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- W4368367040 abstract "In this study, we explore the potential of using a straightforward neural network inspired by the retina model to efficiently restore low-light images. The retina model imitates the neurophysiological principles and dynamics of various optical neurons. Our proposed neural network model reduces the computational overhead compared to traditional signal-processing models while achieving results similar to complex deep learning models from a subjective perceptual perspective. By directly simulating retinal neuron functionalities with neural networks, we not only avoid manual parameter optimization but also lay the groundwork for constructing artificial versions of specific neurobiological organizations." @default.
- W4368367040 created "2023-05-05" @default.
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- W4368367040 date "2023-05-02" @default.
- W4368367040 modified "2023-09-25" @default.
- W4368367040 title "Bio-Inspired Simple Neural Network for Low-Light Image Restoration: A Minimalist Approach" @default.
- W4368367040 doi "https://doi.org/10.20944/preprints202305.0067.v1" @default.
- W4368367040 hasPublicationYear "2023" @default.
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