Open Access
Malaysian Medicinal Plant Leaf Shape Identification and Classification
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TLDR
This study proposes a framework to identify and classify tropical medicinal plants in Malaysia based the extracted patterns from the leaf based on several angle features.Abstract:
Malaysian medicinal plants may be abundant natural resources but there has not been much research done on preserving the knowledge of these medicinal plants which enables general public to know the leaf using computing capability. This study proposes a framework to identify and classify tropical medicinal plants in Malaysia based the extracted patterns from the leaf. The extracted patterns from medicinal plant leaf are obtained based on several angle features. Five classifiers, obtained from WEKA and an ensemble classifier, called Direct Ensemble Classifier for Imbalanced Multiclass Learning (DECIML), are used to compare their performance accuracies over this data. In this experiment, five species of Malaysian medicinal plants are identified and classified in which each species will be represented by using 65 images. This study is important in order to assist local community to utilize the knowledge discovery and application of Malaysian medicinal plants for future generation. In this paper, a preliminary study is conducted toread more
Citations
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Journal Article
Shape recognition based on radial basis probabilistic neural network and application to plant species identification
TL;DR: A novel shape recognition method based on radial basis probabilistic neural network (RBPNN) that achieves higher recognition rate and better classification efficiency with respect to radial basis function neural network, BP neural network and multi-Layer perceptron network for the plant species identification.
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A Review of Visual Descriptors and Classification Techniques Used in Leaf Species Identification
TL;DR: This study reviews several image processing methods in the feature extraction of leaves and discusses certain machine learning classifiers for an analysis of different species of leaves.
Journal ArticleDOI
Machine learning in medicinal plants recognition: a review
TL;DR: Various effective and reliable machine learning algorithms for plant classifications using leaf images that have been used in recent years are reviewed and categorised according to their performance when classifying leaf images based on typical plant features.
Journal ArticleDOI
An IoT and Machine Learning Based Intelligent System for the Classification of Therapeutic Plants
Roopashree Shailendra,Anitha Jayapalan,Sathiyamoorthi Velayutham,Arunadevi Baladhandapani,Ashutosh Srivastava,Manoj Kumar +5 more
TL;DR: The work aim to develop an automatic recognition model using IoT and machine learning (ML) techniques for the classification of therapeutic plants to enrich the traditional medicinal system in Ayurveda.
Book ChapterDOI
Automated Classification of Tropical Plant Species Data Based on Machine Learning Techniques and Leaf Trait Measurements
TL;DR: In this paper, three machine learning techniques namely Linear Discriminant Analysis (LDA), Random Forest (RF) and Support Vector Machine (SVM) were applied with/without SMOTE.
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A Leaf Recognition Algorithm for Plant Classification Using Probabilistic Neural Network
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TL;DR: Content-based image retrieval (CBIR), emerged as a promising mean for retrieving images and browsing large images databases and is the process of retrieving images from a collection based on automatically extracted features.