Ultrafast machine vision with 2D material neural network image sensors

By L. Mennel, J. Symonowicz, Stefan Wachter, Dmitry K. Polyushkin, A. Molina‐Mendoza, Thomas Mueller. Nature, 2020

971 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Electrical and Electronic Engineering

View Paper: https://www.semanticscholar.org/paper/48aa48ad0ec699ed19fb7c0ce813ac2e80eb0eb9

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Peter Leonard McMahon

In Electrical and Electronic Engineering

1. Peter Leonard McMahon
2. Logan G. Wright

Citations in the corpus

• Deep physical neural networks trained with backpropagation (2021, background): “Ultimately, PNNs provide routes to improving the energy efficiency and speed of machine learning by many orders of magnitude, and pathways to automatically designing complex functional devices, such as functional nanoparticles 28 , robots 25,26 and smart sensors 30–32 .”