Search Results - (( data normalization based algorithm ) OR ( shape identification method algorithm ))
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Exploring Text Recognition Segmentation and Detection in Natural Scene Images
Published 2024“…Identification, segmentation, and recognition of fonts from real-world images are major challenges in computer vision, particularly due to subtle differences in font shapes, lighting, and backgrounds. …”
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Plant identification using combination of fuzzy c-means spatial pyramid matching, gist, multi-texton histogram and multiview dictionary learning
Published 2016“…Most of the existing plant identification methods are based on both the global shape features and the intact plant leaves. …”
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Human identification at a distance using body shape information
Published 2013“…This paper presents an intelligent system approach for human identification at a distance using human body shape information. …”
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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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An Ar Natural Marker Similarities Measurement Algorithm For E-Biodiversity
Published 2018“…Algorithms of investigation starting with span from extraction, matching and classification to determine the interest point of flower species, like colour and shape features information. …”
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Tag clouds algorithm with the inclusion of personality traits
Published 2015“…The algorithm was developed based on three theories of personality traits, namely Myers-Briggs Type Indicator (MBTI), Shape, and Multiple Intelligence (MI). …”
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The Effect Of Linkages In The Hierarchical Clustering Of Auto-Regressive Algorithm For Defect Identification In Heat Exchanger Tubes
Published 2019“…The AR algorithm characterizes the shape of the stress wave signals by AR coefficients and clustered using ‘centroid’ linkages. …”
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Feature identification in a real surface metrology analysis by means of Double Iteration Sobel (DIS) / Ainaa Farhanah Mohd Razali
Published 2022“…The results of the verification of the system algorithm on the simulated 3D areal surface topography of a sloped bumps shows that the system algorithm can effectively identified the edges features and segmented them following the shape partem of the surface features of the sloped bumps. …”
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Experimental analysis of racing car chassis for Modal Identification / M. N. Aizat Zainal ...[et al.]
Published 2018“…Results from both FDD and EMA are validated and compared to ensure that FDD result can be further used in OMA methods of analysis. Only two out of four identification algorithms in parametric OMA techniques will be applied, namely Enhanced Frequency Domain Decomposition (EFDD) and Canonical Variant Analysis of Covariance-driven Stochastic Subspace Identification (SSI-CVA) methods. …”
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Operational structural damage identification using de-noised modal feature in machine learning / Chen Shilei
Published 2021“…By integrating ISMA, both supervised and unsupervised machine learning algorithms were investigated to develop real-time damage identification schemes. …”
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Classification of Cardiac Disorders Based on Electrocardiogram Data with Fuzzy Cognitive Map (FCM) Algorithm Approach
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The effect of dose calculation algorithms on the normal tissue complication probability values of thoracic cancer
Published 2015“…Purpose: To identify the effect of dose calculation algorithms on the Normal Tissue Complication Probability values of thoracic cancer. …”
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Flow regime identification of particles conveying in pneumatic pipeline using electric charge tomography and neural network techniques
Published 2006“…This research has produced filtered back concentration profiles of each flow regimes owing to the technique of neural network method of flow regime identification.…”
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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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An approach to enhance the structural operational deflection shape under random ambient excitation through mode shape expansion / Muhamad Azhan Anuar
Published 2021“…(iii) An expansion approach was applied by a linear combination of both OMA and FE mode shapes data using the modified LCP method (iv) A new algorithm that includes the selection matrix and rotation matrix were used to obtain the estimated experimental mode shape at higher DOFs. …”
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Data normalization techniques in swarm-based forecasting models for energy commodity spot price
Published 2014“…Data mining is a fundamental technique in identifying patterns from large data sets.The extracted facts and patterns contribute in various domains such as marketing, forecasting, and medical.Prior to that, data are consolidated so that the resulting mining process may be more efficient.This study investigates the effect of different data normalization techniques.which are Min-max, Z-score and decimal scaling, on Swarm-based forecasting models.Recent swarm intelligence algorithms employed includes the Grey Wolf Optimizer (GWO) and Artificial Bee Colony (ABC).Forecasting models are later developed to predict the daily spot price of crude oil and gasoline.Results showed that GWO works better with Z-score normalization technique while ABC produces better accuracy with the Min-Max.Nevertheless, the GWO is more superior than ABC as its model generates the highest accuracy for both crude oil and gasoline price.Such a result indicates that GWO is a promising competitor in the family of swarm intelligence algorithms.…”
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An alternative approach to normal parameter reduction algorithms for decision making using a soft set theory / Sani Danjuma
Published 2017“…In addition, the algorithm was relatively easy to understand compare to the state of the art of normal parameter reduction algorithm. …”
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Web-based clustering tool using fuzzy k-mean algorithm / Ahmad Zuladzlan Zulkifly
Published 2019“…Even a normal people using clustering to grouping their data. …”
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