Your browser doesn't support javascript.
loading
Identification of dragon trees and fruits in ham Thuan Bac growing areas, Phan Thiet city, Binh Thuan province, Vietnam.
Nguyen, Ha Huy Cuong; Jana, Chiranjibe; Hezam, Ibrahim M; Hieu, Ho Phan; Thuy, Nguyen Thanh.
Afiliación
  • Nguyen HHC; Software Development Centre - the University of Danang, Danang City, Viet Nam.
  • Jana C; Saveetha School of Engineering, Saveetha Institute of Medical and Technical Sciences (SIMATS), Chennai 602105, Tamil Nadu, India.
  • Hezam IM; Statistics & Operations Research Department, College of Sciences, King Saud University, Riyadh 11451, Saudi Arabia.
  • Hieu HP; School of National Defense and Security Education - The University of Danang, Danang University Urban Area, Ngu Hanh Son District, 50000, DaNang, Viet Nam.
  • Thuy NT; Faculty of Computer Science, VNU University of Engineering and Technology, E3 Building, 144 Xuan Thuy Street, Cau Giay District, 000084, Hanoi, Viet Nam.
Heliyon ; 10(10): e31233, 2024 May 30.
Article en En | MEDLINE | ID: mdl-38803938
ABSTRACT
With the development of Computer Vision, we can effectively and accurately identify trees, fruit or object images. But to build a high-performance image dataset for tree identification problems in Agriculture is a challenge. Realizing that Vietnam is a country with strong agriculture with many tropical fruits grown widely such as Dragon fruit, Mangosteen, Mango, Orange, Lychee, Longan … We chose the Dragon Fruit tree for the data set. of my proposed images, all images will be collected using the close-up method, including tasks such as taking photos of Dragon Fruit trees from many angles and in different conditions (weather, temperature, light, …). In this article, we want to improve the data quality of the collected images so we have applied image processing techniques such as noise filtering (using Gaussian filter), image quality enhancement (image rotation), flip the image, zoom out, zoom in, etc.). From the collected Dragon Fruit tree data set, we will propose to use the Faster R-CNN model for this data set to build a tree and Dragon Fruit identification system.
Palabras clave

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Heliyon Año: 2024 Tipo del documento: Article Pais de publicación: Reino Unido

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Heliyon Año: 2024 Tipo del documento: Article Pais de publicación: Reino Unido