ASSESSMENT OF JOB SATISFACTION AMONG EMPLOYEES OF ANIMAL CARE SERVICES KONSULT LIMITED, OGERE REMO, OGUN STATE, NIGERIA
DOI:
https://doi.org/10.33003/fjs-2023-0703-1813Keywords:
Promotion Criteria, Employee, Job Satisfaction, Work-Related Skills, CompetencesReferences
Bagiwa, M. A., Abdul Wahab, A. W., Idna Idris, M. Y., Khan, S., & Choo, K.-K. R. (2016). Chroma key background detection for digital video using statistical correlation of blurring artifact. Digital Investigation, 29-43.
Choras, R. S. (2007). Image feature extraction techniques and their applications for CBIR and biometrics systems. INTERNATIONAL JOURNAL OF BIOLOGY AND BIOMEDICAL ENGINEERING, 1, 1-11.
Cozzolino, D., Poggi, G., & Verdoliva, L. (2014). Copy-move forgery detection based on patch match. ICIP, 5247-5251.
D'Avino, D., Cozzolino, D., Poggi, G., & Verdoliva, L. (2017). Autoencoder with recurrent neural networks for video forgery detection. 1-8.
Davide, Cozzolino. (n.d). GRIP Download Retrieved from http://www.grip.unina.it/web-download.html
Held, D., Thrun, S., & Savarese, S. (2016). Learning to Track at 100 FPS with Deep Regression Networks. 26.
Jessica, F., & Jan, K. ( 2012). Rich models for steganalysis of digital images. IEEE Transactions on Information Forensics and Security, 7(3), 868–882.
Junyu, X., Yanru, Y., Yuting, S., Bo, D., & Xingang, Y. (2012). Detection of blue screen special effects in videos International Conference on Medical Physics and Biomedical Engineering, 1316-1322.
Kaur, R., & Kaur, E. J. (2016). Video forgery detection using hybrid techniques. International Journal of Advanced Research in Computer and Communication Engineering, 5, 112-117.
Mary, G. J. J., & Begum, A. R. (2015). Edge detection using third order difference equation: a new dimension Communications on Applied Electronics (CAE), 1, 10-14.
Pandey, R. C., Singh, S. K., & Shukla, K. K. (2014). Passive copy- move forgery detection in videos International conference on computer and communication technology, 301-306.
Pandey, R. C., Singh, S. K., & Shukla, K. K. (2016). Passive forensics in image and video using noise features: A review. Digital Investigation, 1-28.
Saxena, S., Subramanyam, A. V., & Ravi, H. (2016). Video inpainting detection and localization using inconsistencies in optical flow. . IEEE Region 10 Conference.
Singh, R. D., & Aggarwal, N. (2017). Detection of upscale-crop and splicing for digital video authentication. Digital Investigation, 31-52. doi: doi: 10.1016/j.diin.2017.01.001
Singh, Raahat D., & Aggarwal, N. (2017). Video content authentication techniques: a comprehensive survey 1-30. doi: DOI 10.1007/s00530-017-0538-9
Wu, W., Jiang, X., Sun, T., & Wang, W. (2014). Exposing video inter-frame forgery based on velocity field consistency. International Conference on Acoustic, Speech and Signal Processing Assurance and Security (ICASSP), 2693-2697.
Published
How to Cite
Issue
Section
FUDMA Journal of Sciences