A maximum relevancy and minimum redundancy feature selection approach for median filtering forensics

Aanchal Agarwal; Abhinav Gupta

doi:10.1007/s11042-020-08994-4

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A maximum relevancy and minimum redundancy feature selection approach for median filtering forensics

Aanchal Agarwal Abhinav Gupta

Year: 2020 Journal: Multimedia Tools and Applications Vol: 79 (29-30)Pages: 21743-21770 Publisher: Springer Science+Business Media

DOI: 10.1007/s11042-020-08994-4

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Keywords:

Computer science Artificial intelligence Uncompressed video Redundancy (engineering) Feature selection Pattern recognition (psychology) Feature (linguistics) Set (abstract data type) Gaussian

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Digital Media Forensic Detection

Physical Sciences → Computer Science → Computer Vision and Pattern Recognition

Anomaly Detection Techniques and Applications

Physical Sciences → Computer Science → Artificial Intelligence

Advanced Steganography and Watermarking Techniques

Physical Sciences → Computer Science → Computer Vision and Pattern Recognition

A maximum relevancy and minimum redundancy feature selection approach for median filtering forensics

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