Documentos de Toro M. | REDI

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Mostrando 7 resultados de: 7

Filtros aplicados

Palabras Claves: "Machine Learning"

Subtipo de publicación

Conference Object(2)

Publisher

2021 IEEE Symposium Series on Computational Intelligence Ssci 2021 Proceedings(1)

2021 IEEE Symposium Series on Computational Intelligence, SSCI 2021 - Proceedings(1)

Applied Soft Computing(1)

Artificial Intelligence in Medicine(1)

Computers and Electronics in Agriculture(1)

Área temáticas

Agricultura y tecnologías afines(3)

Ciencias de la computación(3)

Métodos informáticos especiales(2)

Área de conocimiento

Aprendizaje automático(3)

Ciencias de la computación(3)

Ciencia agraria(2)

Aprendizaje profundo(1)

Objetivos de Desarrollo Sostenible

ODS 2: Hambre cero(5)

ODS 9: Industria, innovación e infraestructura(4)

ODS 15: Vida de ecosistemas terrestres(3)

ODS 3: Salud y bienestar(3)

ODS 17: Alianzas para lograr los objetivos(2)

Año de Publicación

Origen

Palabras Claves

Artificial intelligence(3)

Precision Livestock Farming(2)

Animal health(1)

Anomaly detection(1)

A Classification Model of Cotton Boll-Weevil Population

Conference Object

Abstract: Integrated pest management (IPM) seeks to minimize the environmental impact of pesticide application

Palabras claves:

cotton crop, Data Analysis, insect pest management, Machine Learning, Pest control, Weather, XGBoost

Caro M., Hoyos W., José Lisandro Aguilar Castro, Toro M., Toscano-Miranda R., Trebilcok A.

A clinical decision-support system for dengue based on fuzzy cognitive maps

Abstract: Dengue is a viral infection widely distributed in tropical and subtropical regions of the world. Den

Palabras claves:

Artificial intelligence, Clinical decision-support system, DENGUE, diagnosis, Fuzzy Cognitive Maps, Machine Learning

Hoyos W., José Lisandro Aguilar Castro, Toro M.

A systematic literature review on the use of machine learning in precision livestock farming

Abstract: This article presents a systematic literature review of recent works on the use of machine learning

Palabras claves:

Animal health, Artificial intelligence, Big Data Analytics, grazing, Industry 4.0, Machine Learning, Precision Livestock Farming

José Lisandro Aguilar Castro, Pinto A.D., Rodrigo G., Rodríguez P., Toro M.

Weight-Identification Model of Cattle Using Machine-Learning Techniques for Anomaly Detection

Conference Object

Abstract: Cattle raising is an important economic activity, where livestock entrepreneurs keep track of their

Palabras claves:

Anomaly detection, identification system, Machine Learning, Precision Livestock Farming

Jiménez M., José Lisandro Aguilar Castro, Rodrigo G., Toro M.

Dengue models based on machine learning techniques: A systematic literature review

Abstract: Background: Dengue modeling is a research topic that has increased in recent years. Early prediction

Palabras claves:

DENGUE, Diagnostic model, Epidemic model, intervention model, Machine Learning

Hoyos W., José Lisandro Aguilar Castro, Toro M.

Artificial-intelligence and sensing techniques for the management of insect pests and diseases in cotton: A systematic literature review

Abstract: Integrated pest management (IPM) seeks to minimize the environmental impact of pesticide application

Palabras claves:

Internet of Things, Key words Image processing, Machine Learning, pest detection, precision agriculture, Remote Sensing, Smart agriculture

A. Marulanda, Caro M., José Lisandro Aguilar Castro, Marulanda A., Toro M., Toscano-Miranda R., Trebilcok A.

Different transfer learning approaches for insect pest classification in cotton

Abstract: Boll weevil is an important pest that affects cotton crops worldwide, causing significant economic l

Palabras claves:

Artificial intelligence, Cotton management, Insect pests, Machine Learning, Transfer learning

Caro M., Hoyos W., José Lisandro Aguilar Castro, Toro M., Toscano-Miranda R., Trebilcok A.