Machine Learning
EURASIP Journal on Applied Signal Processing
Intelligent Music Information Systems: Tools and Methodologies
Intelligent Music Information Systems: Tools and Methodologies
Musical Instruments in Random Forest
ISMIS '09 Proceedings of the 18th International Symposium on Foundations of Intelligent Systems
Fast Keypoint Recognition Using Random Ferns
IEEE Transactions on Pattern Analysis and Machine Intelligence
Real-Time Detection and Tracking for Augmented Reality on Mobile Phones
IEEE Transactions on Visualization and Computer Graphics
Advances in Music Information Retrieval
Advances in Music Information Retrieval
Random musical bands playing in random forests
RSCTC'10 Proceedings of the 7th international conference on Rough sets and current trends in computing
All that jazz in the random forest
ISMIS'11 Proceedings of the 19th international conference on Foundations of intelligent systems
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In this paper, we first apply random ferns for classification of real music recordings of a jazz band. No initial segmentation of audio data is assumed, i.e., no onset, offset, nor pitch data are needed. The notion of random ferns is described in the paper, to familiarize the reader with this classification algorithm, which was introduced quite recently and applied so far in image recognition tasks. The performance of random ferns is compared with random forests for the same data. The results of experiments are presented in the paper, and conclusions are drawn.