Intelligent phase imaging guided by physics models
Implicit neural representation characterizes the mapping between the signal’s coordinate to its attributes, and has been widely used in the optimization of inverse problems by embedding the physics process into the loss function.However, the implicit neural representation is suffering the low conver...
Saved in:
Main Authors: | Zhen LIU, Hao ZHU, You ZHOU, Zhan MA, Xun CAO |
---|---|
Format: | Article |
Language: | zho |
Published: |
China InfoCom Media Group
2023-06-01
|
Series: | 物联网学报 |
Subjects: | |
Online Access: | http://www.wlwxb.com.cn/zh/article/doi/10.11959/j.issn.2096-3750.2023.00345/ |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Self-supervised speech representation learning based on positive sample comparison and masking reconstruction
by: Wenlin ZHANG, et al.
Published: (2022-07-01) -
Pseudolabel guided pixels contrast for domain adaptive semantic segmentation
by: Jianzi Xiang, et al.
Published: (2024-12-01) -
Near‐Isotropic, Extreme‐Stiffness, Continuous 3D Mechanical Metamaterial Sequences Using Implicit Neural Representation
by: Yunkai Zhao, et al.
Published: (2025-01-01) -
A cross‐project defect prediction method based on multi‐adaptation and nuclear norm
by: Qingan Huang, et al.
Published: (2022-04-01) -
PDE-Based Physics Guided Neural Network for SAR Image Segmentation
by: Rachana Rao, et al.
Published: (2025-01-01)