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Ong, B. (2007).  Structural Analysis and Segmentation of Music Signals. Department of Information and Communication Technologies. Abstract
Oramas, S., Nieto O., Barbieri F., & Serra X. (2017).  Multi-label Music Genre Classification from Audio, Text and Images Using Deep Features. 18th International Society for Music Information Retrieval Conference (ISMIR 2017). Abstract
Oramas, S., Barbieri F., Nieto O., & Serra X. (2018).  Multimodal Deep Learning for Music Genre Classification. Transactions of the International Society for Music Information Retrieval. 1(1), 4-21. Abstract
Oramas, S., Nieto O., Sordo M., & Serra X. (2017).  A Deep Multimodal Approach for Cold-start Music Recommendation. 2nd Workshop on Deep Learning for Recommender Systems, at RecSys 2017. Abstract
Oramas, S., Espinosa-Anke L., Lawlor A., Serra X., & Saggion H. (2016).  Exploring Customer Reviews for Music Genre Classification and Evolutionary Studies. 17th International Society for Music Information Retrieval Conference (ISMIR 2016). 150-156. Abstract
Oramas, S., Ostuni V. C., Di Noia T., Serra X., & Di Sciascio E. (2016).  Sound and Music Recommendation with Knowledge Graphs. ACM Transactions on Intelligent Systems and Technology (TIST). 8(2), 1-21. Abstract
Oramas, S., Sordo M., Espinosa-Anke L., & Serra X. (2015).  A Semantic-based Approach for Artist Similarity. 16th International Society for Music Information Retrieval Conference. 100-106. Abstract
Pons, J., & Serra X. (2017).  Designing Efficient Architectures for Modeling Temporal Features with Convolutional Neural Networks. 42th International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2017) . Abstract
Pons, J., & Serra X. (2019).  Randomly weighted CNNs for (music) audio classification. 44th IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP2019). Abstract
Pons, J., Lidy T., & Serra X. (2016).  Experimenting with Musically Motivated Convolutional Neural Networks. 14th International Workshop on Content-based Multimedia Indexing (CBMI 2016). Abstract