Our team endeavors to uncover the complex computational dynamics underlying visual cognition in both humans and machines. This pursuit involves delving into the computational principles and neural mechanisms within the brain that enable stable visual representations of our environment. In parallel, we leverage understanding from human cognition to advance machine models. As machines become integral to our daily lives and play a crucial role in society, the demand for trustworthy, human-compatible machine models cannot be overstated. We envision a future where machines and humans work together seamlessly, with technology augmenting human tasks and activities. If our vision aligns with your academic or professional pursuits, feel free to contact the PI to discuss collaboration opportunities or to learn more about becoming a member of our team.
고려대학교 인간-기계 비전 연구실에서는 인간과 기계의 시각 시스템을 비교 분석하여, 두 시스템 간의 작동 방식과 인지 과정의 차이를 심층적으로 연구하고 있습니다. 구체적으로, 심리학과 뇌공학의 융합적 접근 방식을 통해 시각 인지와 관련된 행동 및 신경학적 원리를 탐구하며, 이를 바탕으로 인간 중심의 신뢰할 수 있는 인공지능 모델 개발을 목표로 하고 있습니다. 연구실과의 협력 기회나 팀 일원으로의 참여에 관심이 있다면, 연구 책임자에게 이메일(✉️)로 문의해 주시기 바랍니다.
Exploring how psychological and neuroscientific knowledge can advance machine vision models presents a promising research direction. Our group is interested in investigating machine models that not only mirror biological systems but also provide tangible advantages for applications in the real world.
Brain decoding techniques offer a novel approach to accessing and interpreting the mental processes of perception and cognition. These methods allow researchers to decode the complex mental processes without the need for individuals to verbally articulate their thoughts, thus often referred to as “neural mind reading.”
A key characteristic of human visual perception is its robustness. Despite variations in the external environment, our internal visual representations remain stable and consistent. What mechanisms enable this robustness, and how can they be understood? Answering this question is also crucial for developing reliable machine vision systems.
Exploring how simple sensory experiences turn into complex thinking is a fascinating topic for vision science. Researchers investigate how people make sense of object relationships, interpret and express emotions through facial expressions, navigate busy streets and sign reading, or appreciate the aesthetic value in art and nature.