Zobrazeno 1 - 10
of 114
pro vyhledávání: '"Maria Luisa Sapino"'
Publikováno v:
Data Science and Engineering, Vol 8, Iss 3, Pp 221-222 (2023)
Externí odkaz:
https://doaj.org/article/2beba21566724c32b5bce468df629968
Publikováno v:
Applied Sciences, Vol 11, Iss 22, p 10873 (2021)
A common challenge in multimedia data understanding is the unsupervised discovery of recurring patterns, or motifs, in time series data. The discovery of motifs in uni-variate time series is a well studied problem and, while being a relatively new ar
Externí odkaz:
https://doaj.org/article/cd46d70fe10047799b56921f16ec57a6
Autor:
K. Selçuk Candan, Maria Luisa Sapino
Multimedia data require specialised management techniques because the representations of colour, time, semantic concepts, and other underlying information can be drastically different from one another. This textbook on multimedia data management tech
Publikováno v:
IEEE Transactions on Knowledge and Data Engineering. 35:4267-4280
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::345f7429e89522c2312b671337404dd7
https://doi.org/10.1109/tkde.2021.3135715
https://doi.org/10.1109/tkde.2021.3135715
Autor:
Hans Walter Behrens, Xilun Chen, Sicong Liu, Maria Luisa Sapino, Mao-Lin Li, Magesh Vijayakumaren, Dalton Turner, Xinsheng Li, K. Selçuk Candan, Shadab, Yash Garg
Urban systems are characterized by complexity and dynamicity. Data-driven simulations represent a promising approach in understanding and predicting complex dynamic processes in the presence of shifting demands of urban systems. Yet, today’s silo-b
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::80ca23e95a1cdb3df2ef3f3bbfe73438
http://hdl.handle.net/2318/1830235
http://hdl.handle.net/2318/1830235
Autor:
Xin Wang, Maria Luisa Sapino, Wook-Shin Han, Amr El Abbadi, Gill Dobbie, Zhiyong Feng, Yingxiao Shao, Hongzhi Yin
The four-volume set LNCS 13943, 13944, 13945 and 13946 constitutes the proceedings of the 28th International Conference on Database Systems for Advanced Applications, DASFAA 2023, held in April 2023 in Tianjin, China.The total of 125 full papers, alo
Publikováno v:
SMDS
With the increasing availability of sensory data, inferring the existence of relevant events in the observations is becoming a critical task for smart data service delivery in applications that rely on such data sources. Yet, existing solutions tend
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::50394fc1a1a645b316cdf543dcc44119
https://doi.org/10.1109/smds49396.2020.00014
https://doi.org/10.1109/smds49396.2020.00014
Publikováno v:
ICDE
With many applications relying on multi-dimensional datasets for decision making, matrix factorization (or decomposition) is becoming the basis for many knowledge discoveries and machine learning tasks, from clustering, trend detection, anomaly detec
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::114de774047dc52c9e9266b3086d66ce
https://doi.org/10.1109/icde48307.2020.00240
https://doi.org/10.1109/icde48307.2020.00240
Publikováno v:
Similarity Search and Applications ISBN: 9783030609351
SISAP
SISAP
The demand for searching, querying multimedia data such as image, video and audio is omnipresent, how to effectively access data for various applications is a critical task. Nevertheless, these data usually are encoded as multi-dimensional arrays, or
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::79ba5bbc8ca80449f9da0b3d5c9376b1
https://doi.org/10.1007/978-3-030-60936-8_15
https://doi.org/10.1007/978-3-030-60936-8_15