Search Results - optical ((((mode algorithm) OR (tree algorithm))) OR (model algorithm))*

Analysis of Motion Detection of Breast Tumor Based on Tissue Elasticity From B Mode Ultrasound Images Using Gradient Method Optical Flow Algorithm by Shuib, FMM, Abdulrahim, K, Zulkifli, Z, Marinah Othman

Analysis of motion detection of breast tumor based on tissue elasticity from B mode ultrasound images using gradient method optical flow algorithm by Shuib F.M.M., Othman, M., Abdul Rahim, K., Zulkifli Z.

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A survey on signal processing methods in fiber optic sensor for oxidized carbon steel by Jaafar, N.S.M., Aziz, I.A., Jaafar, J., Mahmood, A.K., Gilal, A.R.

“…We selected these two algorithms because our focus is on these methods. Firstly, this paper exhibits the inner workings of each algorithm both in the original authorsâ�� intuition and the mathematical model utilized. …”
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A survey on signal processing methods in fiber optic sensor for oxidized carbon steel by Jaafar, N.S.M., Aziz, I.A., Jaafar, J., Mahmood, A.K., Gilal, A.R.

“…We selected these two algorithms because our focus is on these methods. Firstly, this paper exhibits the inner workings of each algorithm both in the original authorsâ�� intuition and the mathematical model utilized. …”
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Improving the performance of hierarchical bandwidth allocation for upstream EPON by Sadon S.Kh., Din N.Md., Al-Mansoori M.H., Yaacob M.B., Radzi N.A.M., Mustafa I.S., Majid M.S.B.A.

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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

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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.

“…The algorithms analyzed were generalized linear model (GLM), deep learning (DL), random forest (RF), gradient boosted trees (GBT), and support vector machine (SVM). …”

Traditional and higher order sliding mode control of MEMS optical switch by Keramati, Ehsan

“…Both traditional sliding mode (TSM) and higher order sliding mode (HOSM) algorithms have been applied to the system. …”
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Particle swarm optimization on threshold exponential gain of stimulated Brillouin scattering in single mode fibers. by Al-Asadi, H. A., Al-Mansoori, M. H., Hitam, Salasiah, Saripan, M. Iqbal, Mahdi, Mohd Adzir

“…We implement a particle swarm optimization (PSO) algorithm to characterize stimulated Brillouin scattering phenomena in optical fibers. …”
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QoS Forwarding on the Optical Internet Backbone Area Using R-IWDMTC Protocol by Addie Irawan, Hashim, R. Badlishah, Ahmad

“…Discrete event simulator called OMNeT++ is used for modelling and analysis purposes and model of optical internet backbone area has been developed. …”
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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

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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

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Dynamic evolving neural fuzzy inference system equalization scheme in mode division multiplexing for optical fiber transmission by Noori, Awab

“…The performance of optical mode division multiplexing (MDM) is affected by intersymbol interference (ISI) from nonlinear channel impairments arising from higherorder mode coupling and modal dispersion in multimode fiber. …”
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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.

“…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. …”

Accounting Information Systems Genetic Algorithms for All-Optical Shared Fiber-Delay-Line Packet Switches by Liew, S.Y., Wong, E.S.K.

“…In the first algorithm, packet scheduling is formulated as a tree-searching problem. …”
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QR factorization equalisation scheme for mode devision multiplexing transmission in fibre optics by Abbas, Sharafal-Deen Abdulkadhum

“…Mode division multiplexing is introduced as a new emerging technique to improve the optical network capacity by the use of the light modes as individual channels. …”
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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, Mohd Anif A. A., Ker, Pin Jern, Tang, Shirley G. H., Baharuddin, Mohd Zafri, Lee, Hui Jing, Omar, Abdul Rahman

“…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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A preliminary lightweight random forest approach-based image classification for plant disease detection by Mashitah Ibrahim, Muzaffar Hamzah, Mohammad Fadhli Asli

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Application of optimized higher order sliding mode control on MEMS optical switch by Keramati, Ehsan, Teimoortashloo, Mazdak, Mohd Noor, Samsul Bahari

“…This paper presents the results of an optimised Higher Order Sliding Mode (HOSM) position controller design. The algorithm requires time derivatives of the sliding variable. …”
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Building extraction for 3D city modelling using infused airborne LiDAR and high-resolution aerial photograph by Sani, Ojogbane Success

“…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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