Deep Learning based enhanced aerial object detection Article Swipe
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· 2025
· Open Access
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· DOI: https://doi.org/10.58825/jog.2025.19.1.197
In congested urban environments, accurate detection and counting of humans and vehicles provide valuable insights for optimizing traffic flow, identifying congestion hotspots, and designing efficient transportation systems. By leveraging computer vision algorithms, such as deep learning based object detection models, real-time monitoring of pedestrian and vehicular traffic can be achieved with high accuracy and granularity. The ability to precisely quantify pedestrian and vehicle movements enables urban planners and policymakers to make data-driven decisions regarding infrastructure development, road maintenance, and public transit planning. In this work, we enhanced the existing deep learning based network architecture for object detection using UAV images. The enhanced network architecture can detect and give a count of the number of objects for any particular area in the image.
Related Topics
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.58825/jog.2025.19.1.197
- https://onlinejog.org/index.php/journal_of_geomatics/article/download/197/80
- OA Status
- diamond
- References
- 28
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4410135162
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4410135162Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.58825/jog.2025.19.1.197Digital Object Identifier
- Title
-
Deep Learning based enhanced aerial object detectionWork title
- Type
-
articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2025Year of publication
- Publication date
-
2025-04-30Full publication date if available
- Authors
-
Avinash Chouhan, Dibyajyoti Chutia, Biswarup Deb, S. P. AggarwalList of authors in order
- Landing page
-
https://doi.org/10.58825/jog.2025.19.1.197Publisher landing page
- PDF URL
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https://onlinejog.org/index.php/journal_of_geomatics/article/download/197/80Direct link to full text PDF
- Open access
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YesWhether a free full text is available
- OA status
-
diamondOpen access status per OpenAlex
- OA URL
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https://onlinejog.org/index.php/journal_of_geomatics/article/download/197/80Direct OA link when available
- Concepts
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Artificial intelligence, Object detection, Computer vision, Deep learning, Aerial imagery, Object (grammar), Computer science, Geography, Cartography, Remote sensing, Change detection, Pattern recognition (psychology)Top concepts (fields/topics) attached by OpenAlex
- Cited by
-
0Total citation count in OpenAlex
- References (count)
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28Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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