As AI and smart tech evolve, machine vision faces challenges due to high power and computational needs for visual data processing, limiting its deployment on edge devices. Inspired by the human visual system, researchers have explored neuromorphic computing to enhance efficiency and reduce power consumption. A team from Tokyo University of Science has developed a self-powered artificial synapse able to distinguish colors with high precision using two integrated dye-sensitized solar cells, overcoming the barriers of color recognition and external power reliance, marking a significant step forward in machine vision technology.
The research led by Associate Professor Takashi Ikuno presents a self-powered artificial synapse that mimics human visual processing, achieving color recognition with impressive precision.
By integrating two distinct dye-sensitized solar cells, the new device efficiently distinguishes colors without requiring external power, presenting a significant advancement in machine vision.
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