect through both humoral and neuronal mechanisms, and each hypothalamic area has a distinct role in the regulation of energy expenditure. Recent studies have advanced the understanding of the molecular regulation of energ
We present a novel graph-structured memory for visual navigation, called visual graph memory (VGM), which consists of unsupervised image representations obtained from navigation history. The proposed VGM is constructed incrementally based on the similarities among the unsupervised representations of observed images, and these representations are learned from an unlabeled image dataset. We also propose a navigation framework that can utilize the proposed VGM to tackle visual navigation problems.
This Korean acromegaly survey offers a realistic overview of the predominant epidemiological characteristics of acromegaly in Korea. Annual incidence was at a similar level with western countries. Efforts to diagnose and control the disease earlier are recommended.
We propose a novel type of map for visual navigation, a renderable neural radiance map (RNR-Map), which is designed to contain the overall visual information of a 3D environment. The RNR-Map has a grid form and consists of latent codes at each pixel. These latent codes are embedded from image observations, and can be converted to the neural radiance field which enables image rendering given a camera pose. The recorded latent codes implicitly contain visual information about the environment, whic
Serum serotonin levels displayed meal-related diurnal oscillations, which were disrupted by fasting and obesity. These findings suggest the possibility that circulating serotonin modulates metabolic function in humans.
The dipeptidyl peptidase-4 (DPP4) inhibitors have become widely used antidiabetic medication. They control glycemia by interacting with serum DPP4 to interfere catalyzation of incretins. The aim of this pilot study was to discover the DPP4 polymorphisms that could affect the efficacy of vildagliptin, a DPP-4 inhibitor in diabetic patients.
We identified distinct multi-omic signatures in individuals with ESRD or sarcopenia, providing new insights into the mechanisms underlying ESRD-related muscle wasting, which differ from primary sarcopenia. These findings may support interventions for context-dependent muscle loss and contribute to the development of targeted treatments and preventive strategies for muscle wasting.
This paper tackles a localization problem in large-scale indoor environments with wayfinding maps. A wayfinding map abstractly portrays the environment, and humans can localize themselves based on the map. However, when it comes to using it for robot localization, large geometrical discrepancies between the wayfinding map and the real world make it hard to use conventional localization methods. Our objective is to estimate a robot pose within a wayfinding map, utilizing RGB images from perspecti
This paper tackles the image-goal navigation problem, in which a robot needs to find a goal pose based on the target image. The proposed algorithm estimates the geometric information between the target pose and the current pose of the robot. Using the estimated geometric information, the navigation policy predicts the most appropriate actions to reach the target pose. We evaluated our method using the Habitat simulator with the Gibson dataset, which provides photo-realistic indoor environments.
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