Meta-neural-network for real-time and passive deep-learning-based object recognition
oleh: Jingkai Weng, Yujiang Ding, Chengbo Hu, Xue-Feng Zhu, Bin Liang, Jing Yang, Jianchun Cheng
| Format: | Article |
|---|---|
| Diterbitkan: | Nature Portfolio 2020-12-01 |
Deskripsi
The authors present a passive meta-neural-network for real-time recognition of objects by analysis of acoustic scattering. It consists of unit cells termed meta-neurons, mimicking an analogous neural network for classical waves, and is shown to recognise handwritten digits and misaligned orbital-angular-momentum vortices.