Automatic Vehicle Detection from Satellite Images Using Deep Learning Algorithm

Gupta, Himanshu; Jindal, Parul; Verma, Om Prakash

doi:10.1007/978-981-16-1696-9_52

Advances in Intelligent Systems and Computing

2021

DOI: 10.1007/978-981-16-1696-9_52

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Automatic Vehicle Detection from Satellite Images Using Deep Learning Algorithm

Himanshu Gupta

Parul Jindal

Om Prakash Verma

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2024

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Cited by 1 publication

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Ship detection using ensemble deep learning techniques from synthetic aperture radar imagery

Gupta,

Verma,

Sharma

et al. 2024

Sci Rep

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Synthetic Aperture Radar (SAR) integrated with deep learning has been widely used in several military and civilian applications, such as border patrolling, to monitor and regulate the movement of people and goods across land, air, and maritime borders. Amongst these, maritime borders confront different threats and challenges. Therefore, SAR-based ship detection becomes essential for naval surveillance in marine traffic management, oil spill detection, illegal fishing, and maritime piracy. However, the model becomes insensitive to small ships due to the wide-scale variance and uneven distribution of ship sizes in SAR images. This increases the difficulties associated with ship recognition, which triggers several false alarms. To effectively address these difficulties, the present work proposes an ensemble model (eYOLO) based on YOLOv4 and YOLOv5. The model utilizes a weighted box fusion technique to fuse the outputs of YOLOv4 and YOLOv5. Also, a generalized intersection over union loss has been adopted in eYOLO which ensures the increased generalization capability of the model with reduced scale sensitivity. The model has been developed end-to-end, and its performance has been validated against other reported results using an open-source SAR-ship dataset. The obtained results authorize the effectiveness of eYOLO in multi-scale ship detection with an F 1 score and mAP of 91.49% and 92.00%, respectively. This highlights the efficacy of eYOLO in multi-scale ship detection using SAR imagery.

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Ship detection using ensemble deep learning techniques from synthetic aperture radar imagery

Gupta,

Verma,

Sharma

et al. 2024

Sci Rep

View full text Add to dashboard Cite

show abstract

scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.

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Automatic Vehicle Detection from Satellite Images Using Deep Learning Algorithm

Cited by 1 publication

References 12 publications

Ship detection using ensemble deep learning techniques from synthetic aperture radar imagery

Ship detection using ensemble deep learning techniques from synthetic aperture radar imagery

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