Search Results - (( optical based algorithm ) OR ( optical ((svm algorithm) OR (tree algorithm)) ))

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  1. 1

    Comparative analysis on the deployment of machine learning algorithms in the distributed brillouin optical time domain analysis (BOTDA) fiber sensor by Nordin N.D., Zan M.S.D., Abdullah F.

    Published 2023
    “…The algorithms analyzed were generalized linear model (GLM), deep learning (DL), random forest (RF), gradient boosted trees (GBT), and support vector machine (SVM). …”
    Article
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    Translating conventional wisdom on chicken comb color into automated monitoring of disease-infected chicken using chromaticity-based machine learning models by Bakar M.A.A.A., Ker P.J., Tang S.G.H., Baharuddin M.Z., Lee H.J., Omar A.R.

    Published 2024
    “…The development of the algorithms shows that Logistic Regression, SVM with Linear and Polynomial kernels performed the best with 95% accuracy, followed by SVM-RBF kernel, and KNN with 93% accuracy, Decision Tree with 90% accuracy, and lastly, SVM-Sigmoidal kernel with 83% accuracy. …”
    Article
  3. 3

    Translating conventional wisdom on chicken comb color into automated monitoring of disease-infected chicken using chromaticity-based machine learning models by Bakar, Mohd Anif A. A., Ker, Pin Jern, Tang, Shirley G. H., Baharuddin, Mohd Zafri, Lee, Hui Jing, Omar, Abdul Rahman

    Published 2023
    “…The development of the algorithms shows that Logistic Regression, SVM with Linear and Polynomial kernels performed the best with 95 accuracy, followed by SVM-RBF kernel, and KNN with 93 accuracy, Decision Tree with 90 accuracy, and lastly, SVM-Sigmoidal kernel with 83 accuracy. …”
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  4. 4

    Optimized techniques for landslide detection and characteristics using LiDAR data by Mezaal, Mustafa Ridha

    Published 2018
    “…The locations of landslides were detected accurately by employing two Machine learning classifiers, namely, SVM and RF, decision rule and hierarchal rules sets were developed by applying decision tree (DT) algorithm to provide improved landslide inventory. …”
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  5. 5

    Seeing trees from space: above-ground biomass estimates of intact and degraded montane rainforests from high-resolution optical imagery by Phua, Mui How, Ling, Zia-Yiing, David Anthony Coomes, Wilson Wong, Alexius Korom, Satoshi Tsuyuki, Keiko Ioki, Yasumasa Hirata, Hideki Saito, Gen Takao

    Published 2017
    “…The intact and degraded forests not only had different AGB but were also dissimilar in biodiversity. A tree-centric approach to carbon mapping based on high-resolution optical imagery, could be a cheap alternative to airborne laser-scanning.…”
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    Simultaneous measurement of multiple soil properties through proximal sensor data fusion: a case study by Wenjun, Ji, Adamchuk, Viacheslav I., Song, Chao Chen, Mat Su, Ahmad S., Ismail, Ashraf, Qianjun, Gan, Zhou, Shi, Biswas, Asim

    Published 2019
    “…After choosing the optimal sensor combination for each soil property, the predictive capability was compared using different data mining algorithms, including support vector machines (SVM), random forest (RF), multivariate adaptive regression splines (MARS), and regression trees (CART). …”
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    Building extraction for 3D city modelling using infused airborne LiDAR and high-resolution aerial photograph by Sani, Ojogbane Success

    Published 2021
    “…The second goal employs a deep learning(DL) algorithm to predict the best sensor for detection, either the LiDAR, optics or the fusion of the LiDAR and high-resolution aerial photography, to know which is most suitable for building detection with little or no user intervention. …”
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  13. 13

    Deep convolutional neural network processing of aerial stereo imagery to monitor vulnerable zones near power lines by Qayyum, A., Saad, N.M., Kamel, N., Malik, A.S.

    Published 2018
    “…This paper presents a cost-effective approach based on a convolutional neural network (CNN) algorithm to compute the height (depth maps) of objects proximal to power poles and transmission lines. …”
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  14. 14

    Deep convolutional neural network processing of aerial stereo imagery to monitor vulnerable zones near power lines by Qayyum, A., Saad, N.M., Kamel, N., Malik, A.S.

    Published 2018
    “…This paper presents a cost-effective approach based on a convolutional neural network (CNN) algorithm to compute the height (depth maps) of objects proximal to power poles and transmission lines. …”
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  15. 15

    Delineating mangrove forest zone using spectral reflectance by Abdul Whab @ Abdul Wahab,, Zulfa

    Published 2020
    “…To identify individual mangrove species, in-situ measurement was conducted using handheld optical sensors of spectroradiometer to examine the most effective wave bands and spectral regions for discriminating mangrove tree species. …”
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  16. 16

    Detection of vegetation encroachment in power transmission line corridor from satellite imagery using support vector machine: A features analysis approach by Mahdi Elsiddig Haroun F., Mohamed Deros S.N., Bin Baharuddin M.Z., Md Din N.

    Published 2023
    “…Color; Electric lines; Electric power transmission; Optical radar; Satellite imagery; Space-based radar; Synthetic aperture radar; Transmissions; Vector spaces; Vegetation; Classification accuracy; Environmental challenges; Gray level co occurrence matrix(GLCM); Light detection and ranging; Power interruptions; Statistical moments; Support vector machine algorithm; Vegetation density; Support vector machines…”
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    Accounting Information Systems Genetic Algorithms for All-Optical Shared Fiber-Delay-Line Packet Switches by Liew, S.Y., Wong, E.S.K.

    Published 2009
    “…In the first algorithm, packet scheduling is formulated as a tree-searching problem. …”
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    Specific heat capacity extraction of soybean oil/mxene nanofluids using optimized long short-term memory by Qazani, Mohammad Reza Chalak, Aslfattahi, Navid, Kulish, Vladimir Vladimirovich, Asadi, Houshyar, Schmirler, Michal, Zakarya, Muhammad, Alizadehsani, Roohallah, Haleem, Muhammad, Kadirgama, Kumaran

    Published 2024
    “…Researchers are turning to nanofluids in PV/T hybrid systems for enhanced efficiency due to nanoparticle dispersion, improving thermal and optical properties over conventional fluids. Three different concentrations of formulated soybean oil based MXene nanofluids are considered 0.025, 0.075 and 0.125 wt.%. …”
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