Learning super-resolution and pyramidal convolution residual network for vehicle re-identification
Abstract Vehicle re-identification (Vehicle Re-ID) aims at retrieving and tracking the specified target vehicle with multiple other cameras, which can provide help in checking violations and catching fugitives, but there are still the following problems that need to be solved urgently. First, the ex...
Saved in:
| Main Authors: | Mengxue Liu, Weidong Min, Qing Han, Hongyue Xiang, Meng Zhu |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2024-11-01
|
| Series: | Scientific Reports |
| Online Access: | https://doi.org/10.1038/s41598-024-77973-8 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Residual trio feature network for efficient super-resolution
by: Junfeng Chen, et al.
Published: (2024-11-01) -
Channel Graph Convolutional Networks for Animation Image Super-Resolution
by: Fuchun Wang, et al.
Published: (2024-01-01) -
Lightweight Reference-Based Video Super-Resolution Using Deformable Convolution
by: Tomo Miyazaki, et al.
Published: (2024-11-01) -
Image Super-Resolution Using Lightweight Multiscale Residual Dense Network
by: Shilin Li, et al.
Published: (2020-01-01) -
PCCN: Polarimetric Contexture Convolutional Network for PolSAR Image Super-Resolution
by: Lin-Yu Dai, et al.
Published: (2025-01-01)