Search Results - (( effective classification using algorithm ) OR ( code classification using algorithm ))
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Network Traffic Classification Analysis on Differentiated Services Code Point Using Deep Learning Models for Efficient Deep Packet Inspection
Published 2024“…This study develops and analyze using neural network-based models for effective classification of data packets using the DSCP header field. …”
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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. …”
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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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4
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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Plant identification using combination of fuzzy c-means spatial pyramid matching, gist, multi-texton histogram and multiview dictionary learning
Published 2016“…Moreover with simple concatenating features, classification results are not optimal. It is crucial to integrate these heterogeneous features to create more accurate and robust classification results than using each individual type of features. …”
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6
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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HUMAN MOTION ANALYSIS IN VIDEO SURVEILLANCE SYSTEM
Published 2019“…In a human detection, the software is represented by algorithms, in which algorithm also being used in the process of training the dataset. …”
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Final Year Project -
8
Improving brain tumor segmentation in MRI images through enhanced convolutional neural networks
Published 2023“…The evaluations show that the proposed technique is significantly more effective than those currently in use. In the future, enhancement of the segmentation using artificial neural networks will help in the earlier and more precise detection of brain tumors. …”
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Pemetaan Pm10 Dan Aot Menggunakan Teknik Penderiaan Jauh Di Semenanjung Malaysia
Published 2006“…Average filtering was applied to the PM10 map to mininise the noise effect. The proposed algorithms were also validated using the multidate data. …”
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Thesis -
11
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 -
12
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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Enhancement of feature sets for subjectivity analysis on Malay-English code-switching text
Published 2023“…In the unified code-switching feature set, the extracted Malay and English features were unified using an adapted algorithm known as the Malay-English Unified POS. …”
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XAIRF-WFP: a novel XAI-based random forest classifier for advanced email spam detection
Published 2024“…However, these algorithms often suffer from the "black box" dilemma, a lack of transparency that hinders their applicability in security contexts where understanding the reasoning behind classifications is essential for effective risk assessment and mitigation strategies. …”
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Malay festive seasons food recognition for calorie detection / Nurul Hafiza Basiruddin
Published 2021“…Then the result from the Color Feature Extraction Method is used to identify the type of food by using Error-Correcting Output Codes (ECOC) classification which is the part of the Support Vector Machine (SVM) algorithm. …”
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Thesis -
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On line fault detection for transmission line using power system stabilizer signals
Published 2007“…Hence, this study will show that not only the PSS able to compensate the damping due to the disturbance but also by using the developed algorithm it succeeds to detect and classify the fault conditions on the parallel transmission lines.…”
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17
Android Malware classification using static code analysis and Apriori algorithm improved with particle swarm optimization
Published 2014“…In this method, features were extracted from Android applications byte-code through static code analysis, selected and were used to train supervised classifiers. …”
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Proceeding Paper -
18
Static code analysis of permission-based features for android malware classification using apriori algorithm with particle swarm optimization
Published 2015“…However, supervised learning technique has limitations for malware classification task. This paper presents a classification approach on android malware using candidate detectors generated from an unsupervised association rule of Apriori Algorithm. …”
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Malay festive seasons food recognition for calorie detection using SVM and ECOC approaches / Nurul Hafiza Binti Basiruddin, Zalikha Zulkifli and Samsiah Ahmad
Published 2022“…Then the result from the Color Feature Extraction Method is used to identify the type of food by using Error-Correcting Output Codes (ECOC) classification, which is part of the Support Vector Machine (SVM) algorithm. …”
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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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