All-optical machine learning using diffractive deep neural networks

Abstract

All-optical deep learning Deep learning uses multilayered artificial neural networks to learn digitally from large datasets. It then performs advanced identification and classification tasks. To date, these multilayered neural networks have been implemented on a computer. Lin et al. demonstrate all-optical machine learning that uses passive optical components that can be patterned and fabricated with 3D-printing. Their hardware approach comprises stacked layers of diffractive optical elements analogous to an artificial neural network that can be trained to execute complex functions at the speed of light. Science , this issue p. 1004

Keywords

Computer scienceDeep learningArtificial intelligenceArtificial neural networkFeature (linguistics)LithographyDeep neural networksPattern recognition (psychology)Computer architectureComputer visionMaterials scienceOptoelectronics

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Publication Info

Year: 2018
Type: article
Volume: 361
Issue: 6406
Pages: 1004-1008
Citations: 2123
Access: Closed

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APA Style

                            
                                
                                    Xing Lin, 
                                
                                    Yair Rivenson, 
                                
                                    Nezih Tolga Yardimci
                                
                                et al.
                            
                            (2018). 
                            All-optical machine learning using diffractive deep neural networks. 
                            Science
                            , 361
                            (6406)
                            , 1004-1008.
                            https://doi.org/10.1126/science.aat8084
                        

Identifiers

DOI: 10.1126/science.aat8084