STeInFormer: Spatial–Temporal Interaction Transformer Architecture for Remote Sensing Change Detection
Convolutional neural networks and attention mechanisms have greatly benefited remote sensing change detection (RSCD) because of their outstanding discriminative ability. Existent RSCD methods often follow a paradigm of using a noninteractive Siamese neural network for multitemporal feature extractio...
Saved in:
Main Authors: | Xiaowen Ma, Zhenkai Wu, Mengting Ma, Mengjiao Zhao, Fan Yang, Zhenhong Du, Wei Zhang |
---|---|
Format: | Article |
Language: | English |
Published: |
IEEE
2025-01-01
|
Series: | IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing |
Subjects: | |
Online Access: | https://ieeexplore.ieee.org/document/10815617/ |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Impermanence and Architecture. Ideas, Concepts, Words
by: Massimo Perriccioli
Published: (2018-12-01) -
The effect of auditory rhythm on the temporal allocation of visual attention in aging
by: Zhihan Xu, et al.
Published: (2025-02-01) -
Editorial: From sub-lexical to discourse-level effects in bi- and multilingual language processing
by: Katarzyna Jankowiak, et al.
Published: (2025-02-01) -
Habitat and Spatio-Temporal Interaction Between Green Peafowl with Cattle and Megaherbivores in Baluran National Park
by: Satyawan Pudyatmoko
Published: (2019-05-01) -
Representing temporal concepts using redundant gestures in L2 ongoing interactions
by: Hiroki Hanamoto
Published: (2023-12-01)