• Proceedings of the KIEE Conference
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• 1992.07a
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• pp.427-430
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• 1992

In this paper, we proposed an algorithm for the musical note recognition. Firstly, a given bit-mapped music score image is converted to a set of individual note pattern images via vertical projection. Then, the pitch of a note is determinal by comparison in the note-head position with the reference five-lines. Also, the length of a note is found via leader clustering with a set of normalized note patterns. Finally, a datafile to play the music is obtained using the pitch and length of musical notes. Experimental results with a simple musical score image show that the proposed scheme is performed well.

• Proceedings of the IEEK Conference
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• 2000.07a
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• pp.306-309
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• 2000

We developed an electronic music glove (EMG) system that could play musical scores in real time processing. The EMG system interfaces with the signal coming from the controller to the sound card in the computer. The computer, according to the status of the finger and foot switches, generates the signals to the speaker systems using the application C++ program by making use of MIDI message. The EMG systems can control up to several octave notes and duration of sound, and several musical performance expressions such as chorus, reverberation, rhythm, and volume. Finally, our EMG could play the performance of simple music depending on the choice of any kind of musical instruments in the sound card in computer systems.

• Journal of electromagnetic engineering and science
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• v.15 no.1
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• pp.37-43
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• 2015

We implemented a real-time radar system for an unmanned ground vehicle designed to run on unpaved or bumpy roads. The system must be able to detect slow targets in a cluttered environment and cover wide angular sections with high resolution at the same time. The system consists of array antennas, preprocessors for digital beam forming, and digital signal processors for the detection process which uses sawtooth waveforms and high-resolution estimation, and is called forward/backward spatial smoothing beamspace multiple signal classification (FBSS BS-MUSIC). We show that the sawtooth waveforms enhance the angular estimation capability of FBSS BS-MUSIC in addition to their well-known advantages of removing the ambiguity of targets and detecting slow targets with improved velocity resolution.

• Proceedings of the Korean Information Science Society Conference
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• 2012.06c
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• pp.87-88
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• 2012

지금까지 한국근대음악에 대한 담론은 꾸준히 진행되어 왔으나 음악원전을 공유할 수 있는 시스템이 아직 구축되지 않은 상태이며, 특히 한국의 근대음악문화를 형성하는 데 중요한 역할을 담당했던 음악교육자료는 쉽게 찾아보기 힘들다. 본 논문에서는 동아시아의 음악교육자료를 바탕으로 음악원전을 공유할 수 있는 데이터베이스를 구축함으로써, 한국 근대음악문화를 보다 거시적인 안목에서 연구할 수 있는 선도역할을 하고자 한다.

• ETRI Journal
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• v.43 no.6
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• pp.1081-1092
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• 2021

Electroencephalography (EEG) recordings taken during the perception of music tempo contain information that estimates the tempo of a music piece. If information about this tempo stimulus in EEG recordings can be extracted and classified, it can be effectively used to construct a music-based brain-computer interface. This study proposes a novel convolutional recurrent attention model (CRAM) to extract and classify features corresponding to tempo stimuli from EEG recordings of listeners who listened with concentration to the tempo of musics. The proposed CRAM is composed of six modules, namely, network inputs, two-dimensional convolutional bidirectional gated recurrent unit-based sample encoder, sample-level intuitive attention, segment encoder, segment-level intuitive attention, and softmax layer, to effectively model spatiotemporal features and improve the classification accuracy of tempo stimuli. To evaluate the proposed method's performance, we conducted experiments on two benchmark datasets. The proposed method achieves promising results, outperforming recent methods.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2009.10a
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• pp.1059-1062
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• 2009

As the electronic processing of music gradually is developed, there has been growing interest in automatical input of music. As a result, various researches which input music in the computer has been studied. However, previous studies have drawbacks that only the experts can do it. In other words, if beginners would like to use traditional production program of music scores than prior knowledge is required. To resolve this, we propose system painting music scores automatically using a bandwidth of soundsource, after extracting the voice sounds created by amateurs. The System provides amateurs with convenience so that they can compose. As well as, the System provides the ability to play music that produced by the computer. By using the system, amateurs can compose using voice and simple system handling. And, they can make a music that plays desired instruments.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.1
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• pp.69-77
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• 2021

This paper deals with the development of an application that converts the PDF music score entered by the user into a MIDI file of the chord the user wants. This application converts the PDF file into a PNG file for chord conversion when the user enters the PDF music score file and the chord which the user wants to change. After recognizing the melody of sheet music through image processing algorithm and recognizing the tempo of sheet music notes through deep learning, then the MIDI file of chord for existing sheet music is produced. The OpenCV algorithm and deep learning can recognize minim note, quarter note, eighth note, semi-quaver note, half rest, eighth rest, quarter rest, semi-quaver rest, successive notes and chord notes. The experiment shows that the note recognition rate of the music score was 100% and the tempo recognition rate was 90% or more.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.377-379
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• 2021

According to a 2006 paper by a music therapist and a music therapist in elementary schools, the demand for special education increased, and a 2018 music education study showed that music rooms and equipment increased, but it was difficult to move or lacked various instruments. In this work, we develop a module that combines hardware and software for social improvement education in autistic children using tools. Various instrument sounds can be set using piezo sensors and Arduino, so you can experience various instruments through simple operation and there are instruments designed for music therapy through modularity. Hopefully, the study will help disabled children heal their music.

• Journal of Digital Contents Society
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• v.19 no.4
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• pp.829-836
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• 2018

Sheet music is one of the inevitable elements for successful melody interpretation, playing or rendering, and performance, most of performing artists usually utilize a paper sheet music in the cases. However, the paper sheet music can be a one of the reason to degrade the concentration of audiences and artists or entire performing flows. In addition, it might be a weakness to use a paper sheet music in an outside performing place. We propose an electronic sheet music page tuner application, which can overcome these problems, based on a Tablet PC. The proposed page tuner application, which uses the OpenCV to adapt an eye tracking and behavior recognition, can provide an automatical page pass function to the performing artists. We will expect that the proposed application can highly decrease the weakness of paper sheet music.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.9 no.3
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• pp.291-297
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• 2016

In this paper, we are comparative analysis of exit algorithm and proposal algorithm for desired target direction of arrival estimation in correlation signal system. Proposed algorithm in this paper is to decrease target direction of arrival an estimation error probability using bayesian, maximum posterior, and MUSIC algorithm in order to decrease direction of arrival error probability as optimize and use linear constrained minimum variance to update weight value. Through simulation, we were comparative analysis proposed algorithm and exit MUSIC algorithm. In case SNR is 10dB and antenna element arrays are 9 and 12, We show the superior performance of the proposed method relative to the class method to decrease of signal estimation error probability about 11% and 13%, respectively.