Home › Entities › academia › Using cascade CNN-LSTM-FCNs to identify AI-altered video based on eye state sequence

Using cascade CNN-LSTM-FCNs to identify AI-altered video based on eye state sequence

Research article (PLoS ONE, 2022) · cited 18× · AI/ML
academia openalex:W4311552567
Press Enter · cited answer in seconds

Using cascade CNN-LSTM-FCNs to identify AI-altered video based on eye state sequence

Summary

Using cascade CNN-LSTM-FCNs to identify AI-altered video based on eye state sequence is a scholarly article[1].

Key Facts

  • Using cascade CNN-LSTM-FCNs to identify AI-altered video based on eye state sequence's instance of is recorded as scholarly article[2].

References

Programmatic citations — every numbered marker resolves to a verifiable graph row below.

Direct Wikidata claims

  1. [2] ↑ . wikidata.org.

Class ancestry

  1. [1] ↑ . Wikidata. wikidata.org.

📑 Cite this page

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.

APA 4ort.xyz Knowledge Graph. (2026). Using cascade CNN-LSTM-FCNs to identify AI-altered video based on eye state sequence. Retrieved May 24, 2026, from https://4ort.xyz/entity/using-cascade-cnn-lstm-fcns-to-identify-ai-altered-video-based-on-eye-state-sequence
MLA “Using cascade CNN-LSTM-FCNs to identify AI-altered video based on eye state sequence.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/using-cascade-cnn-lstm-fcns-to-identify-ai-altered-video-based-on-eye-state-sequence.
BibTeX @misc{4ortxyz_using-cascade-cnn-lstm-fcns-to-identify-ai-altered-video-based-on-eye-state-sequence_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Using cascade CNN-LSTM-FCNs to identify AI-altered video based on eye state sequence}}, year = {2026}, url = {https://4ort.xyz/entity/using-cascade-cnn-lstm-fcns-to-identify-ai-altered-video-based-on-eye-state-sequence}, note = {Accessed: 2026-05-24}}
LLM prompt According to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Using cascade CNN-LSTM-FCNs to identify AI-altered video based on eye state sequence — https://4ort.xyz/entity/using-cascade-cnn-lstm-fcns-to-identify-ai-altered-video-based-on-eye-state-sequence (retrieved 2026-05-24)

Canonical URL: https://4ort.xyz/entity/using-cascade-cnn-lstm-fcns-to-identify-ai-altered-video-based-on-eye-state-sequence · Last refreshed: