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Here, we demonstrate a ferroelectric\u2010configured weight\u2010reconfigurable photovoltaic device array for in\u2010sensor dynamic computing, enabling robust recognition of dim objects. A series of 2D perovskite ferroelectric nanoplates with controllable size, high crystallinity, and excellent yield are directly synthesized. Reconfigurable and nonvolatile photovoltaics in a graphene\/ferroelectric\/graphene heterostructure are modulated through switchable ferroelectric polarization. Leveraging the ferroelectric\u2010configured photoresponsivity, a convolution kernel optoelectronic sensor array with dynamic correlation of adjacent units is designed for in\u2010sensor dynamic computing. Compared with traditional static optoelectronic convolution processing, our approach selectively amplifies subtle differences of local image pixels, enabling effective edge feature extraction even in low\u2010contrast scenes. Integrated with a convolutional neural network, the system significantly enhances the robustness and accuracy of dim object detection, offering a promising platform for advanced machine vision applications.<\/jats:p>","DOI":"10.1002\/adma.202520823","type":"journal-article","created":{"date-parts":[[2025,12,26]],"date-time":"2025-12-26T09:22:22Z","timestamp":1766740942000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":13,"title":["Ferroelectric\u2010Configured In\u2010Sensor Dynamic Computing with 2D Perovskites for Dim Object Recognition"],"prefix":"10.1002","volume":"38","author":[{"given":"Jie","family":"Liu","sequence":"first","affiliation":[{"name":"College of Smart Materials and Future Energy and State Key Laboratory of Molecular Engineering of Polymers Fudan University  Shanghai P. R. 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