Search Results - (( using classification using algorithm ) OR ( basic evaluation result algorithm ))
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1
An ensemble feature selection method to detect web spam
Published 2018“…In addition, it improves classification metrics in comparison to basic feature selection methods.…”
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Article -
2
Al-Hams and Al-Jahr Sifaat evaluation using classification approach
Published 2021“…Features selection technique was then implemented to reduce the size of the features vector, where later, K-nearest Neighbor (KNN) algorithm was used as the classification technique. …”
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Proceeding Paper -
3
A Machine Learning Classification Approach to Detect TLS-based Malware using Entropy-based Flow Set Features
Published 2022“…Furthermore, using the basic features, TLSMalDetect achieved the highest accuracy of 93.69% by Naïve Bayes (NB) among the ML algorithms applied. …”
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Satellite Image Segmentation Using Thresholding Technique
Published 2017“…Among all the segmentation techniques, thresholding segmentation method is the most popular algorithm and is widely used in the image segmentation field. …”
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Thesis -
5
Deep learning-based breast cancer detection and classification using histopathology images / Ghulam Murtaza
Published 2021“…To reduce the misclassification, a feature selection algorithm (using information gain and principal component analysis schemes) is developed to elicit the most discriminative feature subset. …”
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Thesis -
6
Integrated artificial intelligence-based classification approach for prediction of acute coronary syndrome
Published 2014“…The classification performance of K1-K2-NN model was benchmarked against 13 commonly used classification models using repeated random sub-sampling crossvalidation on ACSEKI data set. …”
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Thesis -
7
Landslide Susceptibility Mapping with Stacking Ensemble Machine Learning
Published 2024“…This is because the occurrence of non-slide incidents is much more than the landslide. The evaluation results of the LSM performance show that the proposed stacking ensemble ML improves the overall accuracy of the individual base ML model even when it is compared with RF which is naturally also ensemble ML. � 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.…”
Conference Paper -
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Image Splicing Detection With Constrained Convolutional Neural Network
Published 2019“…It is shown that CNN with constrained convolution algorithm can be used as a general image splicing detection task.…”
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Thesis -
9
Malay continuous speech recognition using continuous density hidden Markov model
Published 2007“…With their efficient training algorithm (Baum-Welch and Viterbi/Segmental K-mean) and recognition algorithm (Viterbi), as well as it’s modeling flexibility in model topology, observation probability distribution, representation of speech unit and other knowledge sources, HMM has been successfully applied in solving various tasks in this thesis. …”
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Thesis -
10
CYCLOSTATIONARY FEATURES BASED LOW COMPLEXITY MUTLIRESOLUTION SPECTRUM SENSING FOR COGNITVE RADIO APPLICATIONS
Published 2011“…The results found are encouraging and the proposed algorithms are proved to be not only fast but also more robust and reliable. …”
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Thesis -
11
Defect Detection And Classification Of Silicon Solar Wafer Featuring Nir Imaging And Improved Niblack Segmentation
Published 2016“…Meanwhile, a set of descriptors corresponding to Elliptic Fourier Features shape description is extracted for each defect and is evaluated for each cluster to use for clustering and classification part. …”
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Thesis -
12
FEATURES EXTRACTION OF HEP-2 IMMUNOFLUORESCENCE PATTERNS BASED ON TEXTURE AND REGION OF INTEREST TECHNIQUES
Published 2013“…This project involves developing features extraction technique of HEp-2 cell of 2 main patterns namely Nucleolar and Centromere using texture and region of interest technique. Next, to design an algorithm that can automatically identify the 2 patterns of the HEp-2 cell tested using ANA. …”
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Final Year Project -
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Comparison of Landsat 8, Sentinel-2 and spectral indices combinations for Google Earth Engine-based land use mapping in the Johor River Basin, Malaysia
Published 2021“…The Random Forest (RF) algorithm was used to classify the land use land cover (LULC) with 222 training samples and 78 verification samples obtained through the Google Earth Pro higher resolution satellite images and field samplings. …”
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Development Of Double Stage Filter (DSF) On Stereo Matching Algorithm For 3D Computer Vision Applications
Published 2016“…Based on the results of evaluations, the results obtained by DSF is better than the algorithms, basic block matching and dynamic programming.…”
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Thesis -
16
Dengue classification system using clonal selection algorithm / Karimah Mohd
Published 2012“…This project can be improved by making a comparative study on Artificial Immune System and other techniques or algorithms used to solve dengue classification problems.…”
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Improving Classification of Remotely Sensed Data Using Best Band Selection Index and Cluster Labelling Algorithms
Published 2005“…The comparison showed that, the accuracy of the unsupervised classification map with value of 88.4% that was generated by using the cluster labelling algorithm was slightly more than the maximum-likelihood supervised classification map with value of 87.5%. …”
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Thesis -
18
ABC: android botnet classification using feature selection and classification algorithms
Published 2017“…The Information Gain algorithm is used to select the most significant permissions, then the classification algorithms Naïve Bayes, Random Forest and J48 used to classify the Android apps as botnet or benign apps. …”
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An improved pixel-based and region-based approach for urban growth classification algorithms / Nur Laila Ab Ghani
Published 2015“…The urban growth images obtained are analysed to improve existing classification algorithms. The improved algorithm is constructed by adding new parameter and classification rule to existing algorithm. …”
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Thesis -
20
Classification of tropical rainforest using different classification algorithm based on remote sensing imagery: A study of Gunung Basor
Published 2019“…Thehighest accuracy for classification map of Gunung Basor is by using maximum likelihood algorithm with an accuracy of 82.90%. …”
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Undergraduate Final Project Report
