On-Chip Optical Convolutional Neural Networks 来自 Semantic Scholar 喜欢 1 阅读量: 890 作者:H Bagherian,S Skirlo,Y Shen,H Meng,M Soljacic 摘要: Convolutional Neural Networks (CNNs) are a class of Artificial Neural Networks(ANNs) that employ the method of convolving input images with filter-...
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The on-chip learning of the convolutional neural network module implements a synaptic function by using a characteristic which the conductance of a memristor changes according to an applied pulse, and the convolutional kernel value or synaptic weight value is stored in a memristor unit; the input ...
Convolutional neural networks are an important category of deep learning, currently facing the limitations of electrical frequency and memory access time in massive data processing. Optical computing has been demonstrated to enable significant improvements in terms of processing speeds and energy efficiency....
Fig. 1: Schematic and logic diagram of on-chip diffractive optical neural network (DONN). aSchematic of an on-chip DONN, each diffractive unit on a given layer acts as a secondary wave source, the amplitude and phase of which are determined by the product of the input wave and the compl...
The apparatus includes an analog integrated circuit chip having a Convolutional Neural Network (CNN). The CNN includes a two-dimensional (2D) array of analog elements arranged in columns and rows and being configured to simultaneously provide a plurality of outputs by duplicating a same connection ...
This paper presents a configurable convolutional neural network accelerator (CNNA) for a system-on-chip (SoC). The goal was to accelerate inference in different deep learning networks on an embedded SoC platform. The presented CNNA has a scalable architecture that uses high-level synthesis (HLS) ...
Keywords: geometric deep learning; manifold deep learning; cnn; graph convolutional neural networks; high-dimensional informationCite as: Cao W M, Zheng C T, Yan Z Y, et al. Geometric deep learning: progress, applications and challenges. Sci China Inf Sci, 2022, 65(2): 126101, doi: ...
Spectral convolutional neural network chip for in-sensor edge computing of incoherent natural light Kaiyu Cui Shijie Rao Shengjin Wang Nature Communications (2025) Quantum-limited stochastic optical neural networks operating at a few quanta per activation Shi-Yuan Ma Tianyu Wang Peter L. McMahon ...
Photonic neural network processors have great potential for accelerating image processing14,16,22,23,24,25,26,27. Some of these processors enable direct image acquisition without the use of image sensors and subsequent optical processing14,22,23. In particular, on-chip photonic neural networks offer...