Search Results - (( pattern classification using algorithm ) OR ( code classification _ algorithm ))
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1
Genetic algorithm fuzzy logic for medical knowledge-based pattern classification
Published 2018“…The proposed algorithm was applied and tested in four critical illness datasets in medical knowledge pattern classification. …”
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2
Content adaptive fast motion estimation based on spatio-temporal homogeneity analysis and motion classification
Published 2012“…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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3
Genetic algorithm fuzzy logic for medical knowledge-based pattern classification
Published 2023“…The proposed algorithm was applied and tested in four critical illness datasets in medical knowledge pattern classification. …”
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Image classification based on sparse-coded features using sparse coding technique for aerial imagery: a hybrid dictionary approach
Published 2023“…Aerial photography; Aircraft detection; Antennas; Codes (symbols); Discrete cosine transforms; Discrete wavelet transforms; Glossaries; Image classification; Image coding; Image enhancement; Learning algorithms; Learning systems; Object recognition; Remote sensing; Satellite imagery; Satellites; Unmanned aerial vehicles (UAV); Discrete tchebichef transforms; Discriminative features; Finite Ridgelet Transform; Histogram of oriented gradients; Image processing and computer vision; Scale invariant feature transforms; SIFT; Sparse coding; Classification (of information)…”
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Improving hand written digit recognition using hybrid feature selection algorithm
Published 2022“…While mRMR was capable of identifying a subset of features that were highly relevant to the targeted classification variable, it still carry the weakness of capturing redundant features along with the algorithm. …”
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Final Year Project / Dissertation / Thesis -
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Systematic review for phonocardiography classification based on machine learning
Published 2023“…This systematic review aims to examine the existing literature on phonocardiography classification based on machine learning, focusing on algorithms, datasets, feature extraction methods, and classification models utilized. …”
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Modelling of clinical risk groups (CRGs) classification using FAM
Published 2006“…Fuzzy ARTMAP (FAM) is an incremental supervised learning of recognition neural networks in response to input and target pattern [4, 5]. FAM is a fast learning algorithm and used less epoch training [4]. …”
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Conference or Workshop Item -
8
An improved plant identification system by Fuzzy c-means bag of visual words model and sparse coding
Published 2020“…Classic bag of visual words algorithm is based on k-means clustering and every SIFT features belongs to one cluster and it leads to decreasing classification results. …”
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Comparative analysis for topic classification in juz Al-Baqarah
Published 2018“…The SVM performance is then compared against other classification algorithms such as Naive Bayes, J48 Decision Tree and K-Nearest Neighbours. …”
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10
Compacted dither pattern codes over MPEG-7 dominant colour descriptor in video visual depiction
Published 2010“…The algorithmic comparison between the two is presented in this paper, and demonstrates that there are several competitive advantages of CDPC in feature extraction and classification stages when compared to MPEG-7 DCD. …”
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11
Pemetaan Pm10 Dan Aot Menggunakan Teknik Penderiaan Jauh Di Semenanjung Malaysia
Published 2006“…The proposed algorithms were used to generate PM10 and AOT maps for the study areas. …”
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Thesis -
12
An enhanced android botnet detection approach using feature refinement
Published 2019“…The experimental and statistical tests show that 97.28% accuracy achieved by Random Forest machine classifier, it performs well as compared to other classification algorithms. Based on the test results, various open research issues which need to be addressed in future studies are highlighted.…”
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Thesis -
13
CAGDEEP : Mobile malware analysis using force atlas 2 with strong gravity call graph and deep learning
Published 2023“…The novelty of our study lies in the Force Atlas 2 call graph development to capture malware behavior patterns. Afterwards, this study adopts Convolutional Neural Network (CNN) for malware detection and classification algorithm. …”
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Conference or Workshop Item -
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Integration Of Unsupervised Clustering Algorithm And Supervised Classifier For Pattern Recognition
Published 2017“…In pattern recognition system, achieving high accuracy in pattern classification is crucial. …”
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Thesis -
15
Enhancing teaching and learning through data-driven optimization of servicing code demand and lecturer allocation using WEKA analysis
Published 2025“…Furthermore, classification using the Random Forest algorithm depicted that a 95.3% accuracy (k=0.768), confirming robust predictive capability in identifying course approval status and demand trends. …”
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Realization Of The 1D Local Binary Pattern (LBP) Algorithm In Raspberry Pi For Iris Classification Using K-NN Classifier
Published 2018“…There are a lot of feature extraction methods and classification methods for iris classification. Classic local binary pattern (LBP) is one of the most useful feature extraction methods. …”
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Monograph -
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Pattern Recognition for Human Diseases Classification in Spectral Analysis
Published 2022“…On the other hand, classification methods are techniques or algorithms used to group samples into a predetermined category. …”
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The Potential of a Classification-based Algorithm to Calculate Calories in Real-Time Via Pattern Recognition
Published 2016“…While the algorithm helped to classify different types of wavelengths produced from the sensor, a classification-based algorithm via Pattern Recognition Method will be used to classify and match the food components. …”
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Conference or Workshop Item -
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Android Malware classification using static code analysis and Apriori algorithm improved with particle swarm optimization
Published 2014“…This paper presents a classification of android malware using candidate detectors generated from an unsupervised association rule of Apriori algorithm improved with particle swarm optimization to train three different supervised classifiers. …”
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Proceeding Paper
