Search Results - (( java implementation path algorithm ) OR ( using modality learning algorithm ))

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  1. 1

    Heavy Transportation Shortest Route using Dijkstra’s algorithm (HETRO) / Nurul Aqilah Ahmad Nezer by Ahmad Nezer, Nurul Aqilah

    Published 2017
    “…The development tools used in developing this project is NetBeans by using Java for the implementation of the coding. The methodology that used for developing this system is the Dijkstra’s algorithm. …”
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    Thesis
  2. 2

    Embedded system for indoor guidance parking with Dijkstra’s algorithm and ant colony optimization by Mohammad Ata, Karimeh Ibrahim

    Published 2019
    “…BST inserts the nodes in the way that the Dijkstra’s can find the empty parking in fastest way. Dijkstra’s algorithm initials the paths to finding the shortest path while ACO optimizes the paths. …”
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    Thesis
  3. 3

    Path planning for unmanned aerial vehicle (UAV) using rotated accelerated method in static outdoor environment by Shaliza Hayati A. Wahab, Nordin Saad, Azali Saudi, Ali Chekima

    Published 2021
    “…In this study, a fast iterative method known as Rotated Successive Over-Relaxation (RSOR) is introduced. The algorithm is implemented in a self-developed 2D Java tool, UAV Planner. …”
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    Article
  4. 4

    Smart appointment organizer for mobile application / Mohd Syafiq Adam by Adam, Mohd Syafiq

    Published 2009
    “…The main component of this prototype is the use of Dijkstra algorithm to compute the shortest path from source of appointment to the 6 points of destinations within UiTM Shah Alam. …”
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    Thesis
  5. 5

    Learning a deeply supervised multi-modal RGB-D embedding for semantic scene and object category recognition by Mohd Zaki, Hasan Firdaus, Shafait, Faisal, Mian, Ajmal

    Published 2017
    “…This technique motivates bilateral transfer learning between the modalities by taking the outer product of each feature extractor output. …”
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    Article
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    Adaptive Neuro Fuzzy Inference System (ANFIS) and Artificial Neural Networks (ANNs) for structural damage identification by Hakim, S.J.S., Abdul Razak, H.

    Published 2013
    “…However the proposed ANFIS architecture using hybrid learning algorithm was found to perform better than the multilayer feedforward ANN which learns using the backpropagation algorithm. …”
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    Article
  8. 8

    Operational structural damage identification using de-noised modal feature in machine learning / Chen Shilei by Chen , Shilei

    Published 2021
    “…Meanwhile, the unsupervised learning method using PCA-WCC features is good at detecting unknown damage, and is sensitive to low-severity damage. …”
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    Thesis
  9. 9

    Damage identification using experimental modal analysis and adaptive neuro-fuzzy interface system (ANFIS) by Hakim, S.J.S., Razak, H.A.

    Published 2012
    “…The adaptive neuro-fuzzy inference system (ANFIS) is a process for mapping from a given input to a single output using the fuzzy logic and neuro-adaptive learning algorithms. …”
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    Conference or Workshop Item
  10. 10

    Development of damage identification scheme using de-noised modal frequency response function data with artificial neural network / Mohamad Izzudin Hussein Shah by Mohamad Izzudin , Hussein Shah

    Published 2018
    “…Multilayer Perceptron (MLP) with backpropagation learning algorithm ANN is used in this study. Moreover, this study needs to minimize the number of samples used by reducing number of sensors and frequency range used without affecting the performance accuracy. …”
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    Thesis
  11. 11

    Data mining for structural damage identification using hybrid artificial neural network based algorithm for beam and slab girder / Meisam Gordan by Meisam , Gordan

    Published 2020
    “…In the modeling phase, amongst all DM algorithms, the applicability of machine learning, artificial intelligence and statistical data mining techniques were examined using Support Vector Machine (SVM), Artificial Neural Network (ANN) and Classification and Regression Tree (CART) to detect the hidden patterns in vibration data. …”
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    Thesis
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    Partitional clustering algorithms for highly similar and sparseness y-short tandem repeat data / Ali Seman by Seman, Ali

    Published 2013
    “…The idea was incorporated into a new algorithm called, k-Approximate Modal Haplotypes (&-AMH) algorithm. …”
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    Thesis
  14. 14

    Data fusion and multiple classifier systems for human activity detection and health monitoring: Review and open research directions by Nweke, Henry Friday, Teh, Ying Wah, Mujtaba, Ghulam, Al-Garadi, Mohammed Ali

    Published 2019
    “…These sensors are pre-processed and different feature sets such as time domain, frequency domain, wavelet transform are extracted and transform using machine learning algorithm for human activity classification and monitoring. …”
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    Article
  15. 15

    Recent Automatic Segmentation Algorithms of MRI Prostate Regions: A Review by Khan, Z., Yahya, N., Alsaih, K., Al-Hiyali, M.I., Meriaudeau, F.

    Published 2021
    “…This survey reviewed 22 machine learning and 88 deep learning-based segmentation of prostate MRI papers, including all MRI modalities. …”
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    Article
  16. 16

    Recent Automatic Segmentation Algorithms of MRI Prostate Regions: A Review by Khan, Z., Yahya, N., Alsaih, K., Al-Hiyali, M.I., Meriaudeau, F.

    Published 2021
    “…This survey reviewed 22 machine learning and 88 deep learning-based segmentation of prostate MRI papers, including all MRI modalities. …”
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    Article
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    Revolutionizing video analytics: a review of action recognition using 3D by Jeddah, Yunusa Mohammed, Hassan Abdalla Hashim, Aisha, Khalifa, Othman Omran, Ibrahim, Adamu Abubakar

    Published 2024
    “…This paper provides an overview of recent research in 3D video action recognition, concentrating on different deep learning architectures, self-supervised learning, graph-based methods, fewshot and zero-shot learning, cross-modal action understanding, and model interpretability. …”
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    Article
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    Human hearing disorder recognition model using eeg-aep based signal by Md Nahidul, Islam

    Published 2022
    “…Then, the extracted feature was classified using machine learning and deep learning algorithms. …”
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    Thesis