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Paper

Augmented reality-based vision-aid indoor navigation system in GPS denied environment

by Independent / Community 00dc8c9857a74b4120f3cc08c4656b3f502b026a

Free2AITools Nexus Index

67.1

S: Semantic 50

Query-time baseline · scored live at search

A: Authority 80

P: Popularity 55

R: Recency 100

Q: Quality 65

Tech Context

Vital Performance —

High accuracy localization and user positioning tracking is critical in improving the quality of augmented reality environments. The biggest challenge facing developers is localizing the user based on visible surroundings. Current solutions rely on the Global Positioning System (GPS) for tracking and orientation. However, GPS receivers have an accuracy of about 10 to 30 meters, which is not accurate enough for augmented reality, which needs precision measured in millimeters or smaller. This p...

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Semantic Scholar 19 Citations

Paper Information Summary
Entity Passport
Registry ID	00dc8c9857a74b4120f3cc08c4656b3f502b026a
License	ArXiv
Provider	semantic_scholar

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Cite this paper

Academic & Research Attribution

BibTeX

@misc{00dc8c9857a74b4120f3cc08c4656b3f502b026a,
  author = {Unknown},
  title = {Augmented reality-based vision-aid indoor navigation system in GPS denied environment Paper},
  year = {2026},
  howpublished = {\url{https://api.semanticscholar.org/00dc8c9857a74b4120f3cc08c4656b3f502b026a}},
  note = {Accessed via Free2AITools.}
}

APA Style

Unknown. (2026). Augmented reality-based vision-aid indoor navigation system in GPS denied environment [Paper]. Free2AITools. https://api.semanticscholar.org/00dc8c9857a74b4120f3cc08c4656b3f502b026a

🔬Technical Deep Dive

Full Specifications [+]

⚖️ Free2AITools Nexus Index V2.0

Methodology How FNI works

Semantic (S) 50

Query-time baseline · scored live at search

Authority (A) 80

Popularity (P) 55

Recency (R) 100

Quality (Q) 65

💬 Index Insight

FNI V2.0 for Augmented reality-based vision-aid indoor navigation system in GPS denied environment: Authority (A:80), Popularity (P:55), Recency (R:100), Quality (Q:65). Semantic (S) is a query-time baseline scored live at search.

Free2AITools Nexus Index

Data Sources / Provenance

HuggingFace API GitHub Metadata Arxiv Citation DB Methodology

Open data Updated: Live data

📝 Executive Summary

"High accuracy localization and user positioning tracking is critical in improving the quality of augmented reality environments. The biggest challenge facing developers is localizing the user based on visible surroundings. Current solutions rely on the Global Positioning System (GPS) for tracking and orientation. However, GPS receivers have an accuracy of about 10 to 30 meters, which is not accurate enough for augmented reality, which needs precision measured in millimeters or smaller. This p..."

❝ Cite Node

@article{Unknown2026Augmented,
  title={Augmented reality-based vision-aid indoor navigation system in GPS denied environment},
  author={},
  note={Indexed by Free2AITools},
  year={2026}
}

🔗 Full Paper

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Read the full paper on arXiv

📊 Research Signals

📈19CitationsSemantic Scholar

🏛️80AuthorityFNI pillar

⏱️100RecencyFNI pillar

✅65QualityFNI pillar

🗂️vision multimediaField

📦Data Source: semantic_scholar

🔄 Updated daily

Source summary: Based on semantic_scholar metadata. Not a recommendation.

📊 FNI Methodology 📚 Knowledge Baseℹ️ Verify with original source

🛡️ Paper Transparency Report

Technical metadata sourced from upstream repositories.

Open Metadata

🆔 Identity & Source

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

⚙️ Technical Specs

architecture: null
params billions: null
context length: null
pipeline tag

📊 Engagement & Metrics

downloads: 0
stars: null
forks: null
citations: 19

Data indexed from public sources. Updated daily.