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  1. 1
    Hevea leaf features extraction and recognition algorithm for hevea clones classification using image / Mohamad Faizal Ab Jabal, Suhardi Hamid, Salehuddin Shuib

    Hevea leaf features extraction and recognition algorithm for hevea clones classification using image / Mohamad Faizal Ab Jabal, Suhardi Hamid, Salehuddin Shuib by Ab Jabal, Mohamad Faizal, Hamid, Suhardi, Shuib, Salehuddin

    Published 2013
    “…Final result produced by the algorithm is 92.312% of average accuracy and the classification for the leaf was based on the leaf-shape information.…”
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  2. 2
    Automated plant classification system using a hybrid of shape and color features of the leaf

    Automated plant classification system using a hybrid of shape and color features of the leaf by Hamid, Laith Emad

    Published 2016
    “…Automated plant leaf classification is a computerized approach that employs computer vision and machine learning algorithms to identify a plant based on the features of its leaf. …”
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  3. 3
    Application of Fuzzy C-Means with YCbCr and DenseNet-201 for Automated Corn Leaf Disease Detection

    Application of Fuzzy C-Means with YCbCr and DenseNet-201 for Automated Corn Leaf Disease Detection by Chyntia Jaby, Entuni

    Published 2021
    “…The results show that the proposed method performed better than the previous methods with 96.81% for segmentation as well as 95.11% for classification and it is discovered to be a good fusion of algorithms to detect plant leaf diseases.…”
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  4. 4
    Plant recognition based on identification of leaf image using image processing / Nor Silawati Sha’ari

    Plant recognition based on identification of leaf image using image processing / Nor Silawati Sha’ari by Sha’ari, Nor Silawati

    Published 2018
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  5. 5
    Plant identification using combination of fuzzy c-means spatial pyramid matching, gist, multi-texton histogram and multiview dictionary learning

    Plant identification using combination of fuzzy c-means spatial pyramid matching, gist, multi-texton histogram and multiview dictionary learning by Safa, Soodabeh

    Published 2016
    “…This study first starts with some preprocessing phases for images with dried and damaged parts in leaves, that applies on images while finding leaf as region of interest (ROI) with Otsu's method. …”
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  6. 6
    Deep plant: A deep learning approach for plant classification / Lee Sue Han

    Deep plant: A deep learning approach for plant classification / Lee Sue Han by Lee , Sue Han

    Published 2018
    “…Besides using solely a single leaf organ to recognize plant species, numerous studies have employed DL methods to solve multi-organ plant classification problem. …”
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  7. 7
    Plant leaf recognition algorithm using ant colony-based feature extraction technique

    Plant leaf recognition algorithm using ant colony-based feature extraction technique by Ghasab, Mohammad Ali Jan

    Published 2013
    “…Therefore, it can be concluded that the proposed method is capable of a high rate of classification of various plant species.…”
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  8. 8
    Leaf condition analysis using convolutional neural network and vision transformer

    Leaf condition analysis using convolutional neural network and vision transformer by Yong, Wai Chun, Ng, Kok Why, Haw, Su Cheng, Naveen, Palanichamy, Ng, Seng Beng

    Published 2024
    “…In this paper, contrast boosting, sharpening, and image segmentation are used to create an unprocessed leaf disease image dataset. Through the use of a hybrid deep learning model that combines vision transformer and convolutional neural networks for classification, the algorithm can be optimized. …”
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  9. 9
    Maize leaf disease detection and classification using Convolutional Neural Network (CNN) / Syafiqah Amir

    Maize leaf disease detection and classification using Convolutional Neural Network (CNN) / Syafiqah Amir by Amir, Syafiqah

    Published 2023
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  10. 10
    An evaluation of feature selection methods on multi-class imbalance and high dimensionality shape-based leaf image features

    An evaluation of feature selection methods on multi-class imbalance and high dimensionality shape-based leaf image features by Sainin, Mohd Shamrie, Alfred, Rayner, Ahmad, Faudziah, Lammasha, Mohamed A.M

    Published 2017
    “…Multi-class imbalance shape-based leaf image features requires feature subset that appropriately represent the leaf shape.Multi-class imbalance data is a type of data classification problem in which some data classes is highly underrepresented compared to others.This occurs when at least one data class is represented by just a few numbers of training samples known as the minority class compared to other classes that make up the majority class.To address this issue in shapebased leaf image feature extraction, this paper discusses the evaluation of several methods available in Weka and a wrapperbased genetic algorithm feature selection.…”
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  11. 11
    Classification model for hotspot occurrences using a decision tree method

    Classification model for hotspot occurrences using a decision tree method by Sitanggang, Imas Sukaesih, Ismail, Mohd Hasmadi

    Published 2011
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  12. 12
    Mid-infrared spectroscopy for early detection of basal stem rot disease in oil palm

    Mid-infrared spectroscopy for early detection of basal stem rot disease in oil palm by Liaghat, Shohreh, Mansor, Shattri, Ehsani, Reza, Mohd Shafri, Helmi Zulhaidi, Meon, Sariah, Sankaran, Sindhuja

    Published 2014
    “…The algorithms were tested to classify the leaf samples into four levels of disease severity. …”
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  13. 13
    Assessment of near-infrared and mid-infrared spectroscopy for early detection of basal stem rot disease in oil palm plantation

    Assessment of near-infrared and mid-infrared spectroscopy for early detection of basal stem rot disease in oil palm plantation by Liaghat, Shohreh

    Published 2013
    “…The results indicated that LDA-based model resulted in high average overall classification accuracies of 92% (leaf samples) and 94% (trunk samples) when mid-infrared absorbance spectra were analyzed. …”
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  14. 14
    Machine learning in medicinal plants recognition: a review

    Machine learning in medicinal plants recognition: a review by Pushpanathan, Kalananthni, Hanafi, Marsyita, Mashohor, Syamsiah, Fazlil Ilahi, Wan Fazilah

    Published 2020
    “…In this paper, various effective and reliable machine learning algorithms for plant classifications using leaf images that have been used in recent years are reviewed. …”
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  15. 15
    Review of Wheat Disease Classification and Severity Detection Models

    Review of Wheat Disease Classification and Severity Detection Models by Hongyan, Zang, Annie, Joseph, Shourong, Zhang, Rong, Liu, Wanzhen, Wang

    Published 2023
    “…In order to fully grasp the core technology of wheat disease recognition, this paper reviews the research of deep learning technology in wheat leaf disease classification and wheat disease severity. …”
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  16. 16
    A direct ensemble classifier for learning imbalanced multiclass data

    A direct ensemble classifier for learning imbalanced multiclass data by Samry @ Mohd Shamrie Sainin

    Published 2013
    “…Thus, an ensemble of classifiers is one of the methods used to solve multiclass classification tasks. …”
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  17. 17
    Recognition system for leaf images based on its leaf contour and centroid

    Recognition system for leaf images based on its leaf contour and centroid by Mohamed Khmag, Asem Ib., Syed Mohamed, Syed Abdul Rahman Al-Haddad, Kamarudin, Noraziahtulhidayu

    Published 2017
    “…In this study, an image processing algorithm in order to find out the shape structure of tested plants is presented. …”
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  18. 18
    Exploring frogeye leaf spot disease severity in soybean through hyperspectral data analysis and machine learning with Orange Data Mining

    Exploring frogeye leaf spot disease severity in soybean through hyperspectral data analysis and machine learning with Orange Data Mining by Ang, Yuhao, Mohd Shafri, Helmi Zulhaidi, Al-Habshi, Mohammed Mustafa

    Published 2025
    “…Objectives: The main objective of the study is to classify the severity level of FLS disease in soybean using hyperspectral reflectance data and machine learning algorithms. Materials and Methods: We used hyperspectral reflectance data from healthy and FLS of soybeans. …”
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  19. 19
    Introducing new statistical shape based and texture feature extraction methods in the plant species recognition system

    Introducing new statistical shape based and texture feature extraction methods in the plant species recognition system by Seyed Mohammad Hussein, Ahmad, Siti Anom, Hassan, Mohd Khair, Ishak, Asnor Juraiza

    Published 2013
    “…The results show the outperformance of the two proposed methods for image processing and optimized classifier for classification part. …”
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  20. 20
    Evaluation of multiple In Situ and remote sensing system for early detection of Ganoderma boninense infected oil palm

    Evaluation of multiple In Situ and remote sensing system for early detection of Ganoderma boninense infected oil palm by Ahmadi, Seyedeh Parisa

    Published 2018
    “…In conclusion, for early detection of Ganoderma, better accuracies were derived from the spectroradiometer which is a destructive and ground based method and still requires individual leaf sampling. …”
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