Téléchargement | - Voir le manuscrit accepté : Model fusion-based batch learning with application to oil spills detection (PDF, 253 Kio)
|
---|
DOI | Trouver le DOI : https://doi.org/10.1007/978-3-642-31087-4_5 |
---|
Auteur | Rechercher : Yang, Chunsheng1; Rechercher : Yang, Yubin; Rechercher : Liu, Jie |
---|
Affiliation | - Conseil national de recherches du Canada. Institut de technologie de l'information du CNRC
|
---|
Format | Texte, Chapitre de livre |
---|
Conférence | 25th International Conference on Industrial Engineering and Other Applications of Applied Intelligent Systems (IEA/AIE 2012), June 9-12, 2012, Dalian, China |
---|
Sujet | batch data; batch learning; transfer learning; content-based learning; model fusion; oil spill detection |
---|
Résumé | Data split into batches is very common in real-world applications. In speech recognition and handwriting identification, the batches are different people. In areas like oil spill detection and train wheel failure prediction, the batches are the particular circumstances when the readings were recorded. The recent research has proved that it is important to respect the batch structure when learning models for batched data. We believe that such a batch structure is also an opportunity that can be exploited in the learning process. In this paper, we investigated the novel method for dealing with the batched data. We applied the developed batch learning techniques to detect oil spills using radar images collected from satellite stations. This paper reports some progress on the proposed batch learning method and the preliminary results obtained from oil spills detection. |
---|
Date de publication | 2012-08-01 |
---|
Maison d’édition | Springer Berlin Heidelberg |
---|
Dans | |
---|
Série | |
---|
Langue | anglais |
---|
Publications évaluées par des pairs | Oui |
---|
Numéro NPARC | 21261868 |
---|
Exporter la notice | Exporter en format RIS |
---|
Signaler une correction | Signaler une correction (s'ouvre dans un nouvel onglet) |
---|
Identificateur de l’enregistrement | 88a95ade-a09f-4fd7-9ed3-0d651f2bfb75 |
---|
Enregistrement créé | 2013-03-11 |
---|
Enregistrement modifié | 2020-06-04 |
---|