Search Results - (( re evaluation methods algorithm ) OR ( writer classification using algorithm ))
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1
Improved random forest for feature selection in writer identification
Published 2015“…Important features are measured by using Variable Importance (VI). While Mean Absolute Error (MAE) values use to identify the variance between writers, VI value was used for splitting process in tree and MAE value is to ensure the intra-class (same writer) invariance is lower than inter-class (different writer) invariance because lower intra-class invariance indicates accuracy to the real author. …”
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2
Discretization of integrated moment invariants for writer identification
Published 2008“…The results disclose that the proposed discretized invariants reveal 99% accuracy of classification by using 3520 training data and 880 testing data.…”
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3
A New Swarm-Based Framework for Handwritten Authorship Identification in Forensic Document Analysis
Published 2014“…Its principal point is in forensics and biometric application as such the writing style can be used as bio-metric features for authenticating the identity of a writer. …”
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4
A new swarm-based framework for handwritten authorship identification in forensic document analysis
Published 2014“…Its principal point is in forensics and biometric application as such the writing style can be used as bio-metric features for authenticating the identity of a writer. …”
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5
Arabic Calligraphy Classification using Triangle Model for Digital Jawi Paleography Analysis
Published 2011“…Calligraphy classification of the ancient manuscripts gives useful information to paleographers. …”
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6
Arabic Calligraphy Classification using Triangle Model for Digital Jawi Paleography Analysis
Published 2011“…Calligraphy classification of the ancient manuscripts gives useful information to paleographers. …”
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7
Identifying Cyberspace Users� Tendency in Blog Writing Using Machine Learning Algorithms
Published 2023“…A blog is a platform where a writer or group of writers gives their opinion on a specific topic. …”
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8
Segmentation of MRI brain images using statistical approaches
Published 2011“…The non-Local means (NL-means) algorithm is a state-of-the art neighbourhood-based noisereduction method which is time-consuming and its accuracy can be improved. …”
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9
Features Extraction of Arabic Calligraphy using extended Triangle Model for Digital Jawi Paleography Analysis
Published 2013“…The style of writing or calligraphy applied in ancient manuscripts gives useful information to paleographers. The information helps paleographer to identify date, writer, number of writers, place of origin, and the originality of manuscripts. …”
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10
Removal of heavy metals from water by functionalized carbon nanotubes with deep eutectic solvents: An artificial neural network approach / Seef Saadi Fiyadh
Published 2019“…The best result achieved for Pb2+ removal using ANFIS algorithm is with RE 7.078%. For As3+ removal using different adsorbents, two algorithms were applied for the modelling, the feed-forward back-propagation maximum RE achieved is 5.97% while, the NARX algorithm achieved better accuracy with maximum RE of 5.79%. …”
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11
A hybrid grey wolf assisted-sparrow search algorithm for frequency control of RE integrated system
Published 2023“…Moreover, the robustness of the proffered method is also evaluated under the random varying load, variation of HPS system parameter, and weather intermittency of RE resources in real-time conditions. …”
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12
Invariants discretization for individuality representation in handwritten authorship
Published 2008“…Its focal point is in forensics and biometric application as such the writing style can be used as biometric features for authenticating a writer. …”
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13
Hybrid metaheuristic method for clustering in wireless sensor networks / Bryan Raj Peter Jabaraj
Published 2023“…As such, this thesis proposes a hybrid metaheuristic method that consists of Sperm Swarm Optimization (SSO) algorithm and Genetic Algorithm (GA), which is termed HSSOGA. …”
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14
Beyond Sentiment Analysis: A Review of Recent Trends in Text Based Sentiment Analysis and Emotion Detection
Published 2023“…This is because emotions are the finer grained information which could be extracted from opinions. So besides writer sentiments, writer emotion is also a valuable data. …”
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Classification of Learner Retention using Machine Learning Approaches
Published 2021“…The performance of these algorithms was evaluated based on accuracy, precision, recall, and f-measure. …”
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16
Android: S-Based Technique in Mobile Malware Detection
Published 2018“…In order to overcome malware, concern in mobile, we propose a new framework for malware detection which is signature based technique using pattern matching. This framework uses signature number and Secure Hash Algorithm (SHA) as signature in the detection process. …”
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17
Malaysia solar energy experience: intelligent fault location algorithm for unbalanced radial distribution network including PV systems
Published 2016“…The recorded values are evaluated by a designed and tuned multi-layer feed forward neural network and the fault distances from the source are estimated accordingly. …”
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18
Optimizing decentralized exam timetabling with a discrete whale optimization algorithm
Published 2025“…This problem remains an active area of research and, to the authors' knowledge, has not been adequately addressed by the WOA algorithm. The method was evaluated using real-world data from the first semester of 2023/2024 for faculties at the Universiti of Sarawak, Malaysia. …”
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Optimizing Decentralized Exam Timetabling with a Discrete Whale Optimization Algorithm
Published 2025“…This problem remains an active area of research and, to the authors’ knowledge, has not been adequately addressed by the WOA algorithm. The method was evaluated using real-world data from the first semester of 2023/2024 for faculties at the Universiti of Sarawak, Malaysia. …”
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20
Ensemble based categorization and adaptive model for malware detection
Published 2011“…In this paper, we propose an ensemble categorization by using ensemble classification and clustering together with adaptive learning model. …”
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