Neural holography enabled multi-beam steering for multi-task classifier
神经全息术支持多任务分类器的多光束转向
ニューラルホログラフィーはマルチタスク分類器のマルチビームステアリングをサポートする
다중 작업 분류기를 위한 신경 홀로그래피 가능한 멀티 다다다다다중 다다중 작업 분류기를 위한 멀티 다다중
Dirección multihaz habilitada por holografía neuronal para clasificador multitarea
Direction multifaisceau avec holographie neuronale pour classificateur multitâche
Нейронная голография с помощью многолучевого управления для многозадачного классификатора
Lin Wu ¹, Mian Wu ¹, Zhen Li ¹, Ying Qiu ¹, Zichen Liu ², Yongquan Zeng ² ³, Guozhen Liang ³, Hanbing Li ¹, Guoxing Zheng ² ³, Zhixue He ², Xi Xiao ² ⁴, Qi Jie Wang ⁴, Jin Tao ¹ ², Shaohua Yu ²
¹ State Key Laboratory of Optical Communication Technologies and Networks, China Information Communication Technologies Group Corporation (CICT), Wuhan 430074, China
中国 武汉 中国信科集团光通信技术和网络全国重点实验室
² Pengcheng Laboratory, Shenzhen 518000, China
中国 深圳 鹏城实验室
³ Electronic Information School, Wuhan University, Wuhan 430072, China
中国 武汉 武汉大学电子信息学院
⁴ National Information Optoelectronics Innovation Center, China Information Communication Technologies Group Corporation (CICT), Wuhan 430074, China
中国 武汉 中国信息通信科技集团有限公司 国家信息光电子创新中心
⁵ School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore 639798, Singapore
Diffractive neural network is a versatile optical computing platform for accelerating deep learning inference. Whereas enabling the free-space optics for the multi-task processing capability requires complicated and costly system reconfigurations. Herein, we turn the neural network driven holography to a holographic classifier, where multiple image recognition tasks can be tackled simultaneously.
It results in an end-to-end optoelectronic neural network, which processes information from the target image (input layer), through the generated phase map (hidden layer), to the resulting optical pattern (output layer). The simple optical architecture and flexible neural holographic algorithm facilitate the accurate model-to-reality implementation.
The proposed system has potential applications for high-speed information processing, and intelligent control of beam splitting and steering.
