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Article

Diffractive Neural Network Enabled Spectral Object Detection

1
Shanghai Institute of Technical Physics, Chinese Academy of Sciences, Shanghai 200083, China
2
University of Chinese Academy of Sciences, Beijing 100049, China
3
National Key Laboratory of Infrared Detection Technologies, Shanghai Institute of Technical Physics, Chinese Academy of Sciences, 500 Yutian Road, Shanghai 200083, China
*
Author to whom correspondence should be addressed.
Remote Sens. 2025, 17(19), 3381; https://doi.org/10.3390/rs17193381
Submission received: 15 August 2025 / Revised: 3 October 2025 / Accepted: 3 October 2025 / Published: 8 October 2025

Abstract

This article introduces a diffractive neural network-enabled spectral object detection approach (DNN-SOD) to efficiently process massive sky-based multidimensional light field data. DNN-SOD combines the novel exploitation of target spectral features with the intrinsic parallelism of optical computing to process multidimensional information efficiently. DNN-SOD detects targets by segmenting the spectral data cube and processing it with the DNN. The DNN maps spectral intensity to the designated area of the detector, then reconstructs spectral curves, and differentiates targets by comparing them with reference spectral signatures. Classification results from individual sub-spectral data cubes are compiled in sequence, enabling accurate target detection. Simulation results indicate that the architecture achieved an accuracy of 91.56% on the MNIST multi-spectral dataset and 84.27% on the infrared target multi-spectral dataset, validating its feasibility for target detection. This architecture represents an innovative outcome at the intersection of remote sensing and optical computing, significantly advancing the dissemination and practical adoption of optical computing in the field.
Keywords: diffractive neural network; multi-spectral process; optical computing; sky-based remote sensing diffractive neural network; multi-spectral process; optical computing; sky-based remote sensing

Share and Cite

MDPI and ACS Style

Ma, Y.; Chen, R.; Qian, S.; Sun, S. Diffractive Neural Network Enabled Spectral Object Detection. Remote Sens. 2025, 17, 3381. https://doi.org/10.3390/rs17193381

AMA Style

Ma Y, Chen R, Qian S, Sun S. Diffractive Neural Network Enabled Spectral Object Detection. Remote Sensing. 2025; 17(19):3381. https://doi.org/10.3390/rs17193381

Chicago/Turabian Style

Ma, Yijun, Rui Chen, Shuaicun Qian, and Shengli Sun. 2025. "Diffractive Neural Network Enabled Spectral Object Detection" Remote Sensing 17, no. 19: 3381. https://doi.org/10.3390/rs17193381

APA Style

Ma, Y., Chen, R., Qian, S., & Sun, S. (2025). Diffractive Neural Network Enabled Spectral Object Detection. Remote Sensing, 17(19), 3381. https://doi.org/10.3390/rs17193381

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