Showing items with similar title or keywords.

• Developing and testing sub-band spectral features in music genre and music mood machine learning 

  Prezja, Fabi (2018)

  In the field of artificial intelligence, supervised machine learning enables us to try to develop automatic recognition systems. In music information retrieval, training and testing such systems is possible with a variety ...

• Testing a spectral-based feature set for audio genre classification 

  Hartmann, Martín Ariel (2011)

  Automatic musical genre classification is an important information retrieval task since it can be applied for practical purposes such as the organization of data collections in the digital music industry. However, this ...

• Component search in a metaCASE environment 

  Äijänen, Matti (2001)

• Discovering Business Processes from Unstructured Text 

  Pietikäinen, Sampo (2020)

  Asiakirjojen käsittely manuaalisesti kuluttaa paljon tietotyöntekijän resursseja. Tämä koskee myös liiketoimintaprossien johtamisen asiantuntijoita, joiden työ voi vaatia useiden liiketoimintaprosessien kuvausten lukemista. ...

• Exploring Frequency-Dependent Brain Networks from Ongoing EEG Using Spatial ICA During Music Listening 

  Zhu, Yongjie; Zhang, Chi; Poikonen, Hanna; Toiviainen, Petri; Huotilainen, Minna; Mathiak, Klaus; Ristaniemi, Tapani; Cong, Fengyu (Springer, 2020)

  Recently, exploring brain activity based on functional networks during naturalistic stimuli especially music and video represents an attractive challenge because of the low signal-to-noise ratio in collected brain data. ...