Zobrazeno 1 - 10
of 13
pro vyhledávání: '"Amine Chemchem"'
Publikováno v:
Applied Intelligence
Applied Intelligence, Springer Verlag (Germany), In press
HAL
Applied Intelligence, Springer Verlag (Germany), In press
HAL
International audience; THIS IS A PREPRINT for Applied Intelligence. The revised version is available here: https://link.springer.com/article/10.1007/s10489-021-02359-6This paper examines multiple CNN-based (Convolutional Neural Network) models for C
Autor:
Marine Rondeau, Lucas Mohimont, François Alin, Mathias Roesler, Nathalie Gaveau, Amine Chemchem, Luiz Angelo Steffenel
Publikováno v:
Revue Ouverte d'Intelligence Artificielle
Revue Ouverte d'Intelligence Artificielle, 2021, 2 (1), pp.33-63. ⟨10.5802/roia.9⟩
Revue ouverte d'intelligence artificielle
Revue ouverte d'intelligence artificielle, 2021, 2 (1), pp.33-63. ⟨10.5802/roia.9⟩
Revue Ouverte d'Intelligence Artificielle, 2021, 2 (1), pp.33-63. ⟨10.5802/roia.9⟩
Revue ouverte d'intelligence artificielle
Revue ouverte d'intelligence artificielle, 2021, 2 (1), pp.33-63. ⟨10.5802/roia.9⟩
National audience
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c42ecca8a27ffdba79e49b184a135d98
https://hal.univ-reims.fr/hal-03437912
https://hal.univ-reims.fr/hal-03437912
Publikováno v:
AIKE
International Conference on Artificial Intelligence and Knowledge Engineering (AIKE)
International Conference on Artificial Intelligence and Knowledge Engineering (AIKE), 2019, Cagliari, Italy. ⟨10.1109/AIKE.2019.00010⟩
International Conference on Artificial Intelligence and Knowledge Engineering (AIKE)
International Conference on Artificial Intelligence and Knowledge Engineering (AIKE), 2019, Cagliari, Italy. ⟨10.1109/AIKE.2019.00010⟩
International audience; This paper describes a method of predicting wheat yields based on machine learning, which accurately determines the value of wheat yield losses in France. Obtaining reliable value from yield losses is difficult because we are
Publikováno v:
Machine Learning for Networking Second IFIP TC 6 International Conference, MLN 2019, Paris, France, December 3–5, 2019, Revised Selected Papers
International Conference on Machine Learning for Networking (MLN)
International Conference on Machine Learning for Networking (MLN), 2019, Paris, France. ⟨10.1007/978-3-030-45778-5_2⟩
Machine Learning for Networking ISBN: 9783030457778
MLN
International Conference on Machine Learning for Networking (MLN)
International Conference on Machine Learning for Networking (MLN), 2019, Paris, France. ⟨10.1007/978-3-030-45778-5_2⟩
Machine Learning for Networking ISBN: 9783030457778
MLN
International audience; Nowadays, it is almost impossible to imagine our daily life without Internet. This strong dependence requires an effective and rigorous consideration of all the risks related to computer attacks. However traditional methods of
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0fe2beb779d800206383f22ce8a2c349
https://hal.archives-ouvertes.fr/hal-02560294/document
https://hal.archives-ouvertes.fr/hal-02560294/document
Publikováno v:
International Journal of Computational Intelligence and Applications
International Journal of Computational Intelligence and Applications, World Scientific Publishing, 2019, 18 (01), pp.1950005. ⟨10.1142/S1469026819500056⟩
International Journal of Computational Intelligence and Applications, World Scientific Publishing, 2019, 18 (01), pp.1950005. ⟨10.1142/S1469026819500056⟩
International audience; In this paper, a new idea is developed for improving the agent intelligence. In fact with the presented convolutional neural network (CNN) approach for knowledge classification, the agent will be able to manage its knowledge.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::83866f77aaf0f1c8b992263e5b8ded18
https://hal.archives-ouvertes.fr/hal-02528707/file/RevisedManuscript_A-Chemchem.pdf
https://hal.archives-ouvertes.fr/hal-02528707/file/RevisedManuscript_A-Chemchem.pdf
Publikováno v:
International Conference on Future Internet of Things and Cloud Workshops (FiCloudW)
International Conference on Future Internet of Things and Cloud Workshops (FiCloudW), 2018, Barcelone, Spain. ⟨10.1109/W-FiCloud.2018.00009⟩
2018 6th International Conference on Future Internet of Things and Cloud Workshops (FiCloudW)
2018 6th International Conference on Future Internet of Things and Cloud Workshops (FiCloudW), Aug 2018, Barcelona, France. pp.13-20
FiCloud Workshops
International Conference on Future Internet of Things and Cloud Workshops (FiCloudW), 2018, Barcelone, Spain. ⟨10.1109/W-FiCloud.2018.00009⟩
2018 6th International Conference on Future Internet of Things and Cloud Workshops (FiCloudW)
2018 6th International Conference on Future Internet of Things and Cloud Workshops (FiCloudW), Aug 2018, Barcelona, France. pp.13-20
FiCloud Workshops
International audience; Over the last few years, machine learning and data mining methods (MLDM) are constantly evolving, in order to accelerate the process of knowledge discovery from data (KDD). Today's challenge is to select only the most relevant
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::15619d7721b11afd6cc8eeea7955b38f
https://hal.archives-ouvertes.fr/hal-02528705/file/2018_FICLOUD_IEEE.pdf
https://hal.archives-ouvertes.fr/hal-02528705/file/2018_FICLOUD_IEEE.pdf
Autor:
Amine Chemchem, Habiba Drias
Publikováno v:
Expert Systems with Applications. 42:1436-1445
We extend the concept of classification and clustering to deal with induction rules.We present a new mathematical preliminaries for induction rules mining.Prove mathematically all of the presented preliminaries.The study of induction rules mining rea
Publikováno v:
International Journal of Systems and Service-Oriented Engineering. 4:1-25
The tremendous size of data in nowadays world web invokes many data mining techniques. The recent emergence of some new data mining techniques provide also many interesting induction rules. So, it's important to process these induction rules in order
Publikováno v:
NaBIC
The current world wide web is featured by big volumes of data. The classical association rules mining algorithms dealt with data sets somehow in an efficient way and in reasonable time. However they are not capable to cope with a huge amount of data
Publikováno v:
2013 8th International Workshop on Systems, Signal Processing and their Applications (WoSSPA).
The current world wide web is featured by a huge volume of knowledge, making it possible to apply knowledge mining to extract meta-knowledge. This paper explores this possibility and considers knowledge discovery process acceleration. Given that know