The Receptive Field as a Regularizer in Deep Convolutional Neural Networks for Acoustic Scene Classification

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A. Mesaros, T. Heittola, and T. Virtanen, “TUT database for acoustic scene classification and sound event detection,” in Signal Processing Conference (EUSIPCO), 2016 24th European . IEEE, pp. 1128–1132

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B. Lehner, H. Eghbal-Zadeh, M. Dorfer, F. Korzeniowski, K. Koutini, and G. Widmer, “Classifying short acoustic scenes with I-vectors and CNNs: Challenges and optimisations for the 2017 DCASE ASC task.” DCASE2017 Challenge

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A. Mesaros, T. Heittola, A. Diment, B. Elizalde, A. Shah, E. Vincent, B. Raj, and T. Virtanen, “DCASE 2017 challenge setup: Tasks, datasets and baseline system,” in DCASE 2017-Workshop on Detection and Classification of Acoustic Scenes and Events

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M. Dorfer and G. Widmer, “Training general-purpose audio tagging networks with noisy labels and iterative self-verification,” in Proceedings of the Detection and Classification of Acoustic Scenes and Events 2018 Workshop (DCASE2018) , pp. 178–182

2018

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K. Koutini, H. Eghbal-zadeh, and G. Widmer, “Iterative knowledge distillation in R-CNNs for weakly-labeled semi-supervised sound event detection,” in Proceedings of the Detection and Classification of Acoustic Scenes and Events 2018 Workshop (DCASE2018) , pp. 173–177

2018

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A. Mesaros, T. Heittola, and T. Virtanen, “A multi-device dataset for urban acoustic scene classification,” in Proceedings of the Detection and Classification of Acoustic Scenes and Events 2018 Workshop (DCASE2018) , pp. 9–13

2018

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