Search Results - (( developing detection means algorithm ) OR ( java application path algorithm ))
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Smart appointment organizer for mobile application / Mohd Syafiq Adam
Published 2009“…In creating this application, NetBeans IDE 6.5and Java Micro Edition (Java ME) are used. …”
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Thesis -
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An amplitude independent muscle activity detection algorithm based on adaptive zero crossing technique and mean instantaneous frequency of the sEMG signal
Published 2017“…A new algorithm has been developed to detect the presence of muscle activities in weak and noisy sEMG signals. …”
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Conference or Workshop Item -
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Visdom: Smart guide robot for visually impaired people
Published 2025“…The system architecture integrates ROS 2 on a Raspberry Pi, with TCP/IP connectivity enabling remote operation. An Android mobile application, developed using Java and the java.net.Socket library, provides an intuitive and accessible user interface for seamless interaction with the robot. …”
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Final Year Project / Dissertation / Thesis -
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The development of a tracking algorithm for ambulance detection using squaring of RGB and HSV color processing techniques
Published 2016“…In this study, a tracking algorithm is developed by means of image processing technique in detecting ambulance. …”
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Automated Deform Detection On Automotive Body Panels Using Gradient Filtering And Fuzzy C-Mean Segmentation
Published 2016“…As a consequence, this problem is focussed to derive a lot of good-quality deform detected from the surface images. These detections should discriminate the various surface deforms when fed to suitable image processing algorithms. …”
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K-means Clustering Analysis for EEG Features of Situational Interest Detection in Classroom Learning
Published 2021“…This paper proposes a method to detect situational interest in classroom learning using k-means algorithms. …”
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Optimised content-social based features for fake news detection in social media using text clustering approach
Published 2025“…In general, the process of fake news detection was conducted in two different phases, the topic detection phase using a graph-based unsupervised clustering method based on HFPA and Markov Clustering Algorithm (MCL) called (HFPA-MCL) and the fake news detection phase using an unsupervised clustering method based on K-means algorithm. …”
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Development Of Human Skin Detection Algorithm Using Multilayer Perceptron Neural Network And Clustering Method
Published 2017“…The performance of the developed system has been compared with the existing intelligent skin detection systems. …”
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Heartbeat Anomaly Detection Method Based on Electrocardiogram using Improved Certainty Cognitive Map
Published 2023“…This research has 3 objectives To develop algorithms for detecting heart conditions as either abnormal or normal using the modified cognitive map (CM) approach, To develop detection algorithms for anomalous heart conditions based on the enhancement of Certainty Factor (CF) technique, and To evaluate and validate the effectiveness of the new proposed model specifically the Certainty Cognitive Map (CCM) for identifying heart defects. …”
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Epileptic Seizure Detection Using Singular Values And Classical Features Of EEG Signals
Published 2014“…This project aims at developing an automated epileptic seizure event detection algorithm. …”
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Final Year Project -
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A guided hybrid k-means and genetic algorithm models for children handwriting legibility performance assessment / Norzehan Sakamat
Published 2021“…The combined method is called Hybrid K-MeansCGA. Modifications of K-Means structures were done by inserting genetic algorithm operators and tuning the population. …”
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Thesis -
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Fetal heart rate monitoring during pregnancy for assessing the well-being of the fetus
Published 2018“…The resulting average accuracy is 83% for the FHR detection. The detection of the FHR from the maternal abdominal signal by the developed algorithm has also been compared with a short-term monitoring commercial instrument IFM-500 for the assessment of the reliability of the algorithm. …”
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Fetal heart rate monitoring during pregnancy for assessing the well being of the fetus
Published 2017“…The resulting average accuracy is 83% for the FHR detection. The detection of the FHR from the maternal abdominal signal by the developed algorithm has also been compared with a short-term monitoring commercial instrument IFM-500 for the assessment of the reliability of the algorithm. …”
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Proceeding Paper -
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Fetal heart rate monitoring during pregnancy for assessing the well being of the fetus
Published 2018“…The resulting average accuracy is 83% for the FHR detection. The detection of the FHR from the maternal abdominal signal by the developed algorithm has also been compared with a short-term monitoring commercial instrument IFM-500 for the assessment of the reliability of the algorithm. …”
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Robust overlapping community detection in complex networks with graph convolutional networks and fuzzy C-means
Published 2024“…Existing methods often struggle to capture both network topology and node features, leading to suboptimal overlapping community detection. In this paper, we propose an efficient method called GCNFCM, which utilizes Graph Convolutional Networks (GCNs), Fuzzy C-means (FCM), and the modularity Q algorithm for overlapping community detection. …”
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Fetal heart rate monitoring during pregnancy for assessing the well being of the fetus
Published 2017“…The resulting average accuracy is 83% for the FHR detection. The detection of the FHR from the maternal abdominal signal by the developed algorithm has also been compared with a short-term monitoring commercial instrument IFM-500 for the assessment of the reliability of the algorithm. …”
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Cabbage disease detection system using k-NN algorithm
Published 2022“…It is a method of extracting second-order statistical texture features to detect diseases more efficiently. Finally, the KNN algorithm will be used to classify the disease based on sample nature and a cabbage disease data set. …”
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Academic Exercise -
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Neural network algorithm-based fall detection modelling
Published 2020“…High recognition of developed fall detection model is very significance for the elderly to detect the falls. …”
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