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Adaptive Segmentation with Intelligent ResNet and LSTM–DNN for Plant Leaf Multi-disease Classification Model

Kalicharan Sahu · Sonajharia Minz

Sensing and Imaging · 3 Jul 2023 · 10.1007/s11220-023-00428-3

Abstract

Abstract has not been obtained from indexed metadata or an accessible article page.

Code and data availability

The paper's leaf-disease classification experiments use the publicly available PlantifyDR Kaggle dataset (~87k RGB leaf images, 37 classes) as its input image data. No author code, models, or supplementary deposits are mentioned.

Datasetpublic

bability of beggars and producers in terms of searching for food. The pseudo-code of the sug- gested HBM-BSO is given here, Algorithm 1. 4.2 Description of Datasets The developed multi-disease plant leaf classification model gathered the images from standard online sources. The selected input images are obtained from the link “https://www.kaggle.com/datasets/lavaman151/plantifydr-dataset: access date: 2022-05-02”. Here, sample images are collected from the dataset kaggle, whereas the original dataset is collected from the GitHub repo. This dataset holds nearly 87 k rgb healthy and non-healthy images of plant leaves, and it is classified into 37 varie- ties of classes. The whole dataset is s

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