@misc{Zhang_Ye_A_2024,
 author={Zhang, Ye and Zhang, Saining and Zhang, Danni and Wang, Ruiting and Su, Yanmei and Yi, Junkai and Wang, Pengfei and Luo, Guangzhen and Zhou, Xuliang and Pan, Jiaoqing},
 contributor={Urbańczyk, Wacław. Redakcja},
 identifier={DOI: 10.37190/oa240108},
 year={2024},
 rights={Wszystkie prawa zastrzeżone (Copyright)},
 publisher={Oficyna Wydawnicza Politechniki Wrocławskiej},
 description={Optica Applicata, Vol. 54, 2024, nr 1, s. 97-104},
 description={Optica Applicata is an international journal, published in a non-periodical form in the years 1971-1973 and quarterly since 1973. From the beginning of the year 2008, Optica Applicata is an Open Access journal available online via the Internet, with free access to the full text of articles serving the best interests of the scientific community. The journal is abstracted and indexed in: Chemical Abstracts, Compendex, Current Contents, Inspec, Referativnyj Zhurnal, SCI Expanded, Scopus, Ulrich’s Periodicals Directory},
 description={http://opticaapplicata.pwr.edu.pl/},
 language={eng},
 abstract={In recent years, with the expansion of information, artificial intelligence technology has been developed and used in various fields. Among them, optical neural network provides a new type of special neural network accelerator chip solution, which has the advantages of high speed, high bandwidth, and low power consumption. In this paper, we construct an optical neural network based on Mach–Zehnder interferometer. The experimental results on the image classification of MNIST handwritten digitals show that the optical neural network has high accuracy, fast convergence and good scalability.},
 type={artykuł},
 title={A MZI-based optical neural network for image classification},
 keywords={optyka, optical neural network, image classification, Mach–Zehnder interferometer},
}