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Division of Electronics and Electrical Engineering, Biometrics Engineering Research Center (BERC), Dongguk University, 26 Pil-dong 3-ga, Jung-gu, Seoul 100-715, Republic of Korea Dept. of Computer Science, Sangmyung University, 7 Hongji-dong, Jongno-gu, Seoul 110-743, Republic of Korea c Technical Research Institute, Hyundai Mobis, 80-9, Mabuk-dong,(More)
Recently, the necessity for content-based music retrieval that can return results even if a user does not know information such as the title or singer has increased. Query-by-humming (QBH) systems have been introduced to address this need, as they allow the user to simply hum snatches of the tune to find the right song. Even though there have been many(More)
This research proposes new system which finds the music by using Query-by-Humming (QBH). For finding a stored music, the features of humming data are selected by using G.729 feature extractor. We normalize the extracted features by using mean-shifting, median filtering, average filtering and min-max scaling methods. Then the corresponding music is matched(More)
This extended abstract describes the method for MIREX 2011 task “Query by Singing/Humming”. The method extracts the pitch values from a database, and then the extracted data are normalized by zero elimination, meanshifting, median filtering, average filtering, and min-max scaling [1-4]. For matching, we used multiple classifiers. From those, a number of(More)
In scalp skin examinations, it is difficult to find a previously treated region on a patient's scalp through images captured by a camera attached to a diagnostic device because the zoom lens on camera has a small field of view. Thus, doctors manually record the region on a chart or manually mark the region. However, this process is slow and inconveniences(More)