Machine learning en la detección de enfermedades en plantas

Machine learning en la detección de enfermedades en plantas

Palabras clave: Plants, Machine Learning, Algorithm, Neuronal Networks, Diseases (en_US)
Palabras clave: Plantas, Aprendizje Automatico, Algoritmo, Redes Neuronales, Enfermedades (es_ES)

Resumen (es_ES)

El rápido crecimiento de la población a generado una alta demanda de alimentos para cumplir con las necesidades de esta. Además, es difícil cumplir con la demanda gracias a la proliferación de enfermedades en los cultivos, ya que la identificación de dichas enfermedades en su mayoría de casos se realiza de manera manual, lo cual requiere de personal especializado para el diagnóstico y las técnicas utilizadas son rudimentarias tomando mucho tiempo.

En este artículo se busca mostrar la relevancia que está tomando el machine learning en la identificación de enfermedades en plantas a través de la revisión literaria de varios trabajos con diversas técnicas de reconocimiento que permitirán una identificación temprana de enfermedades en plantas para tomar acciones y así evitar una proliferación mayor de la enfermedad.

Resumen (en_US)

The rapid growth of the population has generated a high demand of food to satisfy its needs. In addition, it is difficult to satisfy the demand thanks to the proliferation of diseases in crops, as the identification of theses disease in most cases is done manually, which requires specialized personal to diagnosis and the techniques used are rudimentary taking a long time.

The present article shows the relevance that machine learning is taking in the identification of plants through the literally review of several articles with various recognition techniques that will allow an early identification of diseases in plants to take actions and thus avoid a greater proliferation of disease.

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Referencias

S. U, V. Nagaveni and B. K. Raghavendra,(2019)."A Review on Machine Learning Classification Techniques for Plant Disease Detection," 5th International Conference on Advanced Computing & Communication Systems (ICACCS), Coimbatore, India, pp. 281-284.

J. Shirahatti, R. Patil and P. Akulwar, (2018)."A Survey Paper on Plant Disease Identification Using Machine Learning Approach," 3rd International Conference on Communication and Electronics Systems (ICCES), Coimbatore, India, pp. 1171-1174.

S. R. Maniyath et al., (2018). "Plant Disease Detection Using Machine Learning," 2018 International Conference on Design Innovations for 3Cs Compute Communicate Control (ICDI3C), Bangalore, pp. 41-45.

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F Ahmed, HA AI-Mamun, (2012). ASMH Bari, E Hossain, “Classification of crops and weeds from digital images: A SVM approach”, Elsevier.

P. Sharma, Y. P. S. Berwal and W. Ghai, (2018). "KrishiMitr (Farmer’s Friend): Using Machine Learning to Identify Diseases in Plants," IEEE International Conference on Internet of Things and Intelligence System (IOTAIS), Bali, 2018, pp. 29-34.

B. S. Kusumo, A. Heryana, O. Mahendra and H. F. Pardede, (2018)."Machine Learning-based for Automatic Detection of Corn-Plant Diseases Using Image Processing," International Conference on Computer, Control, Informatics and its Applications (IC3INA), Tangerang, Indonesia, pp. 93-97.

Tlhobogang and M. Wannous, (2018) "Design of plant disease detection Systems: A transfer learning approach work in progress,” IEEE

Cómo citar
Calderon, A., & Hurtado Cortes, H. D. (2020). Machine learning en la detección de enfermedades en plantas. Tecnología Investigación Y Academia, 7(2), 55-61. Recuperado a partir de https://revistas.udistrital.edu.co/index.php/tia/article/view/15685
Castillo de Alhambra de  Granada. España
Publicado: 2020-08-12
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