Search Results - (( pattern classification using algorithm ) OR ( quality classification based algorithm ))

Content adaptive fast motion estimation based on spatio-temporal homogeneity analysis and motion classification by Nisar, Humaira, Malik, Aamir Saeed, Choi, Tae-Sun

“…This is the basis of the proposed algorithm. The proposed algorithm involves a multistage approach that includes motion vector prediction and motion classification using the characteristics of video sequences. …”
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Improved building roof type classification using correlation-based feature selection and gain ratio algorithms by Norman, M., Mohd Shafri, Helmi Zulhaidi, Pradhan, Biswajeet, Yusuf, B.

“…Then, the quality of the selected features was assessed using correlation-based feature selection (CFS). …”
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Enhanced grey wolf optimisation algorithm for feature selection in anomaly detection by Almazini, Hussein

“…The first modification enhances the initial population of the MBGWO using a heuristic based Ant Colony Optimisation algorithm. …”
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Multilevel learning in Kohonen SOM network for classification problems by Mohd. Yusof, Norfadzila

“…Self-organizing map (SOM) is a feed-forward neural network approach that uses an unsupervised learning algorithm has shown a particular ability for solving the problem of classification in pattern recognition. …”
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Classification of diabetic retinopathy clinical features using image enhancement technique and convolutional neural network / Abdul Hafiz Abu Samah by Abu Samah, Abdul Hafiz

“…To solving pattern classification problem, the optimization deep learning architecture and parameter by using four convolution layers is set up to classify the three pathological signs; HEM, MA and exudate. …”
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Backpropagation algorithm for classification problem: academic performance prediction model for UiTM Melaka Mengubah Destini Anak Bangsa (MDAB) program. / Fadhlina Izzah Saman, Nur... by Saman, Fadhlina Izzah, Zainuddin, Nurulhuda, Md Shahid, Khairiyah

“…Multilayer perceptrons (MLPs) is one of the topology used for processing ANN, while backpropagation algorithm is one of the most popular methods in training MLPs. …”
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Hybrid genetic random forest algorithm for the identification of ISI-indexed articles / Mohammadreza Moohebat by Mohammadreza, Moohebat

“…After ensuring that the classification technique was able to accomplish this work, Hybrid Genetic Random Forests (HGRF) was introduced as a new ensemble classifier based on a Random Forest algorithm, but altered slightly with some innovations. …”
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Personalized Recommendation Classification Model of Students’ Social Well-being Based on Personality Trait Determinants Using Machine Learning Algorithms by Rochin Demong, Nur Atiqah, Shahrom, Melissa, Abdul Rahim, Ramita, Omar, Emi Normalina, Yahya, Mornizan

“…In this study, how different personality trait models compare in terms of accuracy and reliability is explored using different machine learning algorithms using the WEKA tool. …”
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A Steganalysis Classification Algorithm Based on Distinctive Texture Features by Hammad B.T., Ahmed I.T., Jamil N.

“…Therefore, in this research, we present a steganalysis classification method based on one of the texture features chosen, such as segmentation-based fractal texture analysis (SFTA), local binary pattern (LBP), and gray-level co-occurrence matrix (GLCM). …”

A framework of modified adaptive neuro-fuzzy inference engine by Hossen, Md. Jakir

“…The performance of MANFIE was compared with existing methods in a diversity of practical benchmark applications such as pattern classifications, time series predictions, modeling with inverse learning control and mobile robot navigation. …”
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Maize leaf disease detection and classification using Convolutional Neural Network (CNN) / Syafiqah Amir by Amir, Syafiqah

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Underwater Image Recognition using Machine Learning by Divya, N.K., Manjula, Sanjay Koti, Priyadarshini, S

“…It encompasses the procedure for feeding algorithms information to create the algorithms realize patterns in the data and then increase the performance of the algorithms. …”
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Minimizing the number of stunting prevalence using the euclid algorithm clustering approach by Zarlis, Muhammad, Oktavia, Tanty, Buaton, Relita, Ernawan, Ferda, Andrian, Kevin

“…The results of the classification and clustering of the best stunting prevalence in cluster one with a very small number, can be used as a source of accurate and updated information that can be used by the government in its efforts to optimize stunting handling in each district/city based on artificial intelligence which can provide handling and optimization patterns. stunting in every district/city.…”
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Cyber parental control framework for objectionable web content classification and filtering based on topic modelling using enhanced latent dirichlet allocation / Hamza H. M. Altart... by Hamza H. M. , Altarturi

“…Despite substantial advancements in automating web classification that combines web mining and content classification methods, the study identifies a gap in applying advanced machine learning algorithms for superior objectionable web content classification. …”
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An interpretable fuzzy-ensemble method for classification and data analysis / Adel Lahsasna by Adel, Lahsasna

“…In addition, we propose a combination method that aims to improve the accuracy of the fuzzy rule-based system by using the accurate ensemble method to classify the patterns that have low certainty degree or in cases of rejected and uncovered classifications. …”
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Electromygraphy (EMG) signal based hand gesture recognition using Artificial Neural Network (ANN) by Ahsan, Md. Rezwanul, Ibrahimy, Muhammad Ibn, Khalifa, Othman Omran

“…The purpose of this paper is to describe the process of detecting different predefined hand gestures (left, right, up and down) using artificial neural network (ANN). ANNs are particularly useful for complex pattern recognition and classification tasks. …”
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Application of image quality assessment module to motion-blurred wood images for wood species identification system by Rajagopal, Heshalini, Khairuddin, Anis Salwa Mohd, Mokhtar, Norrima, Ahmad, Azlin, Yusof, Rubiyah

“…Normally, experts identify the wood species based on the pattern of the wood surface texture. …”
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A comparative study between rough and decision tree classifiers by Mohamad Mohsin, Mohamad Farhan

“…Theoretically, a good set of knowledge should provide good accuracy when dealing with new cases.Besides accuracy, a good rule set must also has a minimum number of rules and each rule should be short as possible.It is often that a rule set contains smaller quantity of rules but they usually have more conditions.An ideal model should be able to produces fewer, shorter rule and classify new data with good accuracy.Consequently, the quality and compact knowledge will contribute manager with a good decision model.Because of that, the search for appropriate data mining approach which can provide quality knowledge is important.Rough classifier (RC) and decision tree classifier (DTC) are categorized as RBC.The purpose of this study is to investigate the capability of RC and DTC in generating quality knowledge which leads to the good accuracy.To achieve that, both classifiers are compared based on four measurements that are accuracy of the classification, the number of rule, the length of rule, and the coverage of rule.Five dataset from UCI Machine Learning namely United States Congressional Voting Records, Credit Approval, Wisconsin Diagnostic Breast Cancer, Pima Indians Diabetes Database, and Vehicle Silhouettes are chosen as data experiment.All datasets were mined using RC toolkit namely ROSETTA while C4.5 algorithm in WEKA application was chosen as DTC rule generator.The experimental results indicated that both classifiers produced good classification result and had generated quality rule in different types of model – higher accuracy, fewer rule, shorter rule, and higher coverage.In term of accuracy, RC obtained higher accuracy in average while DTC significantly generated lower number of rule than RC.In term of rule length, RC produced compact and shorter rule than DTC and the length is not significantly different.Meanwhile, RC has better coverage than DTC.Final conclusion can be decided as follows “If the user interested at a variety of rule pattern with a good accuracy and the number of rule is not important, RC is the best solution whereas if the user looks for fewer nr, DTC might be the best choice”…”
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Enhancement of text representation for Indonesian document summarization with deep sequential pattern mining by Dian Sa’adillah Maylawati

“…First, this study combines SPM with Sentence Scoring method as feature-based approach and Bellman-Ford algorithm as graph-based to validate the performance of SPM. …”
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Detection and restoration of cracked digitized paintings and manuscripts using image processing by Farajalla Ali, Nawafil Abdulwahab, Taha Alshaikhli, Imad Fakhri, Hassan, Raini

“…The purpose of the developed algorithm is to identify cracks using the thresholding operation, which was the output of the top-hat transform morphology. …”
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