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Paper

Embedded Platforms for Computer Vision-based Advanced Driver Assistance Systems: a Survey

by Independent / Community 0024437badc418b788a7c3459441bb811eab7670

Free2AITools Nexus Index

64.3

S: Semantic 50

Query-time baseline · scored live at search

A: Authority 73

P: Popularity 48

R: Recency 100

Q: Quality 65

Tech Context

Vital Performance —

Computer Vision, either alone or combined with other technologies such as radar or Lidar, is one of the key technologies used in Advanced Driver Assistance Systems (ADAS). Its role understanding and analysing the driving scene is of great importance as it can be noted by the number of ADAS applications that use this technology. However, porting a vision algorithm to an embedded automotive system is still very challenging, as there must be a trade-off between several design requisites. Further...

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Semantic Scholar 6 Citations

Paper Information Summary
Entity Passport
Registry ID	0024437badc418b788a7c3459441bb811eab7670
License	ArXiv
Provider	semantic_scholar

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Cite this paper

Academic & Research Attribution

BibTeX

@misc{0024437badc418b788a7c3459441bb811eab7670,
  author = {Unknown},
  title = {Embedded Platforms for Computer Vision-based Advanced Driver Assistance Systems: a Survey Paper},
  year = {2026},
  howpublished = {\url{https://api.semanticscholar.org/0024437badc418b788a7c3459441bb811eab7670}},
  note = {Accessed via Free2AITools.}
}

APA Style

Unknown. (2026). Embedded Platforms for Computer Vision-based Advanced Driver Assistance Systems: a Survey [Paper]. Free2AITools. https://api.semanticscholar.org/0024437badc418b788a7c3459441bb811eab7670

🔬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) 73

Popularity (P) 48

Recency (R) 100

Quality (Q) 65

💬 Index Insight

FNI V2.0 for Embedded Platforms for Computer Vision-based Advanced Driver Assistance Systems: a Survey: Authority (A:73), Popularity (P:48), 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

"Computer Vision, either alone or combined with other technologies such as radar or Lidar, is one of the key technologies used in Advanced Driver Assistance Systems (ADAS). Its role understanding and analysing the driving scene is of great importance as it can be noted by the number of ADAS applications that use this technology. However, porting a vision algorithm to an embedded automotive system is still very challenging, as there must be a trade-off between several design requisites. Further..."

❝ Cite Node

@article{Unknown2026Embedded,
  title={Embedded Platforms for Computer Vision-based Advanced Driver Assistance Systems: a Survey},
  author={},
  note={Indexed by Free2AITools},
  year={2026}
}

🔗 Full Paper

Free2AITools indexes the abstract and factual metadata for this paper. Read the complete, authoritative paper on the official source.

Read the full paper on arXiv

📊 Research Signals

📈6CitationsSemantic Scholar

🏛️73AuthorityFNI pillar

⏱️100RecencyFNI pillar

✅65QualityFNI pillar

🗂️knowledge retrievalField

🏷️ Research Topics

vision models

📦Data Source: semantic_scholar

🔄 Updated daily

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

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🛡️ Paper Transparency Report

Technical metadata sourced from upstream repositories.

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🆔 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: 6

Data indexed from public sources. Updated daily.