Protecting Rose Leaves From Diseases: A Deep Learning Strategy

Roses are famous worldwide for their beauty and smell. Apart from this, rose water is popular as perfume, food, drink, and medicine. Many rose flowers are exported from West Bengal, India, every year. For all this, it is essential to ensure the health of the rose plant and its leaves for proper growth. Rose leaves must be treated before and during any disease. The cost, labor and time of manual disease detection are high and accurate detection is impossible for human beings. Therefore, the main objective of this paper is to diagnose rose leaf diseases correctly and suggest drugs to the farmer using deep learning methods. Two prevalent rose diseases are Black Spot and Downy Mildew consider. Here, diseased rose leaves are considered as input. After the necessary pre-processing, various deep-learning algorithms were applied to the created dataset. Using the CNN deep learning model achieved 94.33% accuracy.

Authors

Institutions

Publication Details

Published
2024-12-06
DOI
https://doi.org/10.1109/ccis63231.2024.11105569
Primary Topic
Plant Pathogens and Fungal Diseases
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Protecting Rose Leaves From Diseases: A Deep Learning Strategy

Anup Das, Abhirup Paria, Arpan Adhikary, Jayeeta Majumder et al.
Plant Pathogens and Fungal Diseases
article

Protecting Rose Leaves From Diseases: A Deep Learning Strategy

Anup Das, Abhirup Paria, Arpan Adhikary, Jayeeta Majumder, Ruma Das, Priyanka Sen
article en

Abstract

Roses are famous worldwide for their beauty and smell. Apart from this, rose water is popular as perfume, food, drink, and medicine. Many rose flowers are exported from West Bengal, India, every year. For all this, it is essential to ensure the health of the rose plant and its leaves for proper growth. Rose leaves must be treated before and during any disease. The cost, labor and time of manual disease detection are high and accurate detection is impossible for human beings. Therefore, the main objective of this paper is to diagnose rose leaf diseases correctly and suggest drugs to the farmer using deep learning methods. Two prevalent rose diseases are Black Spot and Downy Mildew consider. Here, diseased rose leaves are considered as input. After the necessary pre-processing, various deep-learning algorithms were applied to the created dataset. Using the CNN deep learning model achieved 94.33% accuracy.

Haldia Institute of Technology (IN)
Openalex Percentile: Top 73%
Plant Pathogens and Fungal Diseases
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.