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REFERENCES

1 
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2 
G. Gallego, T. Delbrück, G. Orchard, C. Bartolozzi, B. Taba, A. Censi, and D. Scaramuzza, ``Event-based vision: A survey,'' IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 44, no. 1, pp. 154-180, 2020.DOI
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14 
J. Greffier, D. Dabli, J. Frandon, A. Hamard, A. Belaouni, P. Akessoul, and J.-P. Beregi, ``Comparison of two versions of a deep learning image reconstruction algorithm on CT image quality and dose reduction: A phantom study,'' Medical Physics, vol. 48, no. 10, pp. 5743-5755, 2021.DOI
15 
B. Fang and N. Xiao, ``Self-supervised reflectance-guided 3d shape reconstruction from single-view images,'' Applied Intelligence, vol. 53, no. 6, pp. 6966-6977, 2023.DOI
16 
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18 
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19 
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20 
Z. Zhang, Y. Li, C. Huang, Q. Guo, C. Yuen, and Y-L. Guan, ``DNN-aided block sparse Bayesian learning afor user activity detection and channel estimation in grant-free non-orthogonal random access,'' IEEE Transactions on Vehicular Technology, vol. 68, no. 12, pp. 12000-12012, 2019.DOI
21 
S. Nimrah and S. Saifullah, ``Context-free word importance scores for attacking nmural networks,'' Journal of Computational and Cognitive Engineering, vol. 1, no. 4, pp. 187-192, 2022.DOI