Results 21 to 30 of about 3,331,007 (297)

Acknowledgement to Reviewers of Remote Sensing in 2017

Remote Sensing, 2018
Peer review is an essential part in the publication process, ensuring that Remote Sensing maintains high quality standards for its published papers.[...]
Remote Sensing Editorial Office
doaj   +1 more source

Poly Kernel Inception Network for Remote Sensing Detection [PDF]

Computer Vision and Pattern Recognition
Object detection in remote sensing images (RSIs) often suffers from several increasing challenges, including the large variation in object scales and the diverse-ranging context.
Xinhao Cai, Qiuxia Lai, Yuwei Wang, Wenguan Wang, Zeren Sun, Yazhou Yao   +5 more
semanticscholar   +1 more source

ChangeMamba: Remote Sensing Change Detection With Spatiotemporal State Space Model [PDF]

IEEE Transactions on Geoscience and Remote Sensing
Convolutional neural networks (CNNs) and Transformers have made impressive progress in the field of remote sensing change detection (CD). However, both architectures have inherent shortcomings: CNN is constrained by a limited receptive field that may ...
Hongruixuan Chen, Jian Song, Chengxi Han, Junshi Xia, Naoto Yokoya   +4 more
semanticscholar   +1 more source

Acknowledgement to Reviewers of Remote Sensing in 2014

Remote Sensing, 2015
The editors of the Remote Sensing office would like to express their sincere gratitude to the following reviewers for assessing manuscripts in 2014:[...]
Remote Sensing Editorial Office
doaj   +1 more source

Retraction: He, S., et al. The Exploration of Urban Material Anabolism Based on RS and GIS Methods: Case Study in Jinchang, China. Remote Sens. 2020, 12, 370

Remote Sensing, 2020
The Remote Sensing Editorial Office has been made aware that the published paper [...]
Remote Sensing Editorial Office
doaj   +1 more source

RSMamba: Remote Sensing Image Classification With State Space Model [PDF]

IEEE Geoscience and Remote Sensing Letters
Remote sensing image classification forms the foundation of various understanding tasks, serving a crucial function in remote sensing image interpretation.
Keyan Chen, Bo-Ying Chen, Chenyang Liu, Wenyuan Li, Zhengxia Zou, Z. Shi   +5 more
semanticscholar   +1 more source

RS-Mamba for Large Remote Sensing Image Dense Prediction [PDF]

IEEE Transactions on Geoscience and Remote Sensing
Context modeling is critical for remote sensing image dense prediction tasks. Nowadays, the growing size of very-high-resolution (VHR) remote sensing images poses challenges in effectively modeling context.
Sijie Zhao, Hao Chen, Xue-liang Zhang, P. Xiao, Lei Bai, Wanli Ouyang   +5 more
semanticscholar   +1 more source

Erratum: Raney, R.K. Hybrid Dual-Polarization Synthetic Aperture Radar. Remote Sens. 2019, 11, 1521

Remote Sensing, 2019
Due to a technical problem, Figure 1 in [...]
Remote Sensing Editorial Office
doaj   +1 more source

Acknowledgement to Reviewers of Remote Sensing in 2019

Remote Sensing, 2020
The editorial team greatly appreciates the reviewers who have dedicated their considerable time and expertise to the journal’s rigorous editorial process over the past 12 months, regardless of whether the papers are finally published or not.[...]
Remote Sensing Editorial Office
doaj   +1 more source

A Review on Unmanned Aerial Vehicle Remote Sensing: Platforms, Sensors, Data Processing Methods, and Applications

Drones, 2023
In recent years, UAV remote sensing has gradually attracted the attention of scientific researchers and industry, due to its broad application prospects. It has been widely used in agriculture, forestry, mining, and other industries. UAVs can be flexibly
Zhengxin Zhang, Lixue Zhu
semanticscholar   +1 more source