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김은솔 교수

Eun‐Sol Kim

한양대학교 컴퓨터소프트웨어학부 · 컴퓨터과학

연구실 소개

김은솔 교수의 연구실은 주로 인공지능과 신경망 기반의 다중모odal 학습, 특히 인간-객체 상호작용 검출, 신호 처리 기반의 그래프 신경망, 그리고 유연한 하드웨어 기반 신경망 설계에 초점을 맞추고 있습니다. 특히 트랜스포머 기반 아키텍처를 활용한 이미지 인식 및 다중모달 통합 기술, 유기 메모리스토어를 활용한 생체 유사 학습 성능을 구현한 인공 synapse 개발 등 혁신적인 기술 개발을 선도하고 있습니다. 또한 생물학적 생장 조절 메커니즘과도 연계된 구조적 인식 기술 연구를 통해 실생활 응용 가능성을 넓히고 있습니다.

HOI 검출멀티모달 학습유연한 신경망메모리스토어신호 기반 그래프 신경망

연구 현황

논문 수
76
총 인용 수
851
최근 5년 논문
32
주요 분야
컴퓨터과학

연구 성과 추이

표시된 성과는 수집된 데이터 기준으로 산출되며, 일부 차이가 있을 수 있습니다.

5개년 연도별 논문 게재 수
32총합
2022
2023
2024
2025
2026
5개년 연도별 피인용 수
288총합
20222023202420252026

주요 논문

15
1
논문|인용수 261·2021
HOTR: End-to-End Human-Object Interaction Detection with Transformers
Bumsoo Kim, Junhyun Lee, Jaewoo Kang, Eun‐Sol Kim, Hyunwoo J. Kim

Human-Object Interaction (HOI) detection is a task of identifying "a set of interactions" in an image, which involves the i) localization of the subject (i.e., humans) and target (i.e., objects) of interaction, and ii) the classification of the interaction labels. Most existing methods have indirectly addressed this task by detecting human and object instances and individually inferring every pair of the detected instances. In this paper, we present a novel framework, referred by HOTR, which dir

Computer Vision and Pattern RecognitionComputer Science
2
논문|인용수 82·2020
Hypergraph Attention Networks for Multimodal Learning
Eun‐Sol Kim, Woo Young Kang, Kyoung-Woon On, Yu‐Jung Heo, Byoung‐Tak Zhang

One of the fundamental problems that arise in multimodal learning tasks is the disparity of information levels between different modalities. To resolve this problem, we propose Hypergraph Attention Networks (HANs), which define a common semantic space among the modalities with symbolic graphs and extract a joint representation of the modalities based on a co-attention map constructed in the semantic space. HANs follow the process: constructing the common semantic space with symbolic graphs of ea

Computer Vision and Pattern RecognitionComputer Science
3
논문|인용수 78·2022
MSTR: Multi-Scale Transformer for End-to-End Human-Object Interaction Detection
Bumsoo Kim, Jonghwan Mun, Kyoung-Woon On, Minchul Shin, Junhyun Lee, Eun‐Sol Kim
2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Human-Object Interaction (HOI) detection is the task of identifying a set of (human, object, interaction) triplets from an image. Recent work proposed transformer encoder-decoder architectures that successfully eliminated the need for many hand-designed components in HOI detection through end-to-end training. However, they are limited to single-scale feature resolution, providing suboptimal performance in scenes containing humans, objects, and their interactions with vastly different scales and

Computer Vision and Pattern RecognitionComputer Science
4
논문|인용수 70·2023
Organic Memristor‐Based Flexible Neural Networks with Bio‐Realistic Synaptic Plasticity for Complex Combinatorial Optimization
Hyeongwook Kim, Mi‐Seong Kim, Aejin Lee, Hea‐Lim Park, Jaewon Jang, Jin‐Hyuk Bae, In Man Kang, Eun‐Sol Kim, Sin‐Hyung Lee
SJR Q1Advanced ScienceOA

Hardware neural networks with mechanical flexibility are promising next-generation computing systems for smart wearable electronics. Several studies have been conducted on flexible neural networks for practical applications; however, developing systems with complete synaptic plasticity for combinatorial optimization remains challenging. In this study, the metal-ion injection density is explored as a diffusive parameter of the conductive filament in organic memristors. Additionally, a flexible ar

Electrical and Electronic EngineeringEngineering
5
논문|인용수 44·2015
PHABULOSA Controls the Quiescent Center-Independent Root Meristem Activities in Arabidopsis thaliana
José Sebastián, Kook Hui Ryu, Jing Zhou, Danuše Tarkowská, Petr Tarkowski, Young-Hee Cho, Sang-Dong Yoo, Eun-Sol Kim, Ji‐Young Lee
SJR Q1PLoS GeneticsOA

Plant growth depends on stem cell niches in meristems. In the root apical meristem, the quiescent center (QC) cells form a niche together with the surrounding stem cells. Stem cells produce daughter cells that are displaced into a transit-amplifying (TA) domain of the root meristem. TA cells divide several times to provide cells for growth. SHORTROOT (SHR) and SCARECROW (SCR) are key regulators of the stem cell niche. Cytokinin controls TA cell activities in a dose-dependent manner. Although the

Plant ScienceAgricultural and Biological Sciences
6
논문|인용수 44·2021
Image-to-Image Retrieval by Learning Similarity between Scene Graphs
Sangwoong Yoon, Woo Young Kang, Sungwook Jeon, SeongEun Lee, Changjin Han, Jonghun Park, Eun‐Sol Kim
Proceedings of the AAAI Conference on Artificial IntelligenceOA

As a scene graph compactly summarizes the high-level content of an image in a structured and symbolic manner, the similarity between scene graphs of two images reflects the relevance of their contents. Based on this idea, we propose a novel approach for image-to-image retrieval using scene graph similarity measured by graph neural networks. In our approach, graph neural networks are trained to predict the proxy image relevance measure, computed from human-annotated captions using a pre-trained s

Computer Vision and Pattern RecognitionComputer Science
7
논문|인용수 36·2022
Hypergraph Transformer: Weakly-Supervised Multi-hop Reasoning for Knowledge-based Visual Question Answering
Yu‐Jung Heo, Eun‐Sol Kim, Woo Suk Choi, Byoung‐Tak Zhang
Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)OA

Knowledge-based visual question answering (QA) aims to answer a question which requires visually-grounded external knowledge beyond image content itself. Answering complex questions that require multi-hop reasoning under weak supervision is considered as a challenging problem since i) no supervision is given to the reasoning process and ii) highorder semantics of multi-hop knowledge facts need to be captured. In this paper, we introduce a concept of hypergraph to encode highlevel semantics of a

Computer Vision and Pattern RecognitionComputer Science
8
book chapter|인용수 16·2019
Temporal Attention Mechanism with Conditional Inference for Large-Scale Multi-label Video Classification
Eun-Sol Kim, Kyoung-Woon On, Jong-Seok Kim, Yu‐Jung Heo, Seong‐Ho Choi, Hyun-Dong Lee, Byoung-Tak Zhang
SJR Q2Lecture notes in computer science
Computer Vision and Pattern RecognitionComputer Science
9
논문|인용수 11·2023
Effects of stretching intervention on musculoskeletal pain in dental professionals
Eun‐Sol Kim, Eun-Deok Jo, Gyeong‐Soon Han
SJR Q1Journal of Occupational HealthOA

OBJECTIVE: This study aimed to quantitatively confirm the effects of dental specialists' work and stretching on musculoskeletal pain. METHODS: The pain pressure threshold was divided into five parts (neck, shoulder, trunk, lower back, and hand/arm) of the upper body and measured at 15 muscle trigger points. The pain pressure threshold before and after work was measured, and 30 min of stretching and rest were stipulated as an intervention. RESULTS: The pain pressure thresholds reduced significant

Medical Laboratory TechnologyHealth Professions
10
논문|인용수 8·2016
HAWAIIAN SKIRT regulates the quiescent center‐independent meristem activity in Arabidopsis roots
Eun‐Sol Kim, Goh Choe, José Sebastián, Kook Hui Ryu, Linyong Mao, Zhangjun Fei, Ji‐Young Lee
SJR Q1Physiologia Plantarum

Root apical meristem (RAM) drives post-embryonic root growth by constantly supplying cells through mitosis. It is composed of stem cells and their derivatives, the transit-amplifying (TA) cells. Stem cell organization and its maintenance in the RAM are well characterized, however, their relationships with TA cells remain unclear. SHORTROOT (SHR) is critical for root development. It patterns cell types and promotes the post-embryonic root growth. Defective root growth in the shr has been ascribed

Plant ScienceAgricultural and Biological Sciences
11
논문|인용수 4·2011
Mutual information-based evolution of hypernetworks for brain data analysis
Eun‐Sol Kim, Jung-Woo Ha, Wi Hoon Jung, Joon Hwan Jang, Jun Soo Kwon, Byoung‐Tak Zhang

Cortical analysis becomes increasingly important for brain research and clinical diagnosis. This problem involves a combinatorial search to find the essential modules among a large number of brain regions. Despite several statistical approaches, cortical analysis remains a formidable challenge due to high dimensionality and sparsity of data. Here we describe an evolutionary method for finding significant modules from cortical data. The method uses a hypernetwork which is encoded as a population

Artificial IntelligenceComputer Science
12
book chapter|인용수 1·2024
Clustering-based Image-Text Graph Matching for Domain Generalization
Nokyung Park, Daewon Chae, Jeongyong Shim, Sangpil Kim, Eun-Sol Kim, Jinkyu Kim
SJR Q2Lecture notes in computer science
Artificial IntelligenceComputer Science
13
논문|인용수 1·2019
Association between Oral Health Status and Dementia
Eun‐Sol Kim, Eun-Deok Jo, Gyeong‐Soon Han
SJR Q3Iranian Journal of Public HealthOA

This article is a Letter to the Editor and does not include an Abstract.

PeriodonticsDentistry
14
논문|인용수 1·2015
Analyzing Human Behavioral Data to Interact with Restaurant Server Agents
Eun‐Sol Kim, Kyoung-Woon On, Byoung‐Tak Zhang

In this paper, we consider a problem of analyzing human behavioral data to predict the human cognitive states and generate corresponding actions of sever-agent. Specifically, we aim at predicting human cognitive states during meal time and generating relevant dining services for the human. For this study, we collect behavioral data using 2 kinds of wearable devices, which are an eye tracker and a watch type EDA device, during meal time. We focus on the characteristics of the behavioral data, whi

Experimental and Cognitive PsychologyPsychology
15
논문|인용수 1·2025
Evaluation of Combined Odor Mitigating Agents for Ammonia and Hydrogen Sulfide Reduction from Swine Manure
Eun‐Sol Kim, Yun-Ju Jeon, Tae-Hoon Kim, Siyoung Seo, Yeo‐Myeong Yun
SJR Q4Journal of Korea Society of Waste Management
Process Chemistry and TechnologyChemical Engineering

대표 연구 분야

Computer Vision and Pattern RecognitionArtificial IntelligenceMolecular BiologyElectrical and Electronic EngineeringPlant ScienceAgronomy and Crop Science

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