arXiv Open Access 2021

All-Optical Image Identification with Programmable Matrix Transformation

Shikang Li Baohua Ni Xue Feng Kaiyu Cui Fang Liu +2 lainnya

Lihat Sumber

Abstrak

An optical neural network is proposed and demonstrated with programmable matrix transformation and nonlinear activation function of photodetection (square-law detection). Based on discrete phase-coherent spatial modes, the dimensionality of programmable optical matrix operations is 30~37, which is implemented by spatial light modulators. With this architecture, all-optical classification tasks of handwritten digits, objects and depth images are performed on the same platform with high accuracy. Due to the parallel nature of matrix multiplication, the processing speed of our proposed architecture is potentially as high as7.4T~74T FLOPs per second (with 10~100GHz detector)

Topik & Kata Kunci

physics.optics eess.IV

Penulis (7)

Shikang Li

Baohua Ni

Xue Feng

Kaiyu Cui

Fang Liu

Wei Zhang

Yidong Huang

Format Sitasi

APA MLA BibTeX

Li, S., Ni, B., Feng, X., Cui, K., Liu, F., Zhang, W. et al. (2021). All-Optical Image Identification with Programmable Matrix Transformation. https://arxiv.org/abs/2104.02474

Akses Cepat

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Informasi Jurnal

Tahun Terbit: 2021
Bahasa: en
Sumber Database: arXiv
Akses: Open Access ✓