计算机视觉
人工智能
图像传感器
过程(计算)
计算机科学
曲率
传感器阵列
跟踪(教育)
迭代重建
目标检测
对象(语法)
材料科学
图像(数学)
光学
三维重建
霍夫变换
图像处理
机器视觉
曲面(拓扑)
基质(水族馆)
正多边形
视觉对象识别的认知神经科学
曲面重建
数码产品
作者
Lihao Zhou,Zhongyi Duan,La Li,Zhongming Wei,Guozhen Shen
出处
期刊:ACS Nano
[American Chemical Society]
日期:2026-02-27
卷期号:20 (10): 8879-8890
标识
DOI:10.1021/acsnano.6c00364
摘要
Curved image sensors hold great appeal in intelligent artificial vision systems, yet current sensor curving techniques still suffer from certain limitations. Taking inspiration from the cuttability and wrap-like transferability of paper-based electronics in three-dimensional curvy architecture and matched hydrophilic functional materials, we propose an image sensor with variable curvature through a vacuum filtration and folding-pasting process assisted by a thermal release tape mask. This method enables the uniform, patterned, hierarchical, and damage-free integration of Mo2TiC2Tx and silver nanowires onto a paper-based substrate. Both convex and concave image sensors are designed and fabricated: the convex type demonstrates wide-field infrared light source tracking when equipped on a robotic dog, while a concave one enables low-distortion imaging with a single lens. Furthermore, by arranging an array of concave curved image sensors around an object and capturing images from different angles, spatial modeling of the object can be realized even in a dark-field environment, showing great potential in bionic compound eyes and artificial vision systems.
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