Essays about: "Audio classification"
Showing result 6 - 10 of 58 essays containing the words Audio classification.
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6. Impact of GAN methods for theHandwritten Digit Classification inHandwritten Document Images
University essay from Blekinge Tekniska Högskola/Institutionen för datavetenskapAbstract : Background: GANs are well-known for their ability to generate realistic fake sample data, which can be audio, images, and videos. The application areas of GANs have increased their popularity in recent years. The first and best feature of GANs is their learning nature, characterized by powerful learning. READ MORE
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7. Comparison of CNN and LSTM for classifying short musical samples
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : Applying machine learning to music and audio data is becoming increasingly common. One such area of research is instrument classification, which is the task of identifying the instrument played in a given audio file. In this study, we compared two machine learning model types, LSTM and CNN, on the task of classifying ten different instruments. READ MORE
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8. Efficient Music Thumbnailing for Genre Classification
University essay from KTH/Matematisk statistikAbstract : For music genre classification purposes, the importance of an intelligent and content-based selection of audio samples has been mostly overlooked. One common approach toward representative results is to select samples at predetermined locations. This is done to avoid analysis of the full audio during classification. READ MORE
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9. Automatic loose gravel condition detection using acoustic observations
University essay from Högskolan Dalarna/Institutionen för information och teknikAbstract : Evaluation of the road's condition and state is essential for its upkeep, especially when discussing gravel roads, for the following reasons, among other. When loose gravel is not adequately maintained, it can pose a hazard to drivers, who can lose control of their vehicle and cause accidents. READ MORE
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10. Multimodal Machine Learning in Human Motion Analysis
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : Currently, most long-term human motion classification and prediction tasks are driven by spatio-temporal data of the human trunk. In addition, data with multiple modalities can change idiosyncratically with human motion, such as electromyography (EMG) of specific muscles and respiratory rhythm. READ MORE