What question did this study set out to answer?

To enhance temporal modelling for the semantic classification of ethically sensitive video content using YOLOv8.

May 8, 2026

YOLOv8-enhanced temporal modelling for semantic classification of ethically sensitive video content

Key Points

To enhance temporal modelling for the semantic classification of ethically sensitive video content using YOLOv8.
Implemented YOLOv8 for improved semantic classification of video content.
Utilized temporal modelling techniques to analyze video sequences.
Conducted trials to evaluate the accuracy and effectiveness of the approach.
Demonstrated significant improvement in classification accuracy compared to traditional methods.
Achieved a higher detection rate for ethically sensitive content, with specific metrics reflecting performance.

Abstract

Inderscience is a global company, a dynamic leading independent journal publisher disseminates the latest research across the broad fields of science, engineering and technology; management, public and business administration; environment, ecological economics and sustainable development; computing, ICT and internet/web services, and related areas.

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Authors

Chelsi Sen

Kuldeep Kumar Yogi

Journals

International Journal of Innovative Computing and Applications

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YOLOv8-enhanced temporal modelling for semantic classification of ethically sensitive video content

Key Points

Abstract

Citation Network

Connected Papers

Discussion

Authors

Journals

Actions

References and Citations

Citation Network

Connected Papers

Discussion

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