Zobrazeno 1 - 10
of 31
pro vyhledávání: '"Samira Pouyanfar"'
Autor:
Steven Luis, Yudong Tao, S. Sitharama Iyengar, Alonso Miguel, Maria Presa-Reyes, Tianyi Wang, Samira Pouyanfar, Mei-Ling Shyu, Haiman Tian, Shu-Ching Chen
Publikováno v:
ACM Computing Surveys. 54:1-35
From the start, the airline industry has remarkably connected countries all over the world through rapid long-distance transportation, helping people overcome geographic barriers. Consequently, this has ushered in substantial economic growth, both na
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c0afaf48d4cc0b29168fa6f327ba1d29
https://doi.org/10.1145/3469028
https://doi.org/10.1145/3469028
Autor:
Samira Pouyanfar, Azadeh Jaberi Jahromi, Atorod Azizinamini, Alireza Valikhani, Islam M. Mantawy
Publikováno v:
Computer-Aided Civil and Infrastructure Engineering. 36:213-226
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::85207f523af25102bf787d4807a55c37
https://doi.org/10.1111/mice.12605
https://doi.org/10.1111/mice.12605
Publikováno v:
Computers, Materials & Continua. 62:731-746
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::49a620a5d57787b480c485f4baf5bb92
https://doi.org/10.32604/cmc.2020.06508
https://doi.org/10.32604/cmc.2020.06508
Publikováno v:
2020 ASEE Virtual Annual Conference Content Access Proceedings.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::aec8e858b0ce11f27aaaab76eeaf99a0
https://doi.org/10.18260/1-2--34921
https://doi.org/10.18260/1-2--34921
Autor:
S. Sitharama Iyengar, Shu-Ching Chen, Haiman Tian, Yudong Tao, Samira Pouyanfar, Maria Presa Reyes, Yilin Yan, Saad Sadiq, Mei-Ling Shyu
Publikováno v:
ACM Computing Surveys. 51:1-36
The field of machine learning is witnessing its golden era as deep learning slowly becomes the leader in this domain. Deep learning uses multiple layers to represent the abstractions of data to build computational models. Some key enabler deep learni
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::60e31831b1e6b62ff0295b2351dbc000
https://doi.org/10.1145/3234150
https://doi.org/10.1145/3234150
Publikováno v:
World Wide Web. 22:1893-1911
The fast and explosive growth of digital data in social media and World Wide Web has led to numerous opportunities and research activities in multimedia big data. Among them, disaster management applications have attracted a lot of attention in recen
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b7b89dccb0778fc1f1dba32ece397ba4
https://doi.org/10.1007/s11280-018-0636-4
https://doi.org/10.1007/s11280-018-0636-4
Publikováno v:
World Wide Web. 22:1325-1341
Real-world applications usually encounter data with various modalities, each containing valuable information. To enhance these applications, it is essential to effectively analyze all information extracted from different data modalities, while most e
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::5f868d5749ceaebbed0fc19f686d8649
https://doi.org/10.1007/s11280-018-0548-3
https://doi.org/10.1007/s11280-018-0548-3
Publikováno v:
IEEE Transactions on Multimedia. 20:1024-1032
Multimedia concept detection is a challenging topic due to the well-known class imbalance issue, where the data instances are distributed unevenly across different classes. This problem becomes even more prominent when the minority class that contain
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::cdb7df2a0fa5c06979a7ce560468f7e8
https://doi.org/10.1109/tmm.2017.2760623
https://doi.org/10.1109/tmm.2017.2760623
Publikováno v:
ACM Computing Surveys. 51:1-34
With the proliferation of online services and mobile technologies, the world has stepped into a multimedia big data era. A vast amount of research work has been done in the multimedia area, targeting different aspects of big data analytics, such as t
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ed2d188b86522bb8e55668c3f9de1fc5
https://doi.org/10.1145/3150226
https://doi.org/10.1145/3150226