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Double FCOS: A Two-Stage Model Utilizing FCOS for Vehicle Detection in Various Remote Sensing Scenes
2022
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
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Double FCOS is a two-stage detection model based on FCOS. FCOS is exploited in the RPN stage to generate candidate boxes in various scenes. ...
dataset (4MVD) for vehicle detection in various remote sensing scenes. ...
A two-stage detection model called double FCOS is dedicated for vehicle detection in a variety of remote sensing scenes. ...
doi:10.1109/jstars.2022.3181594
fatcat:p7hzt7ctizc6tixyd3d4duyg2e
Generating Anchor Boxes Based on Attention Mechanism for Object Detection in Remote Sensing Images
2020
Remote Sensing
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However, the complex background and the wide range of object sizes in remote sensing images increase the difficulty of object detection. ...
Nowadays, object detection methods based on deep learning are applied more and more to the interpretation of optical remote sensing images. ...
The current object detection methods for remote sensing images are mostly two-stage methods, which are proposed on the basis of region CNN (RCNN) [14] . ...
doi:10.3390/rs12152416
fatcat:uvxbxt2pebe3roalesgycwotyq
Object Detection Based on Adaptive Feature-Aware Method in Optical Remote Sensing Images
2022
Remote Sensing
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Object detection is used widely in remote sensing image interpretation. ...
in remote sensing images. ...
[34] proposed an object and scene context-constrained object detection model for remote sensing images, in which the scene context-constrained channel uses a priori scene information and Bayesian criteria ...
doi:10.3390/rs14153616
fatcat:hlcymgrnojakjjmblqinlrry5q
Urban Traffic Monitoring and Analysis Using Unmanned Aerial Vehicles (UAVs): A Systematic Literature Review
2022
Remote Sensing
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Unmanned aerial vehicles (UAVs) are gaining considerable interest in transportation engineering in order to monitor and analyze traffic. ...
It can be stated that this is still a field in its infancy and that progress in advanced image processing techniques and technologies used in the construction of UAVs will lead to an explosion in the number ...
Author Paper Aim Findings Future Work Proposing a robust vehicle detection model for aerial images. ...
doi:10.3390/rs14030620
fatcat:qjtkacwm2rfhfmsrn3ju57tl3i
Fast and Accurate Object Detection in Remote Sensing Images Based on Lightweight Deep Neural Network
2021
Sensors
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Deep learning-based object detection in remote sensing images is an important yet challenging task due to a series of difficulties, such as complex geometry scene, dense target quantity, and large variant ...
To deal with these challenges, we proposed a lightweight YOLO-like object detector with the ability to detect objects in remote sensing images with high speed and high accuracy. ...
Figure 1 . 1 Demonstration of complicated remote sensing scenes in RSOD dataset. The detected bounding box are draw by using YOLOv4-Tiny. ...
doi:10.3390/s21165460
pmid:34450908
pmcid:PMC8398883
fatcat:u6eng3xfdrhqrp2kacan23oeqm
MTP: Advancing Remote Sensing Foundation Model via Multi-Task Pretraining
[article]
2024
arXiv
pre-print
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2024 pre-print arXiv:2403.13430v1 fatcat:wnarflzovzbdlbkulcgf2lcgay
Foundation models have reshaped the landscape of Remote Sensing (RS) by enhancing various image interpretation tasks. ...
The pretrained models are finetuned on various RS downstream tasks, such as scene classification, horizontal and rotated object detection, semantic segmentation, and change detection. ...
ACKNOWLEDGEMENT The numerical calculations in this paper are partly supported by the Dawning Information Industry Co., Ltd. ...
arXiv:2403.13430v2
fatcat:x3y72btcvveczdiakp3bbpy524
A New Road Damage Detection Baseline with Attention Learning
2022
Applied Sciences
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Automated detection of road damage (ADRD) is a challenging topic in road maintenance. It focuses on automatically detecting road damage and assessing severity by deep learning. ...
With the aim of solving this problem, this work publishes a new road damage dataset named CNRDD, which is labeled according to the latest evaluation standard for highway technical conditions in China ( ...
Faster RCNN is widely used in pedestrian detection, remote sensing image detection and other practical applications. ...
doi:10.3390/app12157594
fatcat:74co6tgo35bw7ajmo2v47plvpy
A Guide to Image and Video based Small Object Detection using Deep Learning : Case Study of Maritime Surveillance
[article]
2022
arXiv
pre-print
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Small object detection (SOD) in optical images and videos is a challenging problem that even state-of-the-art generic object detection methods fail to accurately localize and identify such objects. ...
In addition, the popular datasets that have been used for SOD for generic and maritime applications are discussed, and also well-known evaluation metrics for the state-of-the-art methods on some of the ...
Additionally, the fusion of shallow features and deep features has also been used to detect ships in remote sensing images [160] for ship detection of remote sensing images. ...
arXiv:2207.12926v1
fatcat:fjcuijt2f5d63apgg67eiydofa
Artificial and beneficial – Exploiting artificial images for aerial vehicle detection
2021
ISPRS journal of photogrammetry and remote sensing (Print)
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2021 pre-print arXiv:2104.03054v1 fatcat:or5jqx3f7vf27cni4sfkwugflm
A major challenge in such approaches is the limited amount of data that arises, for example, when more specialized and rarer vehicles such as agricultural machinery or construction vehicles are to be detected ...
One of the most prominent applications is the detection of vehicles, for which deep learning approaches are increasingly used. ...
Acknowledgement The authors would like to thank the DVGW -German Technical and Scientific Association for Gas and Water -for funding this work as part of the research project G201819 -Antonia. ...
doi:10.1016/j.isprsjprs.2021.02.015
fatcat:qhb2hulzdbe5hc3jnyaq5igvvq
Recent Advancements in Deep Learning Applications and Methods for Autonomous Navigation – A Comprehensive Review
[article]
2023
arXiv
pre-print
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This review paper presents a comprehensive overview of end-to-end deep learning frameworks used in the context of autonomous navigation, including obstacle detection, scene perception, path planning, and ...
The review provides a valuable resource for researchers and practitioners working in the field of autonomous navigation and deep learning. ...
Acknowledgements The study presented in this paper is based on A. Asgharpoor Golroudbari's M.Sc. ...
arXiv:2302.11089v2
fatcat:axsn4a5lb5fcvikj5qqlnkxkv4
Dense Label Encoding for Boundary Discontinuity Free Rotation Detection
[article]
2021
arXiv
pre-print
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Rotation detection serves as a fundamental building block in many visual applications involving aerial image, scene text, and face etc. ...
We propose new techniques to push its frontier in two aspects: i) new encoding mechanism: the design of two Densely Coded Labels (DCL) for angle classification, to replace the Sparsely Coded Label (SCL ...
Introduction Rotation detection has recently attracted increasing attention for their important utility across different scenarios, including aerial images, scene text, and faces etc., which is relatively ...
arXiv:2011.09670v4
fatcat:mwoobfo7jzdrdc7dwdgj4glg2u
Deep Learning in Diverse Intelligent Sensor Based Systems
2022
Sensors
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Deep learning has become a predominant method for solving data analysis problems in virtually all fields of science and engineering. ...
for deep learning practitioners and those seeking to innovate deep learning in this space. ...
Object detection in remote sensing aims to identify ground objects of interest such as vehicles, roads, buildings or airports from images and correctly classify them. ...
doi:10.3390/s23010062
pmid:36616657
pmcid:PMC9823653
fatcat:riifuhqtnrbrrkat26mxummwd4
Review of data analysis in vision inspection of power lines with an in-depth discussion of deep learning technology
[article]
2020
arXiv
pre-print
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With the aim of providing a comprehensive overview for researchers who are interested in developing a deep-learning-based analysis system for power lines inspection data, this paper conducts a thorough ...
Following the typical procedure of inspection data analysis, we categorize current works in this area into component detection and fault diagnosis. ...
The authors also employed the cGAN for insulator detection [130] . A two-stage training strategy was proposed to obtain a more accurate cGAN model. ...
arXiv:2003.09802v1
fatcat:2ywazixc2vfq7c35pgzci5gmgq
Remotely Powered Propulsion of Helical Nanobelts
[chapter]
2016
Encyclopedia of Nanotechnology
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Synonyms Bond-order potential; REBO Definition Reactive empirical bond-order potentials are interatomic energy functions used in molecular dynamics simulation and modeling of nanosystems where an accurate ...
To compensate for the uncertainty introduced by the inevitable "blind" manipulation, a model of the manipulation process is utilized enabling a manipulation in open-loop mode. ...
For a reliable alignment in z-direction, a shadow-based depth detection technique is presented. ...
doi:10.1007/978-94-017-9780-1_204
fatcat:6mgkahuskvex3lg42y2iexjusa
Refractometric Sensing Using Plasmonic Nanoparticles
[chapter]
2016
Encyclopedia of Nanotechnology
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Synonyms Bond-order potential; REBO Definition Reactive empirical bond-order potentials are interatomic energy functions used in molecular dynamics simulation and modeling of nanosystems where an accurate ...
To compensate for the uncertainty introduced by the inevitable "blind" manipulation, a model of the manipulation process is utilized enabling a manipulation in open-loop mode. ...
For a reliable alignment in z-direction, a shadow-based depth detection technique is presented. ...
doi:10.1007/978-94-017-9780-1_100984
fatcat:mfkokslav5fddendtnn2mjcuoy
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