Search Results - (( its application based algorithm ) OR ( pattern detection method algorithm ))
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1
Algorithm enhancement for host-based intrusion detection system using discriminant analysis
Published 2004“…Anomaly detection algorithms model normal behavior. Anomaly detection models compare sensor data to normal patterns learned from the training data by using statistical method and try to detect activity that deviates from normal activity. …”
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Fraud detection in telecommunication using pattern recognition method / Mohd Izhan Mohd Yusoff
Published 2014“…The said algorithm uses similarity coefficient to classify the real data based on the log-likelihood function and it’s extended to detect incoming fraud calls as suspected by the telecommunication company. …”
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Pengesanan minutiae imej cap jari berskala kelabu menggunakan algoritma susuran batas
Published 2002“…Thus, Maio and Maltoni (1997) proposed a method to detect minutiae in gray scale fingerprint images based on ridge line following algorithm, which is to trail the ridge line according to the fingerprint directional image. …”
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Identifying melanoma characteristics using directional imaging algorithm and convolutional neural network on dermoscopic images / Mohammad Asaduzzaman Rasel
Published 2024“…Several imaging, computer vision, and pattern recognition algorithms are employed to describe five dermoscopic features. …”
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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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Ensemble based categorization and adaptive model for malware detection
Published 2011“…Current malware detection method involved string search algorithm which based on the pattern detection. …”
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Diabetic retinopathy detection using fusion of textural and optimized convolutional neural network features / Uzair Ishtiaq
Published 2024“…Combining Local Binary Patterns (LBP) based texture features and deep learning features resulted in the creation of the fused features vector which was then optimized using Binary Dragonfly Algorithm (BDA) and Sine Cosine Algorithm (SCA). …”
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Defect detection based on extreme edge of defective region histogram
Published 2018“…Experimental results of the proposed method show that the proposed method outperforms the current methods in terms of defect detection.…”
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Adaptive edge detection and image filtering using light sensor
Published 2005“…Edge detection plays a vital role in image processing. Detected edge can be used for feature analysis, pattern analysis, frequency analysis, and etc. however the result of this analysis subjects to changes in surrounding light intensity. …”
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Enhancing data integrity in internet of things-based healthcare applications: A visualization approach for duplicate detection
Published 2025“…These findings highlight the value of visualization as a preliminary data quality assessment tool and suggest future integration with advanced detection algorithms to enhance robustness and scalability.…”
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Image watermarking optimization algorithms in transform domains and feature regions
Published 2012“…A series of training patterns are constructed by employing between two images.Moreover,the work takes accomplishing maximum robustness and transparency into consideration.HPSO method is used to estimate the multiple parameters involved in the model. …”
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Maize leaf disease detection and classification using Convolutional Neural Network (CNN) / Syafiqah Amir
Published 2023“…The labelled dataset is then used to create and train a CNN architecture which define the type of the leaf based on its category. The dataset used in this project consist of 800 images of four category of leaf achieved 90 percent of accuracy by using the CNN algorithm.…”
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Enhancing data integrity in internet of things-based healthcare applications: a visualization approach for duplicate detection
Published 2025“…These findings highlight the value of visualization as a preliminary data quality assessment tool and suggest future integration with advanced detection algorithms to enhance robustness and scalability…”
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Enhanced faster region-based convolutional neural network for oil palm tree detection
Published 2021“…This study proposed a new deep learning method based on Faster RCNN for oil palm tree detection and counting. …”
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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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Integrated geophysical, hydrogeochemical and artificial intelligence techniques for groundwater study in the Langat Basin, Malaysia / Mahmoud Khaki
Published 2014“…The results learned from the resistivity survey confirmed the pattern of a continuous structure of layers, as detected from the borehole and geological information. …”
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A study on advanced statistical analysis for network anomaly detection
Published 2005“…Anomaly detection algorithms model normal behavior. Anomaly detection models compare sensor data to normal patterns learned from the training data by using statistical method and try to detect activity that deviates from normal activity. …”
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Autonomous anomaly detection using density-based features in streaming data / Muhammmad Yunus Iqbal Basheer
Published 2023“…Hence, it is critical for an anomaly detection algorithm to detect data anomalies patterns. …”
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Classification and detection of intelligent house resident activities using multiagent
Published 2013“…The intelligent home research requires understanding of the human behavior and recognizing patterns of activities of daily living (ADL).However instead of understand the psychosomatic nature of human early projects in this area simply employed intelligence to the household appliance.This paper proposed an algorithm for detecting ADL.The proposed method is based on two opposite state entity extraction.The method reflects on the common data flow of smart home event sequence.The developed algorithm clusters the smart home events by isolating opposite status of home appliance. …”
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