Paper published in a book (Scientific congresses and symposiums)
Advancing MOSFET Fault Type Detection Through Data-Driven Unsupervised Learning
Alfaham, Abdallah; Kocak, Murat; Elmaz, Furkan et al.
2025In Advancing MOSFET Fault Type Detection Through Data-Driven Unsupervised Learning
Peer reviewed
 

Files


Full Text
MOSFET - final version.pdf
Author postprint (1.58 MB)
Request a copy

All documents in ORBi are protected by a user license.

Send to



Details



Disciplines :
Computer science
Author, co-author :
Alfaham, Abdallah ;  Université de Liège - ULiège > Montefiore Institute of Electrical Engineering and Computer Science ; University of Antwerp-imec IDLab,Faculty of Applied Engineering,Antwerp,Belgium
Kocak, Murat;  KU Leuven,Dept. Computer Science,Leuven,Belgium
Elmaz, Furkan;  University of Antwerp-imec IDLab,Faculty of Applied Engineering,Antwerp,Belgium
Mitard, Jerome;  imec,Leuven,Belgium
Vanderschrick, Joris;  imec,Leuven,Belgium
Mets, Kevin;  University of Antwerp-imec IDLab,Faculty of Applied Engineering,Antwerp,Belgium
Mercelis, Siegfried;  University of Antwerp-imec IDLab,Faculty of Applied Engineering,Antwerp,Belgium
Language :
English
Title :
Advancing MOSFET Fault Type Detection Through Data-Driven Unsupervised Learning
Publication date :
14 October 2025
Event name :
IEEE IECON – 51st Annual Conference of the IEEE Industrial Electronics Society
Event place :
Madrid, Spain
Event date :
14-17 October 2025
By request :
Yes
Audience :
International
Main work title :
Advancing MOSFET Fault Type Detection Through Data-Driven Unsupervised Learning
Publisher :
Institute of Electrical and Electronics Engineers (IEEE), Madrid, Unknown/unspecified
Peer review/Selection committee :
Peer reviewed
Available on ORBi :
since 13 November 2025

Statistics


Number of views
22 (4 by ULiège)
Number of downloads
0 (0 by ULiège)

Scopus citations®
 
0
Scopus citations®
without self-citations
0
OpenCitations
 
0
OpenAlex citations
 
0

Bibliography


Similar publications



Contact ORBi