RoseNet: Rose leave dataset for the development of an automation system to recognize the diseases of rose

Author:

Sazzad Sadia,Rajbongshi AdityaORCID,Shakil Rashiduzzaman,Akter Bonna,Kaiser M. ShamimORCID

Funder

Bangladesh Agricultural Research Institute

Publisher

Elsevier BV

Subject

Multidisciplinary

Reference5 articles.

1. Rose diseases recognition using MobileNet;Rajbongshi,2020

2. Description of Rose Diseases, https://hgic.clemson.edu/factsheet/rose-diseases/, 2022. Accessed February 24, 2022.

3. Description of Rose Leave Diseases, https://www.britannica.com/plant/rose-plant, 2022. Accessed February 26, 2022.

4. Description of Rose Leave Description, https://www.gardenguides.com/12348756-information-about-types-of-rose-leaves.html, 2022. Accessed February 27, 2022.

5. A comprehensive investigation to cauliflower diseases recognition: an automated machine learning approach;Rajbongshi;Int. J. Adv. Sci. Eng. Inf. Technol. (IJASEIT),2022

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1. Metabolically Tailored Selection of Ornamental Rose Cultivars through Polyamine Profiling, Osmolyte Quantification and Evaluation of Antioxidant Activities;Horticulturae;2024-04-15

2. RoseVision: An Android Application To Detect Rose Leaf Diseases Using Modified Convolutional Neural Network;2023 26th International Conference on Computer and Information Technology (ICCIT);2023-12-13

3. StegoPix2Pix: Image Steganography Method via Pix2Pix Networks;Proceedings of the Fourth International Conference on Trends in Computational and Cognitive Engineering;2023

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