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A Multi-Feature Fusion and Attention Network for Multi-Scale Object Detection in Remote Sensing Images
2023
Remote Sensing
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Accurate multi-scale object detection in remote sensing images poses a challenge due to the complexity of transferring deep features to shallow features among multi-scale objects. ...
Therefore, this study developed a multi-feature fusion and attention network (MFANet) based on YOLOX. ...
Acknowledgments: We thank the anonymous reviewers for their comments and suggestions that improved this paper.
Conflicts of Interest: The authors declare no conflict of interest. ...
doi:10.3390/rs15082096
fatcat:a34rp4imt5gulm5j3yjlon4orq
Object Detection in Remote Sensing Images Based on Adaptive Multi-Scale Feature Fusion Method
2024
Remote Sensing
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Multi-scale object detection is critical for analyzing remote sensing images. ...
in remote sensing images. ...
Consequently, multi-scale object detection has become a key research focus in remote sensing image analysis. ...
doi:10.3390/rs16050907
fatcat:n4nnpg3qrbgipgrocbkgyll4jy
Attention-Based Multi-Level Feature Fusion for Object Detection in Remote Sensing Images
2022
Remote Sensing
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We study the problem of object detection in remote sensing images. As a simple but effective feature extractor, Feature Pyramid Network (FPN) has been widely used in several generic vision tasks. ...
However, it still faces some challenges when used for remote sensing object detection, as the objects in remote sensing images usually exhibit variable shapes, orientations, and sizes. ...
optimal feature maps for detecting multi-scale remote sensing objects well. ...
doi:10.3390/rs14153735
fatcat:h54whft4ozdfjmxhlkchho3hh4
MS-IAF: Multi-Scale Information Augmentation Framework for Aircraft Detection
2022
Remote Sensing
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However, the multi-scale detection of aircrafts and their key parts from remote sensing images can be a challenge, as images often present complex backgrounds and obscured conditions. ...
Aircrafts have been an important object of study in the field of multi-scale image object detection due to their important strategic role. ...
Acknowledgments: All individuals included in this section have consented to the acknowledgment.
Conflicts of Interest: The authors declare no conflict of interest. Remote Sens. 2022, 14, 3696 ...
doi:10.3390/rs14153696
fatcat:fb76r6di55d7fhjrrwotv6dwwe
SAFFNet: Self-Attention-Based Feature Fusion Network for Remote Sensing Few-Shot Scene Classification
2021
Remote Sensing
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In this paper, a multi-scale feature fusion network for few-shot remote sensing scene classification is proposed by integrating a novel self-attention feature selection module, denoted as SAFFNet. ...
Unlike a pyramidal feature hierarchy for object detection, the informative representations of the images with different receptive fields are automatically selected and re-weighted for feature fusion after ...
Conclusions In the paper, a self-attention feature selection module was proposed for deep feature fusion in a multi-scale structure for a few-shot remote sensing image classification. ...
doi:10.3390/rs13132532
fatcat:fonmvysiczct5kr7wwl3xe2xdm
Multi-Size Object Detection in Large Scene Remote Sensing Images under Dual Attention Mechanism
2022
IEEE Access
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The remote sensing images in large scenes have a complex background, and the types, sizes, and postures of the targets are different, making object detection in remote sensing images difficult. ...
First, the MobileNets backbone network is used to extract multi-layer features of remote sensing images as the input of MFCA, a multi-size feature concentration attention module. ...
ACKNOWLEDGMENT (Jinkang Wang and Xiaohui He are co-first authors.) ...
doi:10.1109/access.2022.3141059
fatcat:vlykxovebzhkdigrunszxyppmu
Object Detection in Remote Sensing Images by Combining Feature Enhancement and Hybrid Attention
2022
Applied Sciences
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The objects in remote sensing images have large-scale variations, arbitrary directions, and are usually densely arranged, and small objects are easily submerged by background noises. ...
Firstly, a feature enhancement fusion network (FEFN) is designed, which carries out dilated convolution with different dilation rates acting on the multi-layer features, and thus fuses multi-scale, multi-receptive ...
With the development of remote sensing techniques, object detection in remote sensing images is gradually attracting attention. Object detection is a very challenging task in computer vision. ...
doi:10.3390/app12126237
fatcat:dv4hkq5ujfeyjfgh534ytp7264
A2RMNet: Adaptively Aspect Ratio Multi-Scale Network for Object Detection in Remote Sensing Images
2019
Remote Sensing
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Object detection is a significant and challenging problem in the study area of remote sensing and image analysis. ...
On the one hand, we design a multi-scale feature gate fusion network to adaptively integrate the multi-scale features of objects. ...
Given a remote sensing image, a multi-scale feature gate fusion network adaptively aggregates semantic features of different scale using gate fusion modules and refine blocks. ...
doi:10.3390/rs11131594
fatcat:rvhpanwnanb67ir7q764c2y2nm
An Adaptive Attention Fusion Mechanism Convolutional Network for Object Detection in Remote Sensing Images
2022
Remote Sensing
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For remote sensing object detection, fusing the optimal feature information automatically and overcoming the sensitivity to adapt multi-scale objects remains a significant challenge for the existing convolutional ...
Such a process can effectively balance the proportion of multi-scale objects and handle the scale-variable properties. ...
Author Contributions: Y.Y. and X.R. developed the method and wrote the manuscript. B.Z., T.T. and X.T. designed and carried out the experiments. Y.G. and Q.Y. reviewed and edited the manuscript. ...
doi:10.3390/rs14030516
fatcat:qxgzg4pphrhs5bkn6pa5i2bgv4
A Self-Attentive Hybrid Coding Network for 3D Change Detection in High-Resolution Optical Stereo Images
2022
Remote Sensing
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This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY ...
Acknowledgments: We sincerely appreciate Yong Hu of the Chongqing Institute of Planning and Natural Resources Monitoring for providing the GF-7 experimental data. ...
The helpful comments and constructive suggestions of academic editors and reviewers.
Conflicts of Interest: The authors declare no conflict of interest. ...
doi:10.3390/rs14092046
dblp:journals/remotesensing/PanLCSC22
fatcat:wzskwmguu5eabdsutkzq7nbwgq
Tucker Bilinear Attention Network for Multi-scale Remote Sensing Object Detection
[article]
2023
arXiv
pre-print
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Based on two modules, we build a new multi-scale remote sensing object detection framework. No bells and whistles. ...
Object detection on VHR remote sensing images plays a vital role in applications such as urban planning, land resource management, and rescue missions. ...
The study [19] introduced a one-stage full-scale object detection network for remote sensing images named FSoD-Net which consists of a powerful multi-scale enhancement network cascaded with scale-invariant ...
arXiv:2303.05329v1
fatcat:uys7afq55zd3vhvthkh4dzmy5a
CF2PN: A Cross-Scale Feature Fusion Pyramid Network Based Remote Sensing Target Detection
2021
Remote Sensing
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Unfortunately, unlike natural image processing, remote sensing image processing involves dealing with large variations in object size, which poses a great challenge to researchers. ...
First and foremost, a cross-scale fusion module (CSFM) is introduced to extract sufficiently comprehensive semantic information from features for performing multi-scale fusion. ...
Acknowledgments: The authors would like to thank the editors and reviewers for their advice.
Conflicts of Interest: The authors declare no conflict of interest. ...
doi:10.3390/rs13050847
fatcat:nbkfadfggbghjpwn32tjgky2k4
Multi-Feature Information Complementary Detector: A High-Precision Object Detection Model for Remote Sensing Images
2022
Remote Sensing
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Remote sensing for image object detection has numerous important applications. However, complex backgrounds and large object-scale differences pose considerable challenges in the detection task. ...
The detector proposed also improves the detection performance of objects at different scales in the same image using a dual multi-scale feature fusion strategy. ...
Object Detection of Multi-Scale Objects The feature pyramid network (FPN) is a common method for solving multi-scale objects in object detection tasks; many scholars have applied it to remote sensing object ...
doi:10.3390/rs14184519
fatcat:al6zkdjb4jcu5bzxpusxqhcbky
MFSFNet: Multi-Scale Feature Subtraction Fusion Network for Remote Sensing Image Change Detection
2023
Remote Sensing
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Change detection plays a crucial role in remote sensing by identifying surface modifications between two sets of temporal remote sensing images. ...
To overcome these challenges, this paper proposes a Multi-Scale Feature Subtraction Fusion Network (MFSF-Net). ...
Additionally, objects in remote sensing images exhibit different sizes, and a robust and generalizable model should be capable of handling various object scales. ...
doi:10.3390/rs15153740
fatcat:rl7bhr2wizfkzotulwqpknppse
MSF-Net: A multiscale supervised fusion network for building change detection in high-resolution remote sensing images
2022
IEEE Access
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Building change detection is a primary task in the application of remote sensing images, especially in city land resource management and urbanization process assesment. ...
To fill these gaps" this study proposes a multiscale supervised fusion network (MSF-Net), which is an attention mechanismbased approach for building change detection using bi-temporal high-resolution satellite ...
High-resolution remote sensing images have become an important data source for change detection, due to their rich ground object texture features and ground object multiscale features. ...
doi:10.1109/access.2022.3160163
fatcat:fmh7uts5svfyznu2h55uenve5y
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