Search Results - (( data reduction methods algorithm ) OR ( leaf optimization method algorithm ))

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  1. 1
    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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  2. 2
    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
    “…Besides, existing leaf disease detection programs do not provide an optimized user’s experience. …”
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  3. 3
    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
    “…Then, based on the characteristics of each species, decision making is done by means of ant colony optimisation as a search algorithm to return the optimal subset of features regarding the related species. …”
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  4. 4
    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
    “…Moreover, instead of concatenating feature vectors together and send to classifier, sparse coding and dictionary learning methods are used and instead of considering all features as one view (visual feature), K-SVD algorithm that is one of the famous algorithms for sparse representation is optimized and developed to multi-view model.The experimental results prove that the proposed methods has improved accuracy by 53.77% compared to concatenating features and classic K-SVD dictionary learning model as well.…”
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  5. 5
    Feature and Instances Selection for Nearest Neighbor Classification via Cooperative PSO

    Feature and Instances Selection for Nearest Neighbor Classification via Cooperative PSO by Sharifah Sakinah, Syed Ahmad

    Published 2014
    “…The reduction method contains two techniques, namely features reduction and data reduction which are commonly applied to a classification problem. …”
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  6. 6
    Towards lowering computational power in IoT systems: Clustering algorithm for high-dimensional data stream using entropy window reduction

    Towards lowering computational power in IoT systems: Clustering algorithm for high-dimensional data stream using entropy window reduction by Alkawsi G., Al-amri R., Baashar Y., Ghorashi S., Alabdulkreem E., Kiong Tiong S.

    Published 2024
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  7. 7
    Real-time time series error-based data reduction for internet-of-things applications

    Real-time time series error-based data reduction for internet-of-things applications by Wong, Siaw Ling

    Published 2018
    “…There are many time series data reduction methods, ranging from primitive data aggregation such as Rate of Change to sophisticated compression algorithms. …”
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  8. 8
    An Alternative Algorithm for Soft Set Parameter Selection using Special Order

    An Alternative Algorithm for Soft Set Parameter Selection using Special Order by Mohammed, Mohammed Adam Taheir, Wan Maseri, Wan Mohd, Ruzaini, Abdullah Arshah, Mungad, M., Sutoyo, Edi, Chiroma, Haruna

    Published 2015
    “…This paper proposed a parameter reduction algorithm, known as 3C algorithm, to circumvent the false frequent object in reduction. …”
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  9. 9
    Numerical Integration And Data Reduction For Application In Photometry

    Numerical Integration And Data Reduction For Application In Photometry by Chew, Tong Fatt

    Published 2003
    “…In this thesis, an algorithm based on a local interpolation scheme called the Average Angle Method was developed for numerical integration and data reduction of photometric data, and in general, for any data set sharing similar characteristics as the luminous intensity data The new interpolation scheme interpolates discrete data with piecewise cubic polynomials having a CI continuity in the interior. knots. …”
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  10. 10
    Network reconfiguration and control for loss reduction using genetic algorithm

    Network reconfiguration and control for loss reduction using genetic algorithm by Jawad, Mohamed Hassan Izzaldeen

    Published 2010
    “…In this work a feeder reconfiguration algorithm is presented for the purpose of power loss reduction in distribution networks. …”
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  11. 11
    Attribute reduction based scheduling algorithm with enhanced hybrid genetic algorithm and particle swarm optimization for optimal device selection

    Attribute reduction based scheduling algorithm with enhanced hybrid genetic algorithm and particle swarm optimization for optimal device selection by Nwogbaga, Nweso Emmanuel, Latip, Rohaya, Affendey, Lilly Suriani, Abdul Rahiman, Amir Rizaan

    Published 2022
    “…Then canonical Polyadic decomposition-based attribute reduction is applied to the offload-able task to reduce the data size. …”
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  12. 12
    Classification of basal stem rot disease in oil palm using dielectric spectroscopy

    Classification of basal stem rot disease in oil palm using dielectric spectroscopy by Al-Khaled, Al-Fadhl Yahya Khaled

    Published 2018
    “…An analysis was done to see the effect of implementing different data reduction algorithms in classifying BSR disease. …”
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  13. 13
    An Improve k-NN Classifier using Similarity Distance Plot-Data Reduction and Dask for Big Datasets

    An Improve k-NN Classifier using Similarity Distance Plot-Data Reduction and Dask for Big Datasets by Abdul Muqtasid, Rushdi

    Published 2025
    “…To accommodate big-scale data, the method integrates a parallel computing framework, Dask, during both the reduction and classification processes. …”
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  14. 14
    HDRA: A Haybird Data Reduction and Routing Algorithm

    HDRA: A Haybird Data Reduction and Routing Algorithm by Hussein, M. K., Marghescu, Ion, A. M. Alduais, Nayef

    Published 2024
    “…Consequently, this study introduces a Hybrid Data Reduction and Routing Algorithm (HDRA). The principal aim of HDRA is to prolong the lifespan of clusterbased WSNs. …”
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  15. 15
    Enhanced dimensionality reduction methods for classifying malaria vector dataset using decision tree

    Enhanced dimensionality reduction methods for classifying malaria vector dataset using decision tree by Arowolo, Micheal Olaolu, Adebiyi, Marion Olubunmi, Adebiyi, Ayodele Ariyo

    Published 2021
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  16. 16
    HDRA: A Haybird Data Reduction and Routing Algorithm

    HDRA: A Haybird Data Reduction and Routing Algorithm by M. K. Hussein, M. K. Hussein, Ion Marghescu, Ion Marghescu, Nayef A. M. Alduais, Nayef A. M. Alduais

    Published 2024
    “…Consequently, this study introduces a Hybrid Data Reduction and Routing Algorithm (HDRA). The principal aim of HDRA is to prolong the lifespan of clusterbased WSNs. …”
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  17. 17
    Document classification based on kNN algorithm by term vector space reduction

    Document classification based on kNN algorithm by term vector space reduction by Moldagulova A., Sulaiman R.B.

    Published 2023
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  18. 18
    New Learning Models for Generating Classification Rules Based on Rough Set Approach

    New Learning Models for Generating Classification Rules Based on Rough Set Approach by Al Shalabi, Luai Abdel Lateef

    Published 2000
    “…Two different models for learning in data sets were proposed based on two different reduction algorithms. …”
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  19. 19
    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
    “…They look for the procedures or algorithms that maximize the use of leaf databases for plant predictive modelling, but this results in leaf features which are liable to change with different leaf data and feature extraction techniques. …”
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  20. 20
    Enhancing battery state of charge estimation through hybrid integration of barnacles mating optimizer with deep learning

    Enhancing battery state of charge estimation through hybrid integration of barnacles mating optimizer with deep learning by Zuriani, Mustaffa, Mohd Herwan, Sulaiman

    “…In response to the growing importance of SoC estimation, this study introduces a hybrid approach called the Barnacles Mating Optimizer with Deep Learning (BMO-DL) for SoC of Nissan Leaf batteries. …”
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