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Jamimamul Bakas
Jamimamul Bakas
Verified email at nitrkl.ac.in
Title
Cited by
Cited by
Year
Detection and localization of inter-frame video forgeries based on inconsistency in correlation distribution between Haralick coded frames
J Bakas, R Naskar, R Dixit
Multimedia Tools and Applications 78, 4905-4935, 2019
462019
A digital forensic technique for inter–frame video forgery detection based on 3D CNN
J Bakas, R Naskar
International Conference on Information Systems Security, 304-317, 2018
322018
Detection and localization of inter-frame forgeries in videos based on macroblock variation and motion vector analysis
J Bakas, R Naskar, S Bakshi
Computers & Electrical Engineering 89, 106929, 2021
252021
Mpeg double compression based intra-frame video forgery detection using cnn
J Bakas, AK Bashaboina, R Naskar
2018 International Conference on Information Technology (ICIT), 221-226, 2018
142018
Object-based forgery detection in surveillance video using capsule network
J Bakas, R Naskar, M Nappi, S Bakshi
Journal of Ambient Intelligence and Humanized Computing, 1-11, 2023
112023
Double and triple compression-based forgery detection in JPEG images using deep convolutional neural network
J Bakas, S Ramachandra, R Naskar
Journal of Electronic Imaging 29 (2), 023006-023006, 2020
82020
Re–compression based JPEG tamper detection and localization using deep neural network, eliminating compression factor dependency
J Bakas, P Rawat, K Kokkalla, R Naskar
Information Systems Security: 14th International Conference, ICISS 2018 …, 2018
32018
Detection of Object-Based Forgery in Surveillance Videos Utilizing Motion Residual and Deep Learning
M Raj, J Bakas
International Conference on Distributed Computing and Intelligent Technology …, 2023
2023
Compressed Multimedia Forgery Detection through Blind Digital Forensics
J Bakas
2022
12 Illegitimate EPR
S Chinara, R Naskar, J Bakas, SN Mishra
IoT: Security and Privacy Paradigm, 257, 2020
2020
Detection and Localization of Double-Compressed Forged Regions in JPEG Images Using DCT Coefficients and Deep Learning–Based CNN
J Bakas, R Naskar
Artificial Intelligence and Deep Learning for Computer Network, 99-117, 0
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