Search Results - (((( pattern matching algorithm ) OR ( e learning algorithm ))) OR ( patterns among algorithm ))

Using GA and KMP algorithm to implement an approach to learning through intelligent framework documentation by Mat Jani H., Lee S.P.

Subjects: “…Knuth-Morris-Pratt (KMP) pattern matching algorithm…”

Medical Image Analysis Using Deep Learning and Distribution Pattern Matching Algorithm by Jaber M.M., Yussof S., Elameer A.S., Weng L.Y., Abd S.K., Nayyar A.

“…Automation; Complex networks; Computational complexity; Deep learning; Image analysis; Medical imaging; Pattern matching; Pixels; Distribution pattern-matching rule; Distribution patterns; Gray wolf-optimized deep convolution network; Gray wolves; Learning patterns; Matching rules; Medical fields; Medical image analysis; Pattern matching algorithms; Pattern-matching; Convolution…”

Block Matching Algorithm (BMA) of the Hybrid Adaptive Rood Pattern Search (ARPS) Based on Its Motion Speed by Faizul Hadi Jamil, Ali Chekima, Wong Hock Tze @ Farrah Wong, Rosalyn R Porle, Razak Ali Lee, Ismail Saad

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Implementing case-based reasoning approach to framework documentation by Hajar M.J., Lee S.P.

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Investigation of block matching algorithm for video coding by Faizul Hadi Mohamad Jamil

“…The Spatial model exploits the redundancy in a single video frame (I frame) while the temporal model exploits the redundancy among frames (P frame). The temporal model deals with motion estimation (ME) and motion compensation (MC) algorithm with the matching technique called “Block Matching Algorithm” (BMA) to produce the next encoded video frame with motion vector. …”
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Mobile Malware Classification via System Calls and Permission for GPS Exploitation by Madihah Mohd Saudi, Husainiamer, MAB

Improved GART neural network model for pattern classification and rule extraction with application to power systems by Yap K.S., Lim C.P., Au M.T.

“…IGART enhances the dynamics of GART in several aspects, which include the use of the Laplacian likelihood function, a new vigilance function, a new match-tracking mechanism, an ordering algorithm for determining the sequence of training data, and a rule extraction capability to elicit if-then rules from the network. …”

Composing multi-relations association rules from crowdsourcing remuneration data by Siti Salwa Salleh, Nurhayati Zakaria, Norjansalika Janom, Syaripah Ruzaini Syed Aris, Noor Habibah Arshad

“…The data comprise a lot of redundancies, therefore an apriori algorithm is used to normalise it by removing redundancies and then extracting significant patterns. …”
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APPLICATION OF LINK GRAMMAR IN SEMI-SUPERVISED NAMED ENTITY RECOGNITION FOR ACCIDENT DOMAIN by SARI, YUNITA SARI

“…For the third contribution, we have applied the Self-Training algorithm which is one of the semi-supervised machines learning technique. …”
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Improving named entity recognition accuracy of gene and protein in biomedical text by Tohidi, Hossein

“…In this study, to handle the above issues in recognizing gene and protein names, a statistical similarity measurement as a pattern matching function is proposed. Our approach is based on an assumption that a named entity occurs among a noun group which is extracted using Brill Part of Speech tagger. …”
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Classification of students' performance in computer programming course according to learning style by Norwawi N.M., Abdusalam S.F., Hibadullah C.F., Shuaibu B.M.

Music Recommender System Using Machine Learning Content-Based Filtering Technique by Foong, Kin Hong

“…These algorithms identify hidden patterns or data groupings without the assistance of a human. …”
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A guided hybrid k-means and genetic algorithm models for children handwriting legibility performance assessment / Norzehan Sakamat by Sakamat, Norzehan

“…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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STATISTICAL FEATURE LEARNING THROUGH ENHANCED DELAUNAY CLUSTERING AND ENSEMBLE CLASSIFIERS FOR SKIN LESION SEGMENTATION AND CLASSIFICATION by Adil H., Khan, Dayang Nurfatimah, Awang Iskandar, Jawad F., Al-Asad, SAMIR, EL-NAKLA, SADIQ A., ALHUWAIDI

“…Moreover, skin lesion images are clustered based on fused color, pattern and shape based features. A boost ensemble learning algorithm using Support Vector Machines (SVM) as initial classifiers and Artificial Neural Networks (ANN) as a final classifier is employed to learn the patterns of different skin lesion class features. …”
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An efficient fuzzy C-least median clustering algorithm by Mallik, Moksud Alam, Zulkurnain, Nurul Fariza, Nizamuddin, Mohammed Khaja, Aboosalih, K C

“…The outcomes demonstrate a clear improvement of our algorithm than existing FCM algorithm.…”
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Identifying Cyberspace Users� Tendency in Blog Writing Using Machine Learning Algorithms by AbuSalim, S.W.G., Mostafa, S.A., Mustapha, A., Ibrahim, R., Wahab, M.H.A.

“…There is a specific proportion between blog features and bloggersâ�� tendency to social, political, and cultural patterns of different countries and nations that create trends among the bloggers in these countries. …”
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Herb recognition for mobile apps / Jumriyanie Baba by Baba, Jumriyanie

“…Two texture features have been experimented that are Local Binary Pattern (LBP) and Histogram of Oriented Gradient (HOG). …”
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Performance Analysis Of Different Hash Functions Using Bloom Filter For Network Intrusion Detection Systems In 32-Bit And 64-Bit Computer Operation Mode. by Tan , Beng Ghee

“…A Bloom Filter is an array of bits that determine whether a given structure of information belongs to it. A Bloom Filter pattern matching algorithm with fast hashing functions is developed for 32-bit and 64-bit computer system. …”
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Application of machine learning and artificial intelligence in detecting SQL injection attacks by Md Sultan, Abu Bakar, Agiliga, Nwabudike Augustine, Osman, Mohd Hafeez Bin, Sharif, Khaironi Yatim

“…Datasets of well-known SQL injection attack patterns and AI/ML models intended for cybersecurity anomaly detection are among the resources underexplored, these findings show the potential for boosting detection capabilities by deploying ML and AI-based security solutions, with some algorithms scoring up to an 80 percent success rate in identifying SQL injections. …”
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COMPUTER AIDED SYSTEM FOR BREAST CANCER DIAGNOSIS USING CURVELET TRANSFORM by MOHAMED ELTOUKHY, MOHAMED MESELHY

“…Two methods are suggested to accomplish the segmentation stage: an adaptive thresholding method and a pattern matching method. Once the ROI has been identified, an automatic cropping is performed to extract it from the original mammogram. …”
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