EDP Sciences logo
Web of Conferences logo
Search
Menu
All issues Volume 475 (2024) E3S Web Conf., 475 (2024) 02018 References
Open Access
Issue
E3S Web Conf.
Volume 475, 2024
InCASST 2023 - The 1st International Conference on Applied Sciences and Smart Technologies
Article Number 02018
Number of page(s) 7
Section Environmental Impact Assessment and Management
DOI https://doi.org/10.1051/e3sconf/202447502018
Published online 08 January 2024
  1. E.A. Agbede, Y. Bani, W.N.W. Azman-Saini, N.A.M Naseem, The impact of energy consumption on environmental quality: empirical evidence from the MINT countries, Environ Sci Pollut Res 28(38), ,54117-54136, (2021) [CrossRef] [PubMed] [Google Scholar]
  2. K. Vaca, M. M. Jefferies, X. Yang, An Open Audio Processing Platform with Zync FPGA, in Proceeding of 2019 22nd IEEE Int. Symp. Meas. Control Robot. Robot. Benefit Humanit. ISMCR 2019, D1-2-1-D1-2–6, (2019) [Google Scholar]
  3. K. Vaca, A. Gajjar, X. Yang, Real-Time Automatic Music Transcription (AMT) with Zync FPGA, in Proceeding of IEEE Comput. Soc. Annu. Symp. VLSI, ISVLSI, vol. 2019-July (2019), 378–384, (2019) [Google Scholar]
  4. T. Fujishima, Realtime Chord Recognition of Musical Sound: A System Using Common Lisp Music, in ICMC Proceedings, 9(6), 464–467, (1999) [Google Scholar]
  5. P. Rajpurkar, B. Girardeau, T. Migimatsu, A Supervised Approach To Musical Chord Recognition, Stanford Undergrad. Res. J. 15, 36–40, (2015) [Google Scholar]
  6. K. Ma, Automatic Chord Recognition, Personal Project, 2016. http://pages.cs.wisc.edu/~kma/projects.html (accessed Mar. 12, 2023). [Google Scholar]
  7. E. Demirel, B. Bozkurt, X. Serra, Automatic chord-scale recognition using harmonic pitch class profiles, in Proceeding of Sound Music Computing Conference 2019, 72–79, (2019) [Google Scholar]
  8. L. Sumarno, Chord recognition using segment averaging feature extraction with simplified harmonic product spectrum and logarithmic scaling, Int. J. Electr. Eng. Informatics 10(4), 753–764 (2018) [CrossRef] [Google Scholar]
  9. L. Sumarno, Chord Recognition using FFT Based Segment Averaging and Subsampling Feature Extraction, in Proceeding of 2020 8th International Conference on Information and Communication Technology, ICoICT 2020, 465–469,(2020) [Google Scholar]
  10. L. Ivanov, J. Dunn, Automatic Identification of Guitar Types from Prerecorded Audio, in Proceeding of 33rd FLAIRS Conference 2020, 308–311, (2020) [Google Scholar]
  11. D.A. Talavera, E.S.C. Nase, L.D. Pancho, A.L. Ilao, Transcription of guitar chords from acoustic audio, J. Adv. Inf. Technol. 11(3), 149–154 (2020) [Google Scholar]
  12. L Sumarno, The Performance of MFCC Feature Extraction for Guitar Chord Recognition, in Proceedings of the International Conference on Information Technology and Digital Applications 2021 (ICITDA 2021), 020012-1 - 020012-8 (Published 2023) [Google Scholar]
  13. L. Tan, J. Jiang, Digital Signal Processing Fundamentals and Applications, 3rd ed. (Elsevier Inc., Oxford, 2019). [Google Scholar]
  14. O.K. Hamid, Frame Blocking and Windowing Speech Signal, J. Information, Commun. Intell. Syst. 4(5), 87–94 (2018). [Google Scholar]
  15. H. Rakshit, M. A. Ullah, A comparative study on window functions for designing efficient FIR filter, in Proceeding of 2014 9th Int. Forum Strateg. Technol. IFOST 2014, July 2014, 91–96, (2014) [Google Scholar]
  16. M. Voelsen, D.L. Torres, R.Q. Feitosa, F. Rottensteiner, C. Heipke, Investigations on feature similarity and the impact of training data for land cover classification, ISPRS Ann. Photogramm. Remote Sens. Spat. Inf. Sci. 5(3), 181–189 (2021) [CrossRef] [Google Scholar]
  17. I. Izonin, R. Tkachenko, N. Shakhovska, B. Ilchyshyn, K.K. Singh, A Two-Step Data Normalization Approach for Improving Classification Accuracy in the Medical Diagnosis Domain, Mathematics 2022, 10(11), 1942, (2022) [Google Scholar]
  18. A.K. Jain, R.P.W. Duin, J. Mao, Statistical pattern recognition: A review, IEEE Trans. Pattern Anal. Mach. Intell. 22(1), 4–37 (2000) [CrossRef] [Google Scholar]
  19. A. Massari, R.W. Clayton, M. Kohler, Damage detection by template matching of scattered waves, Bull. Seismol. Soc. Am. 108(5), 2556–2564 (2018) [CrossRef] [Google Scholar]
  20. H.U. Zhi-Qiang, Z. Jia-Qi, W. Xin, L.I.U. Zi-Wei, L.I.U. Yong, Improved algorithm of DTW in speech recognition, in Proceeding of IOP Conf. Ser. Mater. Sci. Eng., 563(5), (2019), [Google Scholar]
  21. S. Sohangir, D. Wang, Improved sqrt-cosine similarity measurement, J. Big Data 4, 1 (2017). [Google Scholar]
  22. H.R. Shahdoosti, F. Mirzapour, Spectral–spatial feature extraction using orthogonal linear discriminant analysis for classification of hyperspectral data, Eur. J. Remote Sens., 50(1), (2017) [Google Scholar]

Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.

Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.

Initial download of the metrics may take a while.