Zobrazeno 1 - 10
of 637 558
pro vyhledávání: '"Artificial Intelligence & Image Processing"'
Publikováno v:
IEEE Transactions on Pattern Analysis and Machine Intelligence. 45:6605-6617
In this paper, we propose to tackle egocentric action recognition by suppressing background distractors and enhancing action-relevant interactions. The existing approaches usually utilize two independent branches to recognize egocentric actions, i.e.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7383afea7ffbe96a9a9cf8794fe34d27
https://doi.org/10.1109/tpami.2020.3015894
https://doi.org/10.1109/tpami.2020.3015894
Autor:
Kowerko, Danny
Die Publikationen dieses Tagungsbandes sind im Themenfeld Information Retrieval und künstliche Intelligenz einzuordnen. Die Beiträge wurden als wissenschaftlicher Workshop im Rahmen von Vorträgen auf den Chemnitzer Linux Tagen 2019 präsentiert. D
Autor:
Eric H. Frankel, JunYoung Gwak, Amir Sadeghian, Mihir Patel, Roberto Martín-Martín, Silvio Savarese, Hamid Rezatofighi, Abhijeet Shenoi
Publikováno v:
IEEE Transactions on Pattern Analysis and Machine Intelligence. 45:6748-6765
We present JRDB, a novel egocentric dataset collected from our social mobile manipulator JackRabbot. The dataset includes 64 minutes of annotated multimodal sensor data including stereo cylindrical 360$^\circ$ RGB video at 15 fps, 3D point clouds fro
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f4f992433785675106089116a50a26f9
https://doi.org/10.1109/tpami.2021.3070543
https://doi.org/10.1109/tpami.2021.3070543
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 Neural Networks and Learning Systems. 33:7667-7681
In unsupervised domain adaptation (UDA), a classifier for the target domain is trained with massive true-label data from the source domain and unlabeled data from the target domain. However, collecting fully-true-label data in the source domain is hi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::828dce0ba59db0b8f0e98f75c3a92e00
https://doi.org/10.1109/tnnls.2021.3086093
https://doi.org/10.1109/tnnls.2021.3086093
Publikováno v:
Cham, Switzerland : Springer, Lecture notes in computer science 12075, Theoretical Computer Science and General Issues 515-543 (2020). doi:10.1007/978-3-030-44914-8_19
Programming languages and systems : 29th European Symposium on Programming, ESOP 2020, held as part of the European joint conferences on theory and practice of software, ETAPS 2020, Dublin, Ireland, April 25-30, 2020: proceedings / Peter Müller (ed.)
Programming languages and systems : 29th European Symposium on Programming, ESOP 2020, held as part of the European joint conferences on theory and practice of software, ETAPS 2020, Dublin, Ireland, April 25-30, 2020: proceedings / Peter Müller (ed.)29. European Symposium on Programming, ESOP 2020, online, 2020-04-25-2020-04-30
Programming Languages and Systems ISBN: 9783030449131
ESOP
Programming Languages and Systems
Programming languages and systems : 29th European Symposium on Programming, ESOP 2020, held as part of the European joint conferences on theory and practice of software, ETAPS 2020, Dublin, Ireland, April 25-30, 2020: proceedings / Peter Müller (ed.)
Programming languages and systems : 29th European Symposium on Programming, ESOP 2020, held as part of the European joint conferences on theory and practice of software, ETAPS 2020, Dublin, Ireland, April 25-30, 2020: proceedings / Peter Müller (ed.)29. European Symposium on Programming, ESOP 2020, online, 2020-04-25-2020-04-30
Programming Languages and Systems ISBN: 9783030449131
ESOP
Programming Languages and Systems
We propose a novel logic, called Frame Logic (FL), that extends first-order logic (with recursive definitions) using a construct Sp(.) that captures the implicit supports of formulas -- the precise subset of the universe upon which their meaning depe
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3f7fc29d65b4ef458a48b506ab8c778e
https://doi.org/10.1145/3583057
https://doi.org/10.1145/3583057
Publikováno v:
Fuzzy Sets and Systems. 459:67-81
This paper focuses on the study of synchronization problem for T-S fuzzy memristive neural networks with time delay. First, a delay-independent nonlinear fuzzy control is designed. Second, under the designed fuzzy control, two kinds of finite-time sy
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::fbeb33df3a1ad7fe5d7c639bbfbecf93
https://doi.org/10.1016/j.fss.2022.10.013
https://doi.org/10.1016/j.fss.2022.10.013
Autor:
Michiel M. Spapé, A Antal Haans, Ville Johannes Harjunen, Sima Ipakchian Askari, WA Wijnand IJsselsteijn, Niklas Ravaja
Publikováno v:
IEEE Transactions on Affective Computing, 14(2), 1044-1055. Institute of Electrical and Electronics Engineers
Social touch is essential to human development and communication. Mediated social touch is suggested as a solution for circumstances where distance prevents skin-to-skin contact. However, past research aimed at demonstrating efficacy of mediated touc
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a06b9cc2212fd0724be5931bf31139da
https://doi.org/10.1109/taffc.2021.3085185
https://doi.org/10.1109/taffc.2021.3085185
Publikováno v:
IEEE Transactions on Neural Networks and Learning Systems. 34:1720-1731
In this article, we investigate the problem of social link inference in a target location-aware social network (LSN), which aims at predicting the unobserved links between users within the network. This problem is critical for downstream applications
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7930b14498e4df6afa71c059a61ebddd
https://doi.org/10.1109/tnnls.2020.2986472
https://doi.org/10.1109/tnnls.2020.2986472
Publikováno v:
IEEE Transactions on Neural Networks and Learning Systems. 34:1681-1691
Temporal point process is widely used for sequential data modeling. In this paper, we focus on the problem of modeling sequential event propagation in graph, such as retweeting by social network users, news transmitting between websites, etc. Given a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7eee5309c70373d9d9d04879d19e9774
https://doi.org/10.1109/tnnls.2020.3004626
https://doi.org/10.1109/tnnls.2020.3004626