Search Results - (( evolution classification approach algorithm ) OR ( code classification problems algorithm ))
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Object-Oriented Programming semantics representation utilizing agents
Published 2011“…Novices tend to refer to source codes examples and adapt the source codes to the problem given in their assignments. …”
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Intersection Features For Android Botnet Classification
Published 2019“…This paper proposed an enhancement approach for Android botnet classification based on features selection and classification algorithms. …”
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Scene classification for aerial images based on CNN using sparse coding technique
Published 2017“…Recent developments include several approaches and numerous algorithms address the task. This article proposes a convolutional neural network (CNN) approach that utilizes sparse coding for scene classification applicable for HRRS unmanned aerial vehicle (UAV) and satellite imagery. …”
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Differential evolution for neural networks learning enhancement
Published 2008“…Evolutionary computation is the name given to a collection of algorithms based on the evolution of a population toward a solution of a certain problem. …”
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Thesis -
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Maldroid- attribute selection analysis for malware classification
Published 2019“…Hence, the objective of this paper is to find the most effective and efficient attribute selection and classification algorithm in malware detection. Moreover, in order to get the best combination between attribute selection and classification algorithm, eight attributes selection and seven categories machine learning algorithm are applied in this study. …”
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Scene classification for aerial images based on CNN using sparse coding technique
Published 2023Article -
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Whale Optimisation Freeman Chain Code (WO-FCC) extraction algorithm for handwritten character recognition
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Conference or Workshop Item -
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Email spam classification based on deep learning methods: A review
Published 2025“…Email spam is a significant issue confronting both email consumers and providers. The evolution of spam filtering has progressed considerably, transitioning from basic rule-based filters to more sophisticated machine learning algorithms. …”
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A multilayered convolutional sparse coding framework for modeling of pooling operation of convolution neural networks
Published 2019“…The multilayered version of CSC(ML-CSC) is shown to be connected to forward pass of CNNs and dictionary learning and sparse coding algorithms of this model are analyzed for solving classification and inverse problems in image processing. …”
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Proceeding Paper -
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Improving hand written digit recognition using hybrid feature selection algorithm
Published 2022“…Therefore, many researchers have applied and developed various machine learning algorithms that could efficiently tackle the handwritten digit recognition problem. …”
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Final Year Project / Dissertation / Thesis -
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Cloud Worm Detection and Response Technique By Integrating The Enhanced Genetic Algorithm An Threat Level
Published 2024thesis::doctoral thesis -
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Improved whale optimization algorithm for feature selection in Arabic sentiment analysis
Published 2019“…The proposed algorithm is compared with six well-known optimization algorithms and two deep learning algorithms. …”
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Digital economy tax compliance model in Malaysia using machine learning approach
Published 2021“…Based on the validation of training data with the presence of seven single classifier algorithms, three performance improvements have been established through ensemble classification, namely wrapper, boosting, and voting methods, and two techniques involving grid search and evolution parameters. …”
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Fault tolerance structures in Wireless Sensor Networks (WSNs): survey, classification, and future directions
Published 2022“…Many prior studies have provided classifications for fault tolerance systems. However, this research has enhanced these reviews by proposing an extensively enhanced categorization that depends on the new and additional metrics which include the number of sensor nodes engaged, the overall fault-tolerant approach performance, and the placement of the principal algorithm responsible for eliminating network errors. …”
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Classification with degree of importance of attributes for stock market data mining
Published 2004“…The SVM is a training algorithm for learning classification and regression rules from data [7]. …”
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Stock market turning points rule-based prediction / Lersak Photong … [et al.]
Published 2021“…Results show that the best feature selection is term frequency and trimming of the feature with a frequency greater than 95%. The best news classification approach is based on Deep Learning techniques that provide the most accurate classification. …”
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Book Section -
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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“…Beside that, classic bag of visual words algorithm (BoVW) is based on kmeans clustering and every SIFT feature belongs to one cluster and it leads to decreasing classification results. …”
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Compacted dither pattern codes over MPEG-7 dominant colour descriptor in video visual depiction
Published 2010“…Reduction of feature space of visual descriptors has become important due to the 'curse of dimensionality' problem. This paper reports the efficiency and effectiveness of the Compacted Dither Pattern Code (CDPC) combined with the Bhattacharyya classifier over MPEG-7 Dominant Colour Descriptor (DCD). …”
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