[1] Y. LeCun, Y. Bengio, G. Hinton. Deep learning. Nature, 521, 436(2015).

[2] I. Adjabi et al. Past present and future of face recognition: a review. Electronics, 9, 1188(2020).

[3] Y. Taigman et al. DeepFace: Closing the Gap to Human-Level Performance in Face Verification, 1701(2014).

[4] Y. Sun et al. DeepID3: face recognition with very deep neural networks(2015).

[5] A. K. Jain, A. Ross, S. Prabhakar. An introduction to biometric recognition. IEEE Trans. Circuits Syst. Video Technol., 14, 4(2004).

[6] M. A. P. Chamikara et al. Privacy preserving face recognition utilizing differential privacy. Computers & Security, 97, 101951(2020).

[7] K. Bonawitz et al. Practical secure aggregation for privacy-preserving machine learning, 1175(2017).

[8] C. Gentry, S. Halevi. Implementing gentry’s fully-homomorphic encryption scheme, 129(2011).

[9] F. Boemer et al. MP2ML: a mixed-protocol machine learning framework for private inference, 1(2020).

[10] R. Gilad-Bachrach et al. Cryptonets: applying neural networks to encrypted data with high throughput and accuracy, 201(2016).

[11] Y. Mi et al. Privacy-preserving face recognition using trainable feature subtraction, 297(2024).

[12] C. Henry, M. S. Asif, Z. Li. Privacy preserving face recognition with lensless camera, 1(2023).

[13] J. Tan et al. Face detection and verification using lensless cameras. IEEE Trans. Comput. Imag., 5, 180(2019).

[14] M.-H. Wu, Y.-T. C. Lee, C.-H. Tien. Lensless facial recognition with encrypted optics and a neural network computation. Appl. Opt., 61, 7595(2022).

[15] V. Boominathan et al. Recent advances in lensless imaging. Optica, 9, 1(2022).

[16] E. E. Fenimore. Coded aperture imaging: predicted performance of uniform redundant arrays. Appl. Opt., 17, 3562(1978).

[17] M. P. Edgar, G. M. Gibson, M. J. Padgett. Principles and prospects for single-pixel imaging. Nat. Photonics, 13, 13(2019).

[18] L. Pan et al. Single photon single pixel imaging into thick scattering medium. Opt. Express, 31, 13943(2023).

[19] Z. Zhang, X. Ma, J. Zhong. Single-pixel imaging by means of Fourier spectrum acquisition. Nat. Commun., 6, 6225(2015).

[20] X. Zhu et al. Adaptive real-time single-pixel imaging. Opt. Lett., 49, 1065(2024).

[21] V. Boominathan et al. Recent advances in lensless imaging. Optica, 9, 1(2022).

[22] Y. Ishii, S. Sato, T. Yamashita. Privacy-aware face recognition with lensless multi-pinhole camera, 476(2020).

[23] M. S. Asif et al. Flatcam: thin, lensless cameras using coded aperture and computation. IEEE Trans. Comput. Imaging, 3, 384(2017).

[24] W. Shi et al. LOEN: lensless opto-electronic neural network empowered machine vision. Light: Sci. Appl., 11, 121(2022).

[25] Z. Huang et al. Pre-sensor computing with compact multilayer optical neural network. Sci. Adv., 10, eado8516(2024).

[26] Z. Huang et al. Multi-layer optical convolutional neural network with nonlinear activation(2024).

[27] N. T. Gordon, C. L. Jones, D. J. Purdy. Application of microlenses to infrared detector arrays. Infrared Phys., 31, 599(1991).

[28] S. Ogata, J. Ishida, T. Sasano. Optical sensor array in an artificial compound eye. Opt. Eng., 33, 3649(1994).

[29] J. Tanida et al. Color imaging with an integrated compound imaging system. Opt. Express, 11, 2109(2003).

[30] R. Ng et al. Light field photography with a hand-held plenoptic camera(2005).

[31] N. Ji. Adaptive optical fluorescence microscopy. Nat. Methods, 14, 374(2017).

[32] F. Yu, V. Koltun. Multi-scale context aggregation by dilated convolutions(2015).

[33] L.-C. Chen et al. Semantic image segmentation with deep convolutional nets and fully connected CRFs(2015).

[34] L.-C. Chen et al. DeepLab: Semantic image segmentation with deep convolutional nets, atrous convolution, and fully connected CRFs. IEEE Trans. Pattern Anal. Mach. Intell., 40, 834(2018).

[35] L.-C. Chen et al. Rethinking atrous convolution for semantic image segmentation(2017).

[36] L.-C. Chen et al. Encoder-decoder with atrous separable convolution for semantic image segmentation, 801(2018).

[37] F. Schroff, D. Kalenichenko, J. Philbin. FaceNet: a unified embedding for face recognition and clustering, 815(2015).

[38] C. Szegedy et al. Inception-v4, inception-ResNet and the impact of residual connections on learning(2017).

[39] K. Zhang et al. Joint face detection and alignment using multitask cascaded convolutional networks. IEEE Signal Process. Lett., 23, 1499(2016).

[40] D. Yi et al. Learning face representation from scratch(2014).

[41] G. B. Huang et al. Labeled faces in the wild: a database for studying face recognition in unconstrained environments(2007).

[42] G. B. Huang, E. Learned-Miller. Labeled Faces in the Wild: Updates and New Reporting Procedures(2014).

[43] Z. Huang et al. Privacy-encrypted lensless camera for face recognition(2023).

[44] O. Ronneberger, P. Fischer, T. Brox. U-net: convolutional networks for biomedical image segmentation, 234(2015).