Zobrazeno 1 - 10
of 15
pro vyhledávání: '"Massinissa Hamidi"'
Autor:
Massinissa Hamidi, Aomar Osmani
Publikováno v:
Sensors, Vol 21, Iss 21, p 7278 (2021)
In this article, we study activity recognition in the context of sensor-rich environments. In these environments, many different constraints arise at various levels during the data generation process, such as the intrinsic characteristics of the sens
Externí odkaz:
https://doaj.org/article/4b5c84aed66443ad8494dd5dfe04e341
Publikováno v:
Proceedings of the AAAI Conference on Artificial Intelligence. 36:7904-7912
In a large domain of classification problems for real applications, like human activity recognition, separable spaces between groups of concepts are easier to learn than each concept alone. This is because the search space biases required to separate
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::dfbaba57b26da37be7438acc93fdf916
https://doi.org/10.1609/aaai.v36i7.20760
https://doi.org/10.1609/aaai.v36i7.20760
Autor:
Massinissa Hamidi, Aomar Osmani
Publikováno v:
Machine Learning and Knowledge Discovery in Databases ISBN: 9783031264085
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c20a0606477d8de4881f7496e65f9db4
https://doi.org/10.1007/978-3-031-26409-2_39
https://doi.org/10.1007/978-3-031-26409-2_39
Autor:
Massinissa Hamidi, Aomar Osmani
Publikováno v:
Neurocomputing. 444:244-259
The ever-increasing quantities of data generated by internet of things applications bring diverse and rich perspectives about monitored phenomena. This is the case, for example, of applications monitoring continuously human activities from wearable s
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::84925cd3efb0f49d76fcb94f0dbcfdf0
https://doi.org/10.1016/j.neucom.2020.06.138
https://doi.org/10.1016/j.neucom.2020.06.138
Publikováno v:
Proceedings of the AAAI Conference on Artificial Intelligence. 35:9251-9258
The synthesis of materials using the principle of thermogravimetric analysis to discover new anticorrosive paints requires several costly experiments. This paper presents an approach combining empirical data and domain analytical models to reduce the
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::069d6cc94c1ecfa58ea46cbc630d0710
https://doi.org/10.1609/aaai.v35i10.17116
https://doi.org/10.1609/aaai.v35i10.17116
Publikováno v:
2022 IEEE 9th International Conference on Computational Intelligence and Virtual Environments for Measurement Systems and Applications (CIVEMSA).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::4812b22377b776eb70ba48299e4ee15e
https://doi.org/10.1109/civemsa53371.2022.9853680
https://doi.org/10.1109/civemsa53371.2022.9853680
Autor:
Aomar Osmani, Massinissa Hamidi
Publikováno v:
Advances in Knowledge Discovery and Data Mining ISBN: 9783031059353
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1c822b44245901d9b02f039f3886c91e
https://doi.org/10.1007/978-3-031-05936-0_23
https://doi.org/10.1007/978-3-031-05936-0_23
Publikováno v:
Advances in Knowledge Discovery and Data Mining ISBN: 9783030757649
PAKDD (2)
PAKDD (2)
In multi-class classification tasks, like human activity recognition, it is often assumed that classes are separable. In real applications, this assumption becomes strong and generates inconsistencies. Besides, the most commonly used approach is to l
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a5f5d97b516c62e7e5028727cfce5bb4
https://doi.org/10.1007/978-3-030-75765-6_7
https://doi.org/10.1007/978-3-030-75765-6_7
Autor:
Aomar Osmani, Massinissa Hamidi
Publikováno v:
Machine Learning and Knowledge Discovery in Databases: Applied Data Science Track ISBN: 9783030676667
ECML/PKDD (4)
ECML/PKDD (4)
The dynamics of body movements are often driven by large and intricate low-level interactions involving various body parts. These dynamics are part of an underlying data generation process. Incorporating the data generation process into data-driven a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::fb60450207a7d9d2a40d3705cd84629e
https://doi.org/10.1007/978-3-030-67667-4_23
https://doi.org/10.1007/978-3-030-67667-4_23
Publikováno v:
UbiComp/ISWC Adjunct
To recognize locomotion and transportation modes in a user-independent manner with an unknown target phone position, we (team Eagles) propose an approach based on two main steps: reduction of the impact of regular effects that stem from each phone po
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7832ebecd96e7329f0177ff47059a216
https://doi.org/10.1145/3410530.3414351
https://doi.org/10.1145/3410530.3414351