Publication2025
A Hybridized Approach for Detecting Modified Frames in Video Using Deep Predictive Intelligence
- Industry, Innovation and Infrastructure
- Peace, Justice and Strong Institutions
- Partnerships for the Goals
- Good Governance and Security
The record
- Type
- Publication
- Date
- 1 January 2025
- Level
- International — held abroad
- Journal
- Lecture Notes in Networks and Systems
- Volume
- 1436 LNNS
- Pages
- 461-474
- Published
- 1 January 2025
- DOI
- 10.1007/978-981-96-7134-2_33
- Scopus ID
- 105019313418
- ISSN
- 23673370
- Authors
- 6
- Open access
- No
- Citations
- 0
- International co-authorship
- Yes
- Co-author countries
- CN, GB, IN, US
Classification
Every label below carries the reasoning it was assigned on, the confidence band it was assigned in, and what produced it. The rubric is published.
UN Sustainable Development Goals
16 Promote peaceful and inclusive societies for sustainable development, provide access to justice for all and build effective, accountable and inclusive institutions at all levels
Deep learning approach with explainable AI detects video frame forgery and tampering with high accuracy, supporting justice systems and forensic verification.
- High confidence
- The subject matter is a strong and direct inference from the record type, the funding or organising body, or the programme context, even where the title alone is thin. Example: an ICMR-funded project against SDG 3, on the strength of the agency.
- Judged
- Judged against the published classification rubric, under the rubric and prompt versions recorded with the run that produced it.
- Produced by
- claude-haiku-4-5-20251001, under kortex-publication-v1
9.5 Enhance scientific research, upgrade technological capabilities, and increase researchers and R&D spending
Hybrid deep learning model combining optical flow and pixel analysis represents innovation in computer vision methodology.
- Moderate confidence
- The alignment is plausible and defensible but rests on an assumption a reasonable reviewer could decline. Published, and surfaced in the review queue for a human to confirm or override.
- Produced by
- claude-haiku-4-5-20251001, under kortex-publication-v1
17.6 Enhance North-South, South-South and triangular cooperation on science, technology and innovation, and knowledge sharing
Structural signal: co-authorship outside India.
- Rule-derived
- Emitted by a deterministic rule from structural signals rather than judged from the record’s text. The rule carries a version, so rule-derived and judged labels stay separable.
- Produced by
- sdg17-structural-v1, under kortex-publication-v1
Viksit Bharat @2047
vb-4 Good Governance and Security
Derived through the seeded SDG-to-Viksit-Bharat crosswalk from the primary SDG 16 label. Deep learning approach with explainable AI detects video frame forgery and tampering with high accuracy, supporting justice systems and forensic verification.
- Produced by
- claude-haiku-4-5-20251001, under kortex-publication-v1
Each label above carries the instrument and the version that produced it. How each classification is reached.
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- 1
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Citing this record
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KIIT Deemed to be University. “A Hybridized Approach for Detecting Modified Frames in Video Using Deep Predictive Intelligence”. Kortex.