Zobrazeno 1 - 4
of 4
pro vyhledávání: '"Adrián Tonatiuh Ruiz"'
Autor:
Adrián Tonatiuh Ruiz, Santiago Martínez Balvanera, Everardo Robredo, Julian Equihua, Friedhelm Schwenker, Günther Palm
Publikováno v:
Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications ISBN: 9783030134686
CIARP
CIARP
Bats are indicators for ecosystem health, and therefore the determination of bat activity and species abundance provides essential information for biodiversity research and conservation monitoring. In this study, we propose a computational method for
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3b582be7d01e08e761c3927a2c75c9ed
https://doi.org/10.1007/978-3-030-13469-3_30
https://doi.org/10.1007/978-3-030-13469-3_30
Publikováno v:
Artificial Neural Networks in Pattern Recognition ISBN: 9783319999777
ANNPR
ANNPR
Multi-instance multi-label learning (MIML) is a framework in machine learning in which each object is represented by multiple instances and associated with multiple labels. This relatively new approach has achieved success in various applications, pa
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b68f0739ee7856869694b252e0e43b48
https://doi.org/10.1007/978-3-319-99978-4_11
https://doi.org/10.1007/978-3-319-99978-4_11
Publikováno v:
Mathematics and Computation in Music ISBN: 9783319718262
MCM
MCM
The problem of identifying musical styles using mathematical tools is central not only in musicology and the mathematical theory of music, but also in applications to music pattern recognition and automated music generation in a particular idiom. In
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::9cf82cbea24224dedc1970f5942a9765
https://doi.org/10.1007/978-3-319-71827-9_20
https://doi.org/10.1007/978-3-319-71827-9_20
Publikováno v:
8th International Conference of Pattern Recognition Systems (ICPRS 2017).
Bats are indicators for ecosystem health, and therefore the determination of bat activity and species abundance provides essential information for biodiversity research and conservation monitoring. In this study, we propose a computational method for