Search Results - data ((extraction method) OR (detection method)) algorithm
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Temporal video segmentation using squared form of Krawtchouk-Tchebichef moments
Published 2018“…TVS algorithm design is still challenging because most of the recent methods are unable to achieve robust detection for different types of transitions: hard transition (HT) and soft transition (ST). …”
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An efficient algorithm for cardiac arrhythmia classification using ensemble of depthwise Separable convolutional neural networks
Published 2020“…Using our proposed method, the four stages of ECG classification, i.e., QRS detection, preprocessing, feature extraction, and classification, were reduced to two steps only, i.e., QRS detection and classification. …”
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A fast feature extraction algorithm for image and video processing
Published 2019“…Furthermore, the proposed method is employed for shot boundary detection (SBD) applications to detect transitions in video frames. …”
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Cabbage disease detection system using k-NN algorithm
Published 2022“…Then, the segmented cabbage sample will use the GLCM method for feature extraction. It is a method of extracting second-order statistical texture features to detect diseases more efficiently. …”
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Academic Exercise -
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Fatigue Features Extraction of Road Load Time Data Using the S-Transform
Published 2013“…This technique was developed to produce shortened fatigue data for fatigue durability testing. The S-T method was applied to detect the damaging events contained in the fatigue signals due to high S-T spectrum location. …”
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Breast cancer disease classification using fuzzy-ID3 algorithm with FUZZYDBD method: automatic fuzzy database definition
Published 2021“…FUZZYDBD method, an automatic fuzzy database definition method, would be used to design the fuzzy database for fuzzification of data in the FID3 algorithm. …”
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Power line corridor vegetation encroachment detection from satellite images using retinanet and support vector machine
Published 2023“…The SVM algorithm has been used to detect high- and low-density vegetation regions from the extracted ROI. …”
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Automated threshold detection for object segmentation in colour image
Published 2016“…Most common solution of the task is the uses of threshold strategy based on trial and error method. As the method is not automated, it is time consuming and sometimes a single threshold value does not work for a series of image frames of video data. …”
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Intelligent deep machine learning cyber phishing URL detection based on BERT features extraction
Published 2022“…In this paper, a novel URL phishing detection technique based on BERT feature extraction and a deep learning method is introduced. …”
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Fast temporal video segmentation based on Krawtchouk-Tchebichef moments
Published 2020“…TVS algorithm design is still challenging because most of the recent methods are unable to achieve fast and robust detection. …”
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A guided hybrid k-means and genetic algorithm models for children handwriting legibility performance assessment / Norzehan Sakamat
Published 2021“…Size was extracted using Extreme Point Detection algorithm and Hit or Miss Transformation method was used to extract the stroke formation pattern. …”
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Abnormal Pattern Detection In Ppg Signals Using Time Series Analysis
Published 2022“…This project’s objectives are to implement rule-based algorithm method for abnormal pattern detection in PPG signals, and to investigate the accuracy and performance of rule-based algorithm in detecting the abnormal pattern. …”
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Undergraduates Project Papers -
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Edge detection and contour segmentation for fruit classification in natural environment / Khairul Adilah Ahmad
Published 2018“…Based on previous researches, most existing segmentation methods focused on a specific environment. Therefore, this research has developed an improved edge detection and contour segmentation algorithm that is able to correctly segment various objects from both indoor and outdoor images. …”
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Object-based imagery analysis for automatic urban tree species detection using high resolution satellite image
Published 2016“…The method of maximum likelihood classification and support vector machines leads to the lowest classification accuracy since these algorithms extract only the spectral information of each pixel and consequently fail to utilize spatial, color and textural information.…”
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Multi-sensor fusion and deep learning framework for automatic human activity detection and health monitoring using motion sensor data / Henry Friday Nweke
Published 2019“…Finally, compare the performances with existing multi-sensor fusion and feature extraction methods for human activity detection and health monitoring. …”
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Blotch removal using multi-level scanning, shape analysis, and meta heuristic techniques
Published 2015“…Regarding the detection, a post processing method based on a combination of pixel-based and objects-based methods was proposed. …”
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