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

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

“…Finally, the algorithm found, which would solve the image segmentation problem.…”
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Automatic Number Plate Recognition on android platform: With some Java code excerpts by ., Abdul Mutholib, Gunawan, Teddy Surya, Kartiwi, Mira

“…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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Real-time measurement and gait detection algorithm for motion control of active ankle foot orthosis / Aminuddin Hamid by Hamid, Aminuddin

“…This thesis proposes a real time gait phase detection system to control AAFO for rehabilitation and assist ankle motion. …”
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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

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Fault diagnostic algorithm for precut fractionation column by Heng, H. Y., Ali, Mohamad Wijayanuddin, Kamsah, Mohd. Zaki

“…The tested data is used to interpret the pattern of the chart, where fault is considered to occur if one variable is out of control limits. …”
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Two-factor authentication smart entryway using modified LBPH algorithm by Ayop, Zakiah, Othman, Nur Fadzilah, Anawar, Syarulnaziah, Wan Mohamad Rosdi, Wan Mohamad Hariz, Looi, Wei Hua

“…The system employs the Local Binary Patterns Histograms for the full face recognition algorithm and modified LBPH algorithm for occluded face detection. …”
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Enhanced grey wolf optimisation algorithm for feature selection in anomaly detection by Almazini, Hussein

“…Thus, this study proposes an enhanced binary grey wolf optimiser (EBGWO) algorithm for FS in anomaly detection to overcome the algorithm issues. …”
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A simple model-free butterfly shape-based detection (BSD) method integrated with deep learning CNN for valve stiction detection and quantification by Kamaruddin, B., Zabiri, H., Mohd Amiruddin, A.A.A., Teh, W.K., Ramasamy, M., Jeremiah, S.S.

“…In most methods for shape-based stiction detection, they rely heavily on the traditional controller output (OP) and process variable (PV) plot (i.e. …”
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Sensing texture using an artificial finger and a data analysis based on the standard deviation by Chappell, Paul H., Muridan, Norasmahan, Mohamad Hanif, N. H. H, Cranny, Andy, White, Neil M.

“…Plots for the output from the algorithm show events that correspond to the cyclic waveforms produced from the regularity of object surface patterns. …”
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A COMBINED HISTOGRAM OF ORIENTED GRADIENTS AND COMPLETED LOCAL BINARY PATTERN METHODS FOR PEOPLE COUNTING IN A DENSE CROWD SCENARIO by PARDIANSYAH, INDRATNO

“…This method used a collaborative Histogram of Oriented Gradients (HOG) and Completed Local Binary Pattern (CLBP) based on people detection algorithm to detect headshoulder region. …”
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Application Of Multi-Layer Perceptron Technique To Detect And Locate The Base Of A Young Corn Plant by Morshidi, Malik Arman

“…This information can be processed, analyzed, and transformed into inputs for a decisional algorithm that controls the sprayer nozzle action in real-time. …”
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Sensing texture using an artificial finger and a data analysis based on the standard deviation by Chappell, Paul H., Muridan, Norasmahan, Mohamad Hanif, Nik Hazrin, Cranny, Andy, White, Neil M.

“…The output from the algorithm is the frequency spectrum of a signal. Plots, from the output of the algorithm, show events that correspond to the cyclic waveforms produced from the regularity of object surface patterns. …”
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Ensemble Classifier for Recognition of Small Variation in X-Bar Control Chart Patterns by Alwan, Waseem, Ngadiman, Nor Hasrul Akhmal, Hassan, Adnan, Saufi, Syahril Ramadhan, Mahmood, Salwa

“…This study provides an improved control chart pattern recognition (CCPR) method focusing on X-bar chart patterns of small process variations using an ensemble classifier comprised of five complementing algorithms: decision tree, artificial neural network, linear support vector machine, Gaussian support vector machine, and k-nearest neighbours. …”
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Ensemble Classifier for Recognition of Small Variation in X-Bar Control Chart Patterns by Waseem Alwan, Waseem Alwan, Ngadiman, Nor Hasrul Akhmal, Hassan, Adnan, Syahril Ramadhan Saufi, Syahril Ramadhan Saufi, Mahmood, Salwa

“…This study provides an improved control chart pattern recognition (CCPR) method focusing on X-bar chart patterns of small process variations using an ensemble classifier comprised of five complementing algorithms: decision tree, artificial neural network, linear support vector machine, Gaussian support vector machine, and k-nearest neighbours. …”
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Ensemble Classifier for Recognition of Small Variation in X-Bar Control Chart Patterns by Alwan, Waseem, Ngadiman, Nor Hasrul Akhmal, Hassan, Adnan, Ramadhan Saufi, Syahril, Mahmood, Salwa

“…This study provides an improved control chart pattern recognition (CCPR) method focusing on X-bar chart patterns of small process variations using an ensemble classifier comprised of five complementing algorithms: decision tree, artificial neural network, linear support vector machine, Gaussian support vector machine, and k-nearest neighbours. …”
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Ensemble Classifier for Recognition of Small Variation in X-Bar Control Chart Patterns by Alwan, Waseem, Ngadiman, Nor Hasrul Akhmal, Hassan, Adnan, Saufi, Syahril Ramadhan, Mahmood, Salwa

“…This study provides an improved control chart pattern recognition (CCPR) method focusing on X-bar chart patterns of small process variations using an ensemble classifier comprised of five complementing algorithms: decision tree, artificial neural network, linear support vector machine, Gaussian support vector machine, and k-nearest neighbours. …”
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Ensemble Classifier for Recognition of Small Variation in X-Bar Control Chart Patterns by Waseem Alwan, Waseem Alwan, Ngadiman, Nor Hasrul Akhmal, Adnan Hassan, Adnan Hassan, Syahril Ramadhan Saufi, Syahril Ramadhan Saufi, Mahmood, Salwa

“…This study provides an improved control chart pattern recognition (CCPR) method focusing on X-bar chart patterns of small process variations using an ensemble classifier comprised of five complementing algorithms: decision tree, artificial neural network, linear support vector machine, Gaussian support vector machine, and k-nearest neighbours. …”
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Ensemble Classifier for Recognition of Small Variation in X-Bar Control Chart Patterns by Alwan, Waseem, Ngadiman, Nor Hasrul Akhmal, Hassan, Adnan, Ramadhan Saufi, Syahril, Mahmood, Salwa

“…This study provides an improved control chart pattern recognition (CCPR) method focusing on X-bar chart patterns of small process variations using an ensemble classifier comprised of five complementing algorithms: decision tree, artificial neural network, linear support vector machine, Gaussian support vector machine, and k-nearest neighbours. …”
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Ensemble Classifier for Recognition of Small Variation in X-Bar Control Chart Patterns by Alwan, Waseem, Ngadiman, Nor Hasrul Akhmal, Hassan, Adnan, Saufi, Syahril Ramadhan, Mahmood, Salwa

“…This study provides an improved control chart pattern recognition (CCPR) method focusing on X-bar chart patterns of small process variations using an ensemble classifier comprised of five complementing algorithms: decision tree, artificial neural network, linear support vector machine, Gaussian support vector machine, and k-nearest neighbours. …”
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A Bio-Inspired Behavior-Based Hybrid Framework for Ransomware Detection by Mohammed A. F. Salah, Mohd Fadzli Marhusin, Rossilawati Sulaiman