| Psychology meets machine learning: Interdisciplinary perspectives on algorithmic job candidate screening CCS Liem, M Langer, A Demetriou, AMF Hiemstra, A Sukma Wicaksana, ... Explainable and interpretable models in computer vision and machine learning …, 2018 | 152* | 2018 |
| Modeling, recognizing, and explaining apparent personality from videos HJ Escalante, H Kaya, AA Salah, S Escalera, Y Güçlütürk, U Güçlü, ... IEEE Transactions on Affective Computing 13 (2), 894-911, 2020 | 149 | 2020 |
| One deep music representation to rule them all? A comparative analysis of different representation learning strategies J Kim, J Urbano, CCS Liem, A Hanjalic Neural Computing and Applications 32 (4), 1067-1093, 2020 | 73 | 2020 |
| The need for music information retrieval with user-centered and multimodal strategies CCS Liem, M Müller, D Eck, G Tzanetakis, A Hanjalic Proceedings of the 1st international ACM workshop on Music information …, 2011 | 73 | 2011 |
| Detecting drops in electronic dance music: Content-based approaches to a socially significant music event K Yadati, MA Larson, CCS Liem, A Hanjalic Proceedings of the 15th International Society for Music Information …, 2014 | 40 | 2014 |
| A professionally annotated and enriched multimodal data set on popular music M Schedl, N Orio, CCS Liem, G Peeters Proceedings of the 4th ACM Multimedia Systems Conference, 78-83, 2013 | 35 | 2013 |
| Phenicx: Performances as highly enriched and interactive concert experiences E Gómez, M Grachten, A Hanjalic, J Janer, S Jorda, CF Julia, C Liem, ... SMAC/SMC, 2013 | 27 | 2013 |
| The influence of personal values on music taste: towards value-based music recommendations S Manolios, A Hanjalic, CCS Liem Proceedings of the 13th ACM Conference on Recommender Systems, 501-505, 2019 | 26 | 2019 |
| Transfer learning of artist group factors to musical genre classification J Kim, M Won, X Serra, CCS Liem Companion Proceedings of the The Web Conference 2018, 1929-1934, 2018 | 26 | 2018 |
| Audiovisual analysis of music performances: Overview of an emerging field Z Duan, S Essid, CCS Liem, G Richard, G Sharma IEEE Signal Processing Magazine 36 (1), 63-73, 2018 | 25 | 2018 |
| Social inclusion in curated contexts: Insights from museum practices HY Huang, CCS Liem Proceedings of the 2022 ACM Conference on Fairness, Accountability, and …, 2022 | 24 | 2022 |
| Interweaving and enriching digital music collections for scholarship, performance, and enjoyment D M. Weigl, W Goebl, T Crawford, A Gkiokas, N F. Gutierrez, A Porter, ... Proceedings of the 6th International Conference on Digital Libraries for …, 2019 | 24 | 2019 |
| PHENICX: Innovating the classical music experience CCS Liem, E Gómez, M Schedl 2015 IEEE International Conference on Multimedia & Expo Workshops (ICMEW), 1-4, 2015 | 24 | 2015 |
| User-aware music retrieval M Schedl, S Stober, E Gómez, N Orio, C Liem Dagstuhl Follow-Ups 3, 2012 | 24 | 2012 |
| Some advice for psychologists who want to work with computer scientists on big data C J König, A M Demetriou, P Glock, A Hiemstra, D Iliescu, C Ionescu, ... Personnel Assessment and Decisions 6 (1), 17-23, 2020 | 22 | 2020 |
| Sequences of diverse song recommendations: an exploratory study in a commercial system N Tintarev, C Lofi, CCS Liem Proceedings of the 25th Conference on User Modeling, Adaptation and …, 2017 | 22 | 2017 |
| When music makes a scene: Characterizing music in multimedia contexts via user scene descriptions CCS Liem, M Larson, A Hanjalic International Journal of Multimedia Information Retrieval 2, 15-30, 2013 | 22 | 2013 |
| ReproducedPapers. org: Openly teaching and structuring machine learning reproducibility B Yildiz, H Hung, JH Krijthe, CCS Liem, M Loog, G Migut, FA Oliehoek, ... International Workshop on Reproducible Research in Pattern Recognition, 3-11, 2021 | 20 | 2021 |
| Put the Concert Attendee in the Spotlight. A User-Centered Design and Development approach for Classical Concert Applications MS Melenhorst, CCS Liem Proceedings of the 16th Conference of the International Society for Music …, 2015 | 20 | 2015 |
| Expressive Timing from Cross-Performance and Audio-based Alignment Patterns: An Extended Case Study. CCS Liem, A Hanjalic ISMIR, 519-524, 2011 | 20 | 2011 |
Alan HanjalicProfessor of Computer Science, IEEE Fellow, Delft University of Technology, The NetherlandsVerified email at tudelft.nl
