Shuo Chen and colleagues present a cost-effective neural network-based method to deal with tip-sample convolution artifacts in atomic force microscopy. Their method merges multiview atomic force microscopy images into precise 3D models of complex micro- and nanostructures.
- Shuo Chen
- Mao Peng
- Guofeng Zhang