AI & Media Lab
Research Topics
Multimodal Learning
combines text, images, audio, and video to accommodate various learning preferences, enhancing overall comprehension
Domain Transfer
adapts an AI model from one domain to another, enhancing its performance on related but different data distributions
Scene Understanding
aims to interpret a visual scene, recognizing objects, their relationships, and the context to interact intelligently with their environment
Parameter-Efficient Fine-Tuning
optimizes an AI model using a small subset of its parameters while minimizing computational costs
and memory usage
3D Vision
refers to the process of extracting spatial information from visual input, enabling machines to perceive and navigate the 3D world
Robot Vision
enables robots to understand visual data from their surroundings using cameras and multiple sensors, enhancing their autonomy and versatility
Latest News
[Member] 2024.10 장유지아, 류휘링, 곽도원 학생의 "클래스 속성 및 클래스-무관 특징 결합을 통한 테스트 타임 프롬프트 튜닝" 논문이 제 34회 인공지능 신호처리 학술대회 장려논문으로 선정되었습니다. 축하합니다.
[Project] 2024.09 홍성은 교수님이 참여하시는 "신뢰가능한 인공지능 연구단"이 정보통신기획평가원(IITP) 디지털분야해외석학유치지원사업에 선정되었습니다.
[Member] 2024.03 최소윤, 류휘링 학생의 박사과정 합류와 이승환, 정인영, 조유림, 조은남 학생의 석사과정 합류를 축하합니다.
AI & Media Lab (AIM Lab)
Office : 90313, International Hall, Sungkyunkwan University,
25-2 Sungkyunkwan-ro, Jongno-gu, Seoul 03063, Korea
Email : csehong@skku.edu Web : aim.skku.edu Tel : 02-740-1809