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Drone detection using YOLOv3 with transfer learning on NVIDIA Jetson TX2 paper by Independent / Community
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Paper

Drone detection using YOLOv3 with transfer learning on NVIDIA Jetson TX2

by Independent / Community 00ce73428e3e3e5fc62bb776c1fad514cc5046d5
Free2AITools Nexus Index
69.0
S: Semantic 50

Query-time baseline · scored live at search

A: Authority 84
P: Popularity 60
R: Recency 100
Q: Quality 65
Tech Context
Vital Performance —

The rise of drones in the recent years largely due to the advancements of drone technology which provide drones the ability to perform many more complex tasks autonomously with the incorporation of technologies such as computer vision, object avoidance and artificial intelligence. However, the misuse of drones such as the Gatwick Airport drone incident resulted in major disruptions which affected approximately 140,000 passengers. To deter this from happening in the future, drone surveillance ...

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Semantic Scholar 52 Citations
Paper Information Summary
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Registry ID 00ce73428e3e3e5fc62bb776c1fad514cc5046d5
License ArXiv
Provider semantic_scholar
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Cite this paper

Academic & Research Attribution

BibTeX 
@misc{00ce73428e3e3e5fc62bb776c1fad514cc5046d5,
  author = {Unknown},
  title = {Drone detection using YOLOv3 with transfer learning on NVIDIA Jetson TX2 Paper},
  year = {2026},
  howpublished = {\url{https://api.semanticscholar.org/00ce73428e3e3e5fc62bb776c1fad514cc5046d5}},
  note = {Accessed via Free2AITools.}
}
APA Style
Unknown. (2026). Drone detection using YOLOv3 with transfer learning on NVIDIA Jetson TX2 [Paper]. Free2AITools. https://api.semanticscholar.org/00ce73428e3e3e5fc62bb776c1fad514cc5046d5

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βš–οΈ Free2AITools Nexus Index V2.0

Methodology How FNI works
Semantic (S) 50

Query-time baseline · scored live at search

Authority (A) 84
Popularity (P) 60
Recency (R) 100
Quality (Q) 65

πŸ’¬ Index Insight

FNI V2.0 for Drone detection using YOLOv3 with transfer learning on NVIDIA Jetson TX2: Authority (A:84), Popularity (P:60), Recency (R:100), Quality (Q:65). Semantic (S) is a query-time baseline scored live at search.

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πŸ“ Executive Summary

"The rise of drones in the recent years largely due to the advancements of drone technology which provide drones the ability to perform many more complex tasks autonomously with the incorporation of technologies such as computer vision, object avoidance and artificial intelligence. However, the misuse of drones such as the Gatwick Airport drone incident resulted in major disruptions which affected approximately 140,000 passengers. To deter this from happening in the future, drone surveillance ..."

❝ Cite Node 

@article{Unknown2026Drone,
  title={Drone detection using YOLOv3 with transfer learning on NVIDIA Jetson TX2},
  author={},
  note={Indexed by Free2AITools},
  year={2026}
}

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πŸ“Š Research Signals

πŸ“ˆ52CitationsSemantic Scholar
πŸ›οΈ84AuthorityFNI pillar
⏱️100RecencyFNI pillar
βœ…65QualityFNI pillar
πŸ—‚οΈvision multimediaField

🏷️ Research Topics

vision models
πŸ“¦Data Source: semantic_scholar
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πŸ†” Identity & Source

source
semantic_scholar
author
Unknown
license
ArXiv
tags
paper, research, academic

βš™οΈ Technical Specs

architecture
null
params billions
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