Search Results - (( motion evaluation new algorithm ) OR ( leaf classification using (algorithmic OR algorithms) ))
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Hevea leaf features extraction and recognition algorithm for hevea clones classification using image / Mohamad Faizal Ab Jabal, Suhardi Hamid, Salehuddin Shuib
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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Leaf lesion classification (LLC) algorithm based on artificial bee colony (ABC)
Published 2015“…Results showed that the Leaf Lesion Classification (LLC) algorithm based on Artificial Bee colony (ABC) produced an average 96.83% of accuracy and average 1.66 milliseconds of processing time, indicating that LLC algorithm is better than algorithm such as Otsu, Canny, Roberts and Sobel. …”
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Automated plant classification system using a hybrid of shape and color features of the leaf
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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Performance analysis of machine learning algorithms for classification of infection severity levels on rubber leaves
Published 2023“…The chlorophyll content of each leaf was measured using SPAD meter. Four classification algorithms investigated in this study were artificial neural network (ANN), support vector machine (SVM), knearest neighbour (kNN) and random forest (RF). …”
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Classification of Citrus (Rutaceae) by Using Image Processing
Published 2019“…The study present how to classify selected Citrus genus species with similar leaf shapes based on leaf images by using digital image vision machine classification. …”
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Undergraduate Final Project Report -
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Effects of Different Pre-Trained Deep Learning Algorithms as Feature Extractor in Tomato Plant Health Classification
Published 2023“…This study proposes a system that can classify tomato plant health into five categories of healthy, early blight, late blight, bacterial spot, and yellow leaf curl virus based on their leaves using deep learning algorithms as feature extractors. …”
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Plant recognition based on identification of leaf image using image processing / Nor Silawati Sha’ari
Published 2018“…Image processing techniques are used to extract the leaf feature from histogram of the leaf image. …”
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Effects of Different Pre-Trained Deep Learning Algorithms as Feature Extractor in Tomato Plant Health Classification
Published 2023“…This study proposes a system that can classify tomato plant health into five categories of healthy, early blight, late blight, bacterial spot, and yellow leaf curl virus based on their leaves using deep learning algorithms as feature extractors. …”
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Effects of Different Pre-Trained Deep Learning Algorithms as Feature Extractor in Tomato Plant Health Classification
Published 2023“…This study proposes a system that can classify tomato plant health into five categories of healthy, early blight, late blight, bacterial spot, and yellow leaf curl virus based on their leaves using deep learning algorithms as feature extractors. …”
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Effects of Different Pre-Trained Deep Learning Algorithms as Feature Extractor in Tomato Plant Health Classification
Published 2023“…This study proposes a system that can classify tomato plant health into five categories of healthy, early blight, late blight, bacterial spot, and yellow leaf curl virus based on their leaves using deep learning algorithms as feature extractors. …”
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A novel framework for potato leaf disease detection using an efficient deep learning model
Published 2022“…Therefore, this article proposes a technique based on an improved deep learning algorithm that uses the potato leaf visual features to classify them into five classes i.e., Potato Late Blight (PLB), Potato Early Blight (PEB), Potato Leaf Roll (PLR), Potato Verticilliumwilt (PVw) and Potato Healthy (PH) class. …”
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A novel framework for potato leaf disease detection using an efficient deep learning model
Published 2022“…Therefore, this article proposes a technique based on an improved deep learning algorithm that uses the potato leaf visual features to classify them into five classes i.e., Potato Late Blight (PLB), Potato Early Blight (PEB), Potato Leaf Roll (PLR), Potato Verticilliumwilt (PVw) and Potato Healthy (PH) class. …”
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Weed recognition based on erosion and dilation segmentation algorithm
Published 2009“…Many attempts have been made to develop efficient algorithms for recognition and classification. Currently research is going on for developing new machine vision algorithms for automatic recognition and classification of many divers object groups. …”
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Comparative study on leaf disease identification using Yolo v4 and Yolo v7 algorithm
Published 2023“…This work uses and compares the results of two important Computer vision algorithms namely YOLOv4 and YOLOv7 in classifying the leaf diseases from the leaf images of variety of plant species. …”
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“myHerbs”: A mobile based application for herbal leaf recognition using sift / Nur Nabilah Abu Mangshor …[et al.]
Published 2020“…All images used in this study are self-collected. Scale Invariant Feature Transform (SIFT) algorithm is used for extracting features from the herbs leaf and Fast Library for Approximate Nearest Neighbors (FLANN) algorithm is used for the classification purpose. 55 images have been evaluated for the testing purpose and the accuracy rate of 74.55% is achieved. …”
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Application of Fuzzy C-Means with YCbCr and DenseNet-201 for Automated Corn Leaf Disease Detection
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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Plant leaf recognition algorithm using ant colony-based feature extraction technique
Published 2013“…To do this, at first, based on the proposed algorithm,the physiological dimensions of leaves are automatically measured and with regard to these parameters, specified features such as shape, morph, texture and colour are extracted from the image of the plant leaf through image processing to create a reserved feature database to be used for different species of plants. …”
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Plant identification using combination of fuzzy c-means spatial pyramid matching, gist, multi-texton histogram and multiview dictionary learning
Published 2016“…Moreover with simple concatenating features, classification results are not optimal. It is crucial to integrate these heterogeneous features to create more accurate and robust classification results than using each individual type of features. …”
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Thesis