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Marcus Windmark

Publications and source records attributed to Marcus Windmark.

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Static Gesture Recognition using Leap Motion

In this report, an automated bartender system was developed for making orders in a bar using hand gestures. The gesture recognition of the system was developed using Machine Learning techniques, where the model was trained to classify gestures using collected data. The final model used in the system reached an average accuracy of 95%. The system raised ethical concerns both in terms of user interaction and having such a system in a real world scenario, but it could initially work as a complement to a real bartender.

stat.ML

Musical Instrument Recognition Using Their Distinctive Characteristics in Artificial Neural Networks

In this study an Artificial Neural Network was trained to classify musical instruments, using audio samples transformed to the frequency domain. Different features of the sound, in both time and frequency domain, were analyzed and compared in relation to how much information that could be derived from that limited data. The study concluded that in comparison with the base experiment, that had an accuracy of 93.5%, using the attack only resulted in 80.2% and the initial 100 Hz in 64.2%.

cs.SD