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1. |
Record Nr. |
UNISA996466055303316 |
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Autore |
Tanguiane Andranick S |
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Titolo |
Artificial Perception and Music Recognition [[electronic resource] /] / by Andranick S. Tanguiane |
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Pubbl/distr/stampa |
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Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 1993 |
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ISBN |
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Edizione |
[1st ed. 1993.] |
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Descrizione fisica |
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1 online resource (XV, 210 p.) |
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Collana |
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Lecture Notes in Artificial Intelligence ; ; 746 |
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Disciplina |
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Soggetti |
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Pattern recognition |
Artificial intelligence |
Data structures (Computer science) |
Electrical engineering |
Pattern Recognition |
Artificial Intelligence |
Data Storage Representation |
Communications Engineering, Networks |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Note generali |
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Bibliographic Level Mode of Issuance: Monograph |
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Nota di contenuto |
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Correlativity of perception -- Substantiating the model -- Implementing the model -- Experiments on chord recognition -- Applications to rhythm recognition -- Applications to music theory -- General discussion -- Conclusions. |
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Sommario/riassunto |
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This monograph presents the author's studies in music recognition aimed at developing a computer system for automatic notation of performed music. The performance of such a system is supposed to be similar to that of speech recognition systems: acoustical data at the input and music scoreprinting at the output. The approach to pattern recognition employed is thatof artificial perception, based on self-organizing input data in order to segregate patterns before their identification by artificial intelligencemethods. The special merit of the approach is that it finds optimal representations of data instead of directly recognizing patterns. |
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2. |
Record Nr. |
UNINA9910557750303321 |
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Autore |
PuvacÌa Nikola |
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Titolo |
Sustainable Organic Agriculture for Developing Agribusiness Sector |
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Pubbl/distr/stampa |
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Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021 |
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Descrizione fisica |
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1 online resource (330 p.) |
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Soggetti |
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Biology, life sciences |
Research & information: general |
Technology, engineering, agriculture |
Research and information: general |
Technology, Engineering, Agriculture, Industrial processes |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Sommario/riassunto |
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Developing sustainable organic agriculture and resilient agribusiness sector is fundamental, keeping in mind the value of the opportunity presented by the growing demand for healthy and safe food globally, with the expectation for the global population to reach 9.8 billion by 2050, and 11 billion by 2100.Lately, the main threats in Europe, and worldwide, are the increasingly dynamic climate change and economic factors related to currency fluctuations. While the current environmental policy provides several mechanisms to support agribusinesses in mitigating organic food for daily increasing human population and stability of the currency, it does not contemplate the relative readiness of individuals and businesses to act correctly.Organic farming is the practice that relies more on using sustainable methods to cultivate crops and produce food animals, avoiding chemicals and dietary synthetic drug inputs that do not belong to the natural ecosystem. Organic agriculture can also contribute to meaningful socioeconomic, ecologically sustainable development, and significantly in the development of the agribusiness sector, especially in developing countries. |
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