To emulate the functionality of the human retina and achieve a neuromorphic visual system, the development of a photonic synapse capable of multispectral color discrimination is of paramount importance. However, attaining robust color discrimination across a wide intensity range, even irrespective of medium limitations in the channel layer, poses a significant challenge. Here, we propose an approach that can bestow the color-discriminating synaptic functionality upon a three-terminal transistor flash memory even with enhanced discriminating capabilities. By incorporating the strong induced dipole moment effect at the excitation, modulated by the wavelength of the incident light, into the floating gate, we achieve outstanding RGB color-discriminating synaptic functionality within a remarkable intensity range spanning from 0.05 to 40 mW cm⁻². This approach is not restricted to a specific medium in the channel layer, thereby enhancing its applicability. The effectiveness of this color-discriminating synaptic functionality is demonstrated through visual pre-processing of a photonic synapse array, involving the differentiation of RGB channels and the enhancement of image contrast with noise reduction. Consequently, a convolutional neural network can achieve an impressive inference accuracy of over 94% for Canadian-Institute-For-Advanced-Research-10 colorful image recognition task after the pre-processing. Our proposed approach offers a promising solution for achieving robust and versatile RGB color discrimination in photonic synapses, enabling significant advancements in artificial visual systems.

为了模拟人类视网膜的功能并实现神经形态视觉系统，开发能够进行多光谱颜色辨别的光子突触至关重要。然而，即使在通道层的介质限制下，在较宽的强度范围内实现强大的颜色辨别也是一项重大挑战。在这里，我们提出了一种方法，即使具有增强的区分能力，也可以将颜色区分突触功能赋予三端晶体管闪存。通过将激发时的强感应偶极矩效应（由入射光的波长调制）整合到浮栅中，我们在 0.05 至 40 mW ^cm-2 的显着强度范围内实现了出色的 RGB 颜色区分突触功能。这种方法不限于通道层中的特定媒体，从而增强了其适用性。这种颜色区分突触功能的有效性通过光子突触阵列的视觉预处理得到证明，涉及 RGB 通道的区分以及通过降噪增强图像对比度。因此，卷积神经网络在预处理后可以实现超过 94% 的 Canadian-Institute-For-Advanced-Research-10 彩色图像识别任务的令人印象深刻的推理准确率。我们提出的方法为在光子突触中实现稳健和多功能的 RGB 颜色区分提供了一种有前途的解决方案，从而在人工视觉系统中取得了重大进步。