Zobrazeno 1 - 10
of 19
pro vyhledávání: '"Majid Meghdadi"'
Publikováno v:
Multimedia Tools and Applications.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1d542a2a7e2552f3444ff666e6b8d4da
https://doi.org/10.1007/s11042-023-15021-9
https://doi.org/10.1007/s11042-023-15021-9
Autor:
Amir Khani Yengikand, Majid Meghdadi, Sajad Ahmadian, Seyed Mohammad Jafar Jalali, Abbas Khosravi, Saeid Nahavandi
Publikováno v:
2021 IEEE International Conference on Systems, Man, and Cybernetics (SMC).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::4af301427dfcd7718cdab63dd0519bb2
https://doi.org/10.1109/smc52423.2021.9658978
https://doi.org/10.1109/smc52423.2021.9658978
Publikováno v:
Multimedia Systems. 25:273-291
Scalable coding methods are widely considered as promising coding approaches for image/video transmission in heterogeneous environments. To copyright protection of scalable coded videos, scalable video watermarking was introduced which enables recons
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::9b907490b0b257d796df475d1eaeb6bf
https://doi.org/10.1007/s00530-019-00604-0
https://doi.org/10.1007/s00530-019-00604-0
Publikováno v:
Multimedia Tools and Applications. 78:17763-17798
Recommender systems are intelligent programs to suggest relevant contents to users according to their interests which are widely expressed as numerical ratings. Collaborative filtering is an important type of recommender systems which has established
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a32fac6e36b5a07c05e4dd6e52c4f836
https://doi.org/10.1007/s11042-018-7079-x
https://doi.org/10.1007/s11042-018-7079-x
Publikováno v:
Journal of Information Science. 45:607-642
Trust-aware recommender systems are advanced approaches which have been developed based on social information to provide relevant suggestions to users. These systems can alleviate cold start and data sparsity problems in recommendation methods throug
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e10bca9889aaea9af54536a47e9a4f2b
https://doi.org/10.1177/0165551518808191
https://doi.org/10.1177/0165551518808191
Publikováno v:
Multimedia Tools and Applications. 78:7097-7124
This paper proposes a novel human vision system based, spread spectrum method to scalable image watermarking. A scalable decomposition of the watermark is spread into the entire frequency sub-bands of the wavelet decomposed image. At each wavelet sub
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d0e72e0d7e160e6be9109e3720b4ede8
https://doi.org/10.1007/s11042-018-6419-1
https://doi.org/10.1007/s11042-018-6419-1
Publikováno v:
Information Processing & Management. 54:707-725
Recommender systems are techniques to make personalized recommendations of items to users. In e-commerce sites and online sharing communities, providing high quality recommendations is an important issue which can help the users to make effective dec
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::be689c5f8359479a688eaab3669632e5
https://doi.org/10.1016/j.ipm.2017.03.002
https://doi.org/10.1016/j.ipm.2017.03.002
Publikováno v:
Applied Intelligence. 48:4448-4469
Social recommendation systems use social relations (such as trust, friendship, etc.) among users to find preferences and provide relevant suggestions to users. Historical ratings of items provided by the users are also used to predict unseen items in
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::aa42c52462e927fc2c98c883ae3023ea
https://doi.org/10.1007/s10489-018-1219-x
https://doi.org/10.1007/s10489-018-1219-x
Publikováno v:
Knowledge-Based Systems. 192:105371
Recommender systems attempt to suggest information that is of potential interest to users helping them to quickly find information relevant to them. In addition to historical user–item interaction data, such as users’ ratings on items, social rec
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ba85b8855745367eeb53e61134b0d791
https://doi.org/10.1016/j.knosys.2019.105371
https://doi.org/10.1016/j.knosys.2019.105371
Publikováno v:
ASONAM
Recommender systems aim to suggest relevant items to users among a large number of available items. They have been successfully applied in various industries, such as e-commerce, education and digital health. On the other hand, clustering approaches
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::695180031e9e7ec49f9cbbceb03fd1c3
https://doi.org/10.1109/asonam.2018.8508723
https://doi.org/10.1109/asonam.2018.8508723