Search Results - (( leaf classification problem algorithm ) OR ( java application tree algorithm ))
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Plant recognition based on identification of leaf image using image processing / Nor Silawati Sha’ari
Published 2018“…NN such as Artificial Neural Network (ANN) and K-Nearest Neighbor (KNN) is trained in developing a classification system for agriculture purpose. ANN and KNN is applied to solve the problems in image analysis, pattern recognition and classification. …”
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Student Project -
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Leaf condition analysis using convolutional neural network and vision transformer
Published 2024“…As a result, although customers may receive an excellent interactive features programme, the backend algorithm is not optimized. This problem may discourage users from applying the program to solve plant disease problems. …”
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Deep plant: A deep learning approach for plant classification / 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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Thesis -
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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“…Beside that, classic bag of visual words algorithm (BoVW) is based on kmeans clustering and every SIFT feature belongs to one cluster and it leads to decreasing classification results. …”
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An evaluation of feature selection methods on multi-class imbalance and high dimensionality shape-based leaf image features
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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A direct ensemble classifier for learning imbalanced multiclass data
Published 2013“…In addition, the selected benchmark data, experiments and the results are useful for future research on the imbalanced multiclass classification problem. Furthermore, the DECIML framework was applied to the real world leaf classification problem based on the shape features. …”
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Study and Implementation of Data Mining in Urban Gardening
Published 2019“…Using the J48 tree algorithm implemented through WEKA API on a Java Servlet, data provided is processed to derive a health index of the plant, with the possible outcomes set to “Good,” “Okay”, or “Bad”. …”
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Mining Sequential Patterns using I-PrefixSpan
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Citation Index Journal -
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Adoption of machine learning algorithm for analysing supporters and non supporters feedback on political posts / Ogunfolajin Maruff Tunde
Published 2022“…This thesis is based on the application of sentiment classification algorithm to tweet data with the goal of classifying messages based on the polarity of sentiment towards a particular topic (or subject matter). …”
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Introducing new statistical shape based and texture feature extraction methods in the plant species recognition system
Published 2013“…The results show the outperformance of the two proposed methods for image processing and optimized classifier for classification part. As the classification result, radial basis neural networks (RBFNN), feed forward neural networks (FFNN), neural networks using genetic algorithm (NNUGA) shows 100%, 93%, 97.3% of accuracy respectively . …”
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Mining Sequential Patterns Using I-PrefixSpan
Published 2007“…In this paper, we propose an improvement of pattern growth-based PrefixSpan algorithm, called I-PrefixSpan. The general idea of I-PrefixSpan is to use the efficient data structure for general tree-like framework and separator database to reduce the execution time and memory usage. …”
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Conference or Workshop Item -
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AI powered asthma prediction towards treatment formulation: an android app approach
Published 2022“…We utilized eight robust machine learning algorithms to analyze this dataset. We found that the Decision tree classifier had the best performance, out of the eight algorithms, with an accuracy of 87%. …”
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AI powered asthma prediction towards treatment formulation : An android app approach
Published 2022“…We utilized eight robust machine learning algorithms to analyze this dataset. We found that the Decision tree classifier had the best performance, out of the eight algorithms, with an accuracy of 87%. …”
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