Search Results - (( java application optimisation algorithm ) OR ( leaf optimization system algorithm ))

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  1. 1

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

    Published 2016
    “…Furthermore, most of the existing systems rely on human intervention to select certain points of the leaf to help the system align the leaf or to select the best result among a few candidates after the classification is done. …”
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  2. 2

    Study and Implementation of Data Mining in Urban Gardening by Mohana, Muniandy, Lee, Eu Vern

    Published 2019
    “…The system is essentially a three-part development, utilising Android, Java Servlets, and Arduino platforms to create an optimised and automated urban-gardening system. …”
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  3. 3

    Feature decision-making ant colony optimization system for an automated recognition of plant species by Ghasab, Mohammad Ali Jan, Khamis, Shamsul, Faruq, Mohammad, Fariman, Hessam Jahani

    Published 2015
    “…In the present paper, an expert system for automatic recognition of different plant species through their leaf images is investigated by employing the ant colony optimization (ACO) as a feature decision-making algorithm. …”
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  4. 4
  5. 5

    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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  8. 8

    Web-based expert system for material selection of natural fiber- reinforced polymer composites by Ahmed Ali, Basheer Ahmed

    Published 2015
    “…Finally, the developed expert system was deployed over the internet with central interactive interface from the server as a web-based application. As Java is platform independent and easy to be deployed in web based application and accessible through the World Wide Web (www), this expert system can be one stop application for materials selection.…”
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  9. 9

    Comparison of dose calculation algorithms model: convolution, superposition, and fast superposition in 3-D Conformal Radiotherapy (3D-CRT) treatment plan by Murat, Husain, Abdul Karim, Muhammad Khalis, Haspiharun, Hanif, Kayun, Zunaide

    Published 2019
    “…In this study, we modified protocols described in IAEATecdoc-1583, where four typical treatment techniques such as single field, multiple field, wedge field, and multi-leaf collimated (MLC) field were analysed from the system. …”
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  10. 10

    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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  11. 11

    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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  12. 12

    Image pre-processing algorithm for Ficus deltoidea Jack (Moraceae) varietal recognition: a repeated perpendicular line scanning approach by Ahmad Fakhri, Ab. Nasir, M Nordin, A Rahman, Nashriyah, Mat, Abd Rasid, Mamat, Ahmad Shahrizan, Abdul Ghani

    Published 2018
    “…Some of researchers have developed the image pre-processing algorithm to remove petiole section. However, the algorithm was developed using semi-automatic algorithm which is strongly believed to give an inaccurate feature measurement. …”
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  13. 13
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    Evaluation of multiple In Situ and remote sensing system for early detection of Ganoderma boninense infected oil palm by Ahmadi, Seyedeh Parisa

    Published 2018
    “…During the field experiments, leaf samples of healthy (T1), mildly (T2), moderately (T3) and severely-infected (T4) palms were measured using a Minolta SPAD-502 chlorophyll meter and a SC-1 leaf Porometer to obtain relative leaf chlorophyll content and stomatal conductance, respectively. …”
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