Zobrazeno 1 - 10
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pro vyhledávání: '"Abstract data type"'
Publikováno v:
IEEE Transactions on Pattern Analysis and Machine Intelligence. 45:6969-6983
The task of multi-label image recognition is to predict a set of object labels that present in an image. As objects normally co-occur in an image, it is desirable to model label dependencies to improve recognition performance. To capture and explore
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ff3cb0bda510d3337a2b514dda3d2ea9
https://doi.org/10.1109/tpami.2021.3063496
https://doi.org/10.1109/tpami.2021.3063496
Akademický článek
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Autor:
Guorong Wu, Minjeong Kim, Paul J. Laurienti, Chenggang Yan, Defu Yang, Jiazhou Chen, Martin Styner
Publikováno v:
IEEE transactions on pattern analysis and machine intelligence. 44(11)
Human brain is a complex yet economically organized system, where a small portion of critical hub regions support the majority of brain functions. The identification of common hub nodes in a population of networks is often simplified as a voting proc
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c4c5cbd2b62ce2787451f52d57024770
https://pubmed.ncbi.nlm.nih.gov/34010126
https://pubmed.ncbi.nlm.nih.gov/34010126
Autor:
Saurabh Kumar, Pradeep Kumar
Publikováno v:
IEEE Transactions on Engineering Management. 70:2071-2079
Privacy concerns of users threaten the usage of online social networks (OSN). In this regard, privacy preserving of OSN emerged as a convincing solution for preserving the privacy of users and uncovering useful insights from the social network data.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6f6a4525e0c6506a6e861af18194ebf2
https://doi.org/10.1109/tem.2021.3072812
https://doi.org/10.1109/tem.2021.3072812
Publikováno v:
IEEE Transactions on Pattern Analysis and Machine Intelligence. 45:7035-7049
In this work, we consider transferring the structure information from large networks to compact ones for dense prediction tasks in computer vision. Previous knowledge distillation strategies used for dense prediction tasks often directly borrow the d
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2d7fd83ae6c8f16646101dd7a076bbf0
https://doi.org/10.1109/tpami.2020.3001940
https://doi.org/10.1109/tpami.2020.3001940
Publikováno v:
IEEE Transactions on Engineering Management. 70:1900-1911
In this article, we present an extended data-fitting model which involves different and conflicting criteria, and we propose an algorithm based on a scalarization technique to solve it. Our model integrates in a unique framework three different crite
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f6fe61ac8a7e422aa49c87fb202513d2
https://doi.org/10.1109/tem.2021.3078831
https://doi.org/10.1109/tem.2021.3078831
Autor:
Vicente Liern, Blanca Pérez-Gladish
Publikováno v:
IEEE Transactions on Engineering Management. 70:1871-1880
Composite indicators have been widely used in a large number of fields, including innovation and entrepreneurship as a useful tool for conveying summary information about overall performance in a relatively simple way. The construction of composite i
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7268474762618c9fd565f131bbd90c41
https://doi.org/10.1109/tem.2021.3090155
https://doi.org/10.1109/tem.2021.3090155
Autor:
Dino Vlahek, Domen Mongus
Publikováno v:
IEEE Transactions on Neural Networks and Learning Systems. 34:2606-2618
This article introduces a new iterative approach to explainable feature learning. During each iteration, new features are generated, first by applying arithmetic operations on the input set of features. These are then evaluated in terms of probabilit
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d8d6e803fe54e8287706f15ca9b32d09
https://doi.org/10.1109/tnnls.2021.3107049
https://doi.org/10.1109/tnnls.2021.3107049
Autor:
Zhongjie Zhang, Jian Huang
Publikováno v:
IEEE Transactions on Cybernetics. 53:2993-3006
Sampling from large dataset is commonly used in the frequent patterns (FPs) mining. To tightly and theoretically guarantee the quality of the FPs obtained from samples, current methods theoretically stabilize the supports of all the patterns in rando
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b47ac0ea7508e7a345949293d39f683c
https://doi.org/10.1109/tcyb.2021.3125196
https://doi.org/10.1109/tcyb.2021.3125196
Publikováno v:
IEEE Transactions on Neural Networks and Learning Systems. 34:2693-2700
In this brief, stabilization of Boolean networks (BNs) by flipping a subset of nodes is considered, here we call such action state-flipped control. The state-flipped control implies that the logical variables of certain nodes are flipped from 1 to 0
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8b0f264c0418e12d3b08a96298757734
https://doi.org/10.1109/tnnls.2021.3106918
https://doi.org/10.1109/tnnls.2021.3106918