Home ›
Entities
› academia
› Impact of Dataset and Model Parameters on Machine Learning Performance for the Detection of GPS Spoofing Attacks on Unmanned Aerial Vehicles
Impact of Dataset and Model Parameters on Machine Learning Performance for the Detection of GPS Spoofing Attacks on Unmanned Aerial Vehicles
Research article (Applied Sciences, 2022) · cited 30× · AI/ML
Impact of Dataset and Model Parameters on Machine Learning Performance for the Detection of GPS Spoofing Attacks on Unmanned Aerial Vehicles
Summary
Impact of Dataset and Model Parameters on Machine Learning Performance for the Detection of GPS Spoofing Attacks on Unmanned Aerial Vehicles is a scholarly article[1].
Key Facts
Impact of Dataset and Model Parameters on Machine Learning Performance for the Detection of GPS Spoofing Attacks on Unmanned Aerial Vehicles's instance of is recorded as scholarly article[2].
References
Programmatic citations — every numbered marker resolves to a verifiable graph row below.
Use these citations when quoting this entity in research, articles, AI prompts, or wherever provenance matters. We aggregate Wikidata + Wikipedia + authoritative open-data sources; the stitched, scored, cross-referenced view is what 4ort.xyz contributes.
APA4ort.xyz Knowledge Graph. (2026). Impact of Dataset and Model Parameters on Machine Learning Performance for the Detection of GPS Spoofing Attacks on Unmanned Aerial Vehicles. Retrieved May 24, 2026, from https://4ort.xyz/entity/impact-of-dataset-and-model-parameters-on-machine-learning-performance-for-the-detection-of-gps-spoofing-attacks-on-unma
MLA“Impact of Dataset and Model Parameters on Machine Learning Performance for the Detection of GPS Spoofing Attacks on Unmanned Aerial Vehicles.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/impact-of-dataset-and-model-parameters-on-machine-learning-performance-for-the-detection-of-gps-spoofing-attacks-on-unma.
BibTeX@misc{4ortxyz_impact-of-dataset-and-model-parameters-on-machine-learning-performance-for-the-detection-of-gps-spoofing-attacks-on-unma_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Impact of Dataset and Model Parameters on Machine Learning Performance for the Detection of GPS Spoofing Attacks on Unmanned Aerial Vehicles}}, year = {2026}, url = {https://4ort.xyz/entity/impact-of-dataset-and-model-parameters-on-machine-learning-performance-for-the-detection-of-gps-spoofing-attacks-on-unma}, note = {Accessed: 2026-05-24}}
LLM promptAccording to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Impact of Dataset and Model Parameters on Machine Learning Performance for the Detection of GPS Spoofing Attacks on Unmanned Aerial Vehicles — https://4ort.xyz/entity/impact-of-dataset-and-model-parameters-on-machine-learning-performance-for-the-detection-of-gps-spoofing-attacks-on-unma (retrieved 2026-05-24)
