Ghent University Academic Bibliography

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Semi-supervised constrained clustering : an in-depth overview, ranked taxonomy and future research directions

German Gonzalez-Almagro, Daniel Peralta (UGent) , Eli De Poorter (UGent) , Jose-Ramon Cano and Salvador Garcia

(2025) ARTIFICIAL INTELLIGENCE REVIEW. 58(5).
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Fast field strength prediction using modern machine learning in European cities from few RF-EMF measurements : a neural tangent kernel perspective

Mohammed Mallik, Jorn Schampheleer (UGent) , Laurent Clavier and Margot Deruyck (UGent)

(2025) IEEE ACCESS. 13. p.131003-131014
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A semi-supervised anomaly detection approach for detecting mechanical failures

Colin Soete (UGent) , Michaël Rademaker (UGent) and Sofie Van Hoecke (UGent)

(2024) AI EDAM-ARTIFICIAL INTELLIGENCE FOR ENGINEERING DESIGN ANALYSIS AND MANUFACTURING. 38.
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Active selection of classification features

Thomas Kok (UGent) , R. M. Brouwer, R. M. Mandl, H. G. Schnack and G. Krempl

(2021) Advances in Intelligent Data Analysis XIX, 19th International Symposium on Intelligent Data Analysis, IDA 2021, Proceedings. In Lecture notes in computer science 12695. p.184-195
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Expert-driven trace clustering with instance-level constraints

Pieter De Koninck, Klaas Nelissen, Seppe vanden Broucke (UGent) , Bart Baesens, Monique Snoeck and Jochen De Weerdt

(2021) KNOWLEDGE AND INFORMATION SYSTEMS. 63(5). p.1197-1220
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Curriculum deep reinforcement learning with different exploration strategies : a feasibility study on cardiac landmark detection

Patricio Astudillo, Peter Mortier, Matthieu De Beule and Francis wyffels (UGent)

(2020) PROCEEDINGS OF THE 13TH INTERNATIONAL JOINT CONFERENCE ON BIOMEDICAL ENGINEERING SYSTEMS AND TECHNOLOGIES, VOL 2: BIOIMAGING. p.37-45
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Data augmentation and semi-supervised learning for deep neural networks-based text classifier

Heereen Shim, Stijn Luca (UGent) , Dietwig Lowet and Bart Vanrumste

(2020) Proceedings of the 35th Annual ACM Symposium on Applied Computing (SAC'20). p.1119-1126
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A semi-supervised learning approach towards automatic wireless technology recognition

Miguel Camelo, Adnan Shahid (UGent) , Jaron Fontaine (UGent) , Felipe Augusto Pereira de Figueiredo, Eli De Poorter (UGent) , Ingrid Moerman (UGent) and Steven Latré (UGent)

(2019) 2019 IEEE INTERNATIONAL SYMPOSIUM ON DYNAMIC SPECTRUM ACCESS NETWORKS (DYSPAN). p.420-429
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Knowledge base population using semantic label propagation

Lucas Sterckx (UGent) , Thomas Demeester (UGent) , Johannes Deleu (UGent) and Chris Develder (UGent)

(2016) KNOWLEDGE-BASED SYSTEMS. 108. p.79-91
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Semi-supervised fuzzy-rough feature selection

Richard Jensen, Sarah Vluymans (UGent) , Neil Mac Parthaláin, Chris Cornelis (UGent) and Yvan Saeys (UGent)

(2015) Lecture Notes in Artificial Intelligence. 9437. p.185-195

Academic Bibliography

Semi-supervised constrained clustering : an in-depth overview, ranked taxonomy and future research directions

Fast field strength prediction using modern machine learning in European cities from few RF-EMF measurements : a neural tangent kernel perspective

A semi-supervised anomaly detection approach for detecting mechanical failures

Active selection of classification features

Expert-driven trace clustering with instance-level constraints

Curriculum deep reinforcement learning with different exploration strategies : a feasibility study on cardiac landmark detection

Data augmentation and semi-supervised learning for deep neural networks-based text classifier

A semi-supervised learning approach towards automatic wireless technology recognition

Knowledge base population using semantic label propagation

Semi-supervised fuzzy-rough feature selection

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