Bio‐inspired artificial retina with receptive fields for in‐sensor multiply‐and‐accumulate operations
2026 · InfoMat
저자
Jisang Ha, Jinsung Mok, Jong Ik Kwon, Eungseon Yeon, Jeong Jin Kim, Gil Ju Lee, Do Kyung Hwang, Changsoon Choi, 김대형 (Dae‐Hyeong Kim)
연구주제
Advanced Memory and Neural Computing
NTIS 과학기술표준분류
가장 가까운 분류(전기/전자 > 반도체 소자·회로)가 화학·화공 범위 밖이다. 배정 근거: 지원 과제·키워드 근거가 없어 AI가 논문 제목·초록을 읽고 고른 분류.
AI 연구 키워드·방법
artificial retina 곡면 이미지 센서 어레이 인센서 컴퓨팅 receptive field
키워드 (OpenAlex)
receptive fields in-sensor computing multiply-accumulate operations single-lens imaging edge detection semantic segmentation energy efficiency mobile robot vision
초록
Abstract Bio‐inspired vision systems based on curved image sensors offer a compelling imaging hardware for mobile robots by geometrically matching the image plane to the Petzval surface of single‐lens optics. However, to fully exploit the advantages of biological vision systems, it is essential not only to emulate optical structures but also to integrate sensory‐level processing functions into vision hardware. Here, we propose a robotic vision system that leverages the structural advantages of the human eye (compact single‐lens imaging architecture) and the functional advantages of the biological receptive fields (sensory‐level information pre‐processing for efficient signal transmission and downstream computation). It is enabled by a bio‐inspired artificial retina composed of curved perovskite photoconductors that form artificial receptive fields (ARFs). Each ARF performs multiply‐and‐a…
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교수 1
연구주제 1
Advanced Memory and Neural Computing