Machine learning techniques for atmospheric pollutant monitoring

Reference : Machine learning techniques for atmospheric pollutant monitoring


	Document type :	Scientific congresses, symposiums and conference proceedings : Poster
	Discipline(s) :	Engineering, computing & technology : Multidisciplinary, general & others
	To cite this reference:	http://hdl.handle.net/10993/16306

Title :	Machine learning techniques for atmospheric pollutant monitoring
Language :	English
Author, co-author :	Sainlez, Matthieu [University of Luxembourg > Luxembourg Centre for Systems Biomedicine (LCSB) > >]
	Heyen, Georges []
Publication date :	27-Jan-2012
Number of pages :	A0
Peer reviewed :	No
On invitation :	Yes
Audience :	National
Event name :	PhD day ENVITAM-GEPROC
Event date :	27 janvier 2012
Event organizer :	ENVITAM Graduate School and GEPROC Graduate School
Event place (city) :	Gembloux
Event country :	Belgium
Target :	Researchers
Permalink :	http://hdl.handle.net/10993/16306

File(s) associated to this reference

Fulltext file(s):

	File	Commentary	Version	Size	Access
Limited access	Poster_PHDday.pdf		Author postprint	3.96 MB	Request a copy

All documents in ORBi^lu are protected by a user license.