Search Results - (( optical burst algorithm ) OR ( optical tree algorithm ))

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  1. 1
    Quality-of-service provisioning using hierarchical scheduling in optical burst switched network.

    Quality-of-service provisioning using hierarchical scheduling in optical burst switched network. by Sam, S. M., Fisal, Norsheila, Ariffin, S. H. S.

    Published 2007
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  2. 2
    Parallel Optical Burst Switching (POBS) for Ultra-Dense WDM (U-DWDM) systems

    Parallel Optical Burst Switching (POBS) for Ultra-Dense WDM (U-DWDM) systems by Abdelouahab A., Abbou F.M., Ewe H.T.

    Published 2023
    “…This paper introduces, as a variant of OBS, a new optical switching strategy for Ultra-Dense WDM (U-DWDM), named Parallel Optical Burst Switching (POBS). …”
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  3. 3
    An Adaptive Error Correction Scheme For Synchronous Digital Hierarchy-Based Wavelength Division Multiplexed Optical Network

    An Adaptive Error Correction Scheme For Synchronous Digital Hierarchy-Based Wavelength Division Multiplexed Optical Network by Cheah, Cheng Lai

    Published 2007
    “…In optical communications there are a variety of noise and distortion sources which can cause errors. …”
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  4. 4
    Adaptive waveband granularity algorithm in parallel optical burst switching (AWAGA-POBS)

    Adaptive waveband granularity algorithm in parallel optical burst switching (AWAGA-POBS) by Hussein Ahmed Ali

    Published 2023
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  5. 5
    Accounting Information Systems Genetic Algorithms for All-Optical Shared Fiber-Delay-Line Packet Switches

    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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  6. 6
    Seeing trees from space: above-ground biomass estimates of intact and degraded montane rainforests from high-resolution optical imagery

    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
    “…We used the dimensions of tree crowns detected in the imagery to estimate above-ground biomasses (AGBs) of individual trees and plots. …”
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  7. 7
    QoS Forwarding on the Optical Internet Backbone Area Using R-IWDMTC Protocol

    QoS Forwarding on the Optical Internet Backbone Area Using R-IWDMTC Protocol by Addie Irawan, Hashim, R. Badlishah, Ahmad

    Published 2006
    “…(Extended via Multi-protocol Label Switching (MPLS)) provides connection-oriented setup and multicast tree construction control for Optical Internet data forwarding in the network backbone area. …”
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  8. 8
    Comparative analysis on the deployment of machine learning algorithms in the distributed brillouin optical time domain analysis (BOTDA) fiber sensor

    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). …”
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  9. 9
    Combining data mining algorithm and object-based image analysis for detailed urban mapping of hyperspectral images

    Combining data mining algorithm and object-based image analysis for detailed urban mapping of hyperspectral images by Hamedianfar, Alireza, Mohd Shafri, Helmi Zulhaidi, Mansor, Shattri, Ahmad, Noordin

    Published 2014
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  10. 10
    Integrated approach using data mining-based decision tree and object-based image analysis for high-resolution urban mapping of WorldView-2 satellite sensor data

    Integrated approach using data mining-based decision tree and object-based image analysis for high-resolution urban mapping of WorldView-2 satellite sensor data by Hamedianfar, Alireza, Mohd Shafri, Helmi Zulhaidi

    Published 2016
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  11. 11
    Translating conventional wisdom on chicken comb color into automated monitoring of disease-infected chicken using chromaticity-based machine learning models

    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. …”
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  12. 12
    Delineating mangrove forest zone using spectral reflectance

    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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  13. 13
    Comparison of fusion of different algorithms in mapping of Melaleuca forest in Marang district, Malaysia

    Comparison of fusion of different algorithms in mapping of Melaleuca forest in Marang district, Malaysia by Saberioon, Mohammadmehdi, Mardan, Makhdzir, Nordin, Laili, Mohd Sood, Alias

    Published 2011
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  14. 14
    Translating conventional wisdom on chicken comb color into automated monitoring of disease-infected chicken using chromaticity-based machine learning models

    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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  15. 15
    Deep convolutional neural network processing of aerial stereo imagery to monitor vulnerable zones near power lines

    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
    “…© 2018 Society of Photo-Optical Instrumentation Engineers (SPIE).…”
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  16. 16
    Deep convolutional neural network processing of aerial stereo imagery to monitor vulnerable zones near power lines

    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
    “…© 2018 Society of Photo-Optical Instrumentation Engineers (SPIE).…”
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  17. 17
    A novel selection of optimal statistical features in the DWPT domain for discrimination of ictal and seizure‑free electroencephalography signals

    A novel selection of optimal statistical features in the DWPT domain for discrimination of ictal and seizure‑free electroencephalography signals by Ong, Pauline, Zainuddin, Zarita, Kee, Huong Lai

    Published 2017
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  18. 18
    Building extraction for 3D city modelling using infused airborne LiDAR and high-resolution aerial photograph

    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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  19. 19
    Automatic extraction of digital terrain model and Building Footprint from airborne LiDAR data using rule-based learning techniques

    Automatic extraction of digital terrain model and Building Footprint from airborne LiDAR data using rule-based learning techniques by Jifroudi, Hamidreza Maskani

    Published 2021
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  20. 20
    Optimized techniques for landslide detection and characteristics using LiDAR data

    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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