Search Results - (( java segmentation using algorithm ) OR ( pattern detection context algorithm ))

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  1. 1
    Image clustering comparison of two color segmentation techniques

    Image clustering comparison of two color segmentation techniques by Subramaniam, Kavitha Pichaiyan

    Published 2010
    “…Finally, the algorithm found, which would solve the image segmentation problem.…”
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  2. 2
    Anomaly detection through spatio-temporal context modeling in crowded scenes

    Anomaly detection through spatio-temporal context modeling in crowded scenes by Lu, T., Wu, L., Ma, X., Shivakumara, P., Tan, C.L.

    Published 2014
    “…The proposed framework essentially turns the anomaly detection process into two parts, namely, motion pattern representation and crowded context modeling. …”
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  3. 3
    Automatic Number Plate Recognition on android platform: With some Java code excerpts

    Automatic Number Plate Recognition on android platform: With some Java code excerpts by ., Abdul Mutholib, Gunawan, Teddy Surya, Kartiwi, Mira

    Published 2016
    “…On the other hand, the traditional algorithm using template matching only obtained 83.65% recognition rate with 0.97 second processing time. …”
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  4. 4
    Development of seven segment display recognition using TensorFlow on Raspberry Pi

    Development of seven segment display recognition using TensorFlow on Raspberry Pi by Gunawan, Teddy Surya, Mohammad Reduwan, Haque, Yaacob, Mashkuri, Mohamed Azmin, Nor Fadhillah, Ismail, Nanang, Ismail, Md Yusof, Kartiwi, Mira, A. Rahman, Azhar

    Published 2022
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  5. 5
    An Improved Artificial Dendrite Cell Algorithm for Abnormal Signal Detection

    An Improved Artificial Dendrite Cell Algorithm for Abnormal Signal Detection by Mohamad Mohsin, Mohamad Farhan, Abu Bakar, Azuraliza, Hamdan, Abdul Razak, Abdul Wahab, Mohd Helmy

    Published 2018
    “…This causes the DCA fails to detect new data points if the pattern has distinct behavior from previous information and affects detection accuracy. …”
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  6. 6
    An adaptive anomaly threshold in artificial dendrite cell algorithm

    An adaptive anomaly threshold in artificial dendrite cell algorithm by Mohamad Mohsin, Mohamad Farhan, Abu Bakar, Azuraliza, Hamdan, Abdul Razak

    Published 2017
    “…The dendrite cell algorithm (DCA) relies on the multi-context antigen value (MCAV) to determine the abnormality of a record by comparing it with anomaly threshold.In practice, the threshold is pre-determined before mining based on previous information and the existing MCAV is inefficient when expose to extreme values.This causes the DCA fails to detect unlabeled data if the new pattern distinct from previous information and reduces the detection accuracy.This paper proposed an adaptive anomaly threshold for DCA using the statistical cumulative sum (CUSUM) with the aim to improve its detection capability.In the proposed approach, the MCAV were normalized with upper CUSUM and the new anomaly threshold was calculated during run time by considering the acceptance value and min MCAV.From the experiments towards 12 datasets, the new version of DCA generated a better detection result than its previous version in term of sensitivity, specificity, false detection rate, and accuracy.…”
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  7. 7
    An improved artificial dendrite cell algorithm for abnormal signal detection

    An improved artificial dendrite cell algorithm for abnormal signal detection by Mohamad Mohsin, Mohamad Farhan, Abu Bakar, Azuraliza, Hamdan, Abdul Razak, Abdul Wahab, Mohd Helmy

    Published 2018
    “…This causes the DCA fails to detect new data points if the pattern has distinct behavior from previous information and affects detection accuracy. …”
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  8. 8
    Toward heterogeneous computing to facilitate sequential OLAP real-time applications

    Toward heterogeneous computing to facilitate sequential OLAP real-time applications by Hameed, Shihab A., Habaebi, Mohamed Hadi, Alzeini, Haytham I. M.

    Published 2016
    “…The optimized algorithm is dedicated to detect patterns over parallel data streams in Real-Time. …”
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  9. 9
    Deviation detection in text using conceptual graph interchange format and error tolerance dissimilarity function

    Deviation detection in text using conceptual graph interchange format and error tolerance dissimilarity function by Kamaruddin, Siti Sakira, Hamdan, Abdul Razak, Abu Bakar, Azuraliza, Mat Nor, Fauzias

    Published 2012
    “…We propose a novel error tolerance dissimilarity algorithm to detect deviations in the CGIFs. We evaluate our method in the context of analyzing real world financial statements for identifying deviating performance indicators. …”
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  10. 10
    iBUST: An intelligent behavioural trust model for securing industrial cyber-physical systems

    iBUST: An intelligent behavioural trust model for securing industrial cyber-physical systems by Azad, Saiful, Mahmud, Mufti, Kamal Zuhairi, Zamli, Kaiser, M. Shamim, Jahan, Sobhana, Razzaque, Md Abdur

    Published 2024
    “…These threats can largely be tackled by employing a Trust Management Model (TMM) by exploiting the behavioural patterns of nodes to identify their trust class. In this context, ML-based models are best suited due to their ability to capture hidden patterns in data, learning and improving the pattern detection accuracy over time to counteract and tackle threats of a dynamic nature, which is absent in most of the conventional models. …”
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  11. 11
    Toward Predicting Student�s Academic Performance Using Artificial Neural Networks (ANNs)

    Toward Predicting Student�s Academic Performance Using Artificial Neural Networks (ANNs) by Baashar Y., Alkawsi G., Mustafa A., Alkahtani A.A., Alsariera Y.A., Ali A.Q., Hashim W., Tiong S.K.

    Published 2023
    “…This study also attempts to capture a pattern of the most used ANN techniques and algorithms. …”
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  12. 12
    Assessment of crops healthiness via deep learning approach: Python / Mohamad Amirul Asyraf Mohd Ramli

    Assessment of crops healthiness via deep learning approach: Python / Mohamad Amirul Asyraf Mohd Ramli by Mohd Ramli, Mohamad Amirul Asyraf

    Published 2023
    “…Detecting healthy crops using Python in the context of an analysis project has emerged as an approach that speeds up a process to find out the current state of crops. …”
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  13. 13
    Analyzing UiTMCTKKT vehicle utilization and travel pattern using predictive analytics

    Analyzing UiTMCTKKT vehicle utilization and travel pattern using predictive analytics by Syed Mohamad, Sharifah Masyitah

    Published 2025
    “…This indicates its strong ability to model temporal and operational patterns in the dataset accurately. The dashboard enabled users to trace mileage, detect underused vehicles, and identify periods suitable for vehicle maintenance. …”
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  14. 14
    Data Classification and Its Application in Credit Card Approval

    Data Classification and Its Application in Credit Card Approval by Thai , VinhTuan

    Published 2004
    “…This project is involved with identification of the available algorithms used in data classification and the implementation of C4.5 decision tree induction algorithm in solving the data classifying task. …”
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  15. 15
    Wifi-based location-independent human activity recognition and localization using deep learning

    Wifi-based location-independent human activity recognition and localization using deep learning by Abuhoureyah, Fahd Saad Amed

    Published 2024
    “…Second, Multi-head Attention Mechanism Networks capture intricate patterns in Channel State Information (CSI) data, enhancing recognition accuracy for human activities detected through WiFi signals. …”
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  16. 16
    Robust tweets classification using arithmetic optimization with deep learning for sustainable urban living

    Robust tweets classification using arithmetic optimization with deep learning for sustainable urban living by Hamza, Manar Ahmed, Hassan Abdalla Hashim, Aisha, Motwakel, Abdelwahed, Elhameed, Elmouez Samir Abd, Osman, Mohammed, Kumar, Arun, Singla, Chinu, Munjal, Muskaan

    Published 2024
    “…DL techniques like recurrent neural network (RNN) or transformer- based frameworks like BERT are used to mechanically learn difficult linguistic patterns and contextual info from tweet data. These techniques able to capture subtleties of language with sarcasm, sentiment, and context-specific meanings and making them suitable for tasks like sentiment analysis or topic classification in realm of social media. …”
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