FlowerNet: An extensive rose leaves dataset for disease recognition applying machine learning and deep learning models

Published: 12 April 2022| Version 1 | DOI: 10.17632/7z67nyc57w.1
Contributors:
Aditya Rajbongshi,
,
Rashiduzzaman Shakil,
,

Description

(1) Plant diseases are the leading cause of decreased agricultural output, which leads to economic losses. Rose is known as both the "Queen of Flowers" and the "King of Flowers." This implies that it possesses both kingliness (magnificence, status, and power) and queenliness (beauty, grace, and cultural refinement). Rose illnesses, on the other hand, have a detrimental effect on rose production. (2) Computer vision and image processing have a big influence on detecting numerous illnesses in flowering plants. (3) The collection comprises images of diseased Rose leaves as well as disease-free Rose leaves, which may be used to construct an automated method for researchers to forecast illnesses in Rose Flowers. The dataset includes two Rose diseases: black spot and downy mildew. Aside from the disease-free leaves, the dataset also includes them. (4) This section includes two types of datasets: the original dataset (a total of 917 photos) and the augmented dataset (a total of 4342 images). Each picture has a generalized dimension of 512*512 pixels. (5) The photos were personally taken from the Village of Roses (Golap Gram), Sadullapur Road Birulia Bridge, Dhaka 1216, Bangladesh, with the assistance of domain specialists and a plant study institute.

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Institutions

National Institute of Textile Engineering and Research

Categories

Computer Vision, Image Processing, Machine Learning, Image Classification, Deep Learning

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