Search Results - (( data classification method algorithm ) OR ( data visualization based algorithm ))
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Improving Classification of Remotely Sensed Data Using Best Band Selection Index and Cluster Labelling Algorithms
Published 2005“…Methods for improving supervised and unsupervised classification of remotely sensed data were developed in this study. …”
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Evaluation and Comparative Analysis of Feature Extraction Methods on Image Data to increase the Accuracy of Classification Algorithms
Published 2024“…The classification algorithm used in this research is the Convolutional Neural Network (CNN) algorithm. …”
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Sentiment analysis of restaurant reviews in Kuala Terengganu based on K-Nearest Neighbor/ Siti Syazwana Jafri
Published 2021“…In the future, it is very recommended to experiment with different algorithm. The volume of data should be large as it can generate better result of classification method.…”
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4
HEP-2 CELL IMAGES CLASSIFICATION BASED ON STATISTICAL TEXTURE ANALYSIS AND FUZZY LOGIC
Published 2014“…Automated system also saves time and cost as the system is able to process large amount of image data at one time. This project proposes a pattern recognition algorithm consisting of statistical methods to extract seven textural features from the HEp-2 cell images followed by classification of staining patterns by using fuzzy logic. …”
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Final Year Project -
5
Classification of labour pain using electroencephalogram signal based on wavelet method / Sai Chong Yeh
Published 2020“…The training and parameters selection of the machine learning algorithms are conducted using EEG data collected from ten subjects in the laboratory. …”
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Sauvola Segmentation and Support Vector Machine-Salp Swarm Algorithm Approach for Identifying Nutrient Deficiencies in Citrus Reticulata Leaves
Published 2024“…The proposed method integrates colour and texture feature-based image analysis with machine learning algorithms for classification. …”
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7
Decoding of visual activity patterns from fMRI responses using multivariate pattern analyses and convolutional neural network
Published 2017“…MVPA-CNN based proposed algorithm is compared with region of interest (ROI) based method and MVPA based estimated values. …”
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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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Sentiment analysis on national cultural tourism using Linear Support Vector Machine (LSVM) / Nur Haida Hanna Samsuddin
Published 2020“…In future, it is recommended to experiment with different algorithm or kernel of Support Vector Machine. The volume of data should be large as it can generate better result of classification method.…”
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10
Enhancing minority sentiment classification in gastronomy tourism: a hybrid sentiment analysis framework with data augmentation, feature engineering and business intelligence
Published 2024“…Subsequently, we optimize machine learning sentiment classification by employing data augmentation in conjunction with feature engineering strategies, with the goal of improving the recognition of minority sentiment classes. …”
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Enhancing minority sentiment classification in gastronomy tourism: a hybrid sentiment analysis framework with data augmentation, feature engineering and business intelligence
Published 2024“…Subsequently, we optimize machine learning sentiment classification by employing data augmentation in conjunction with feature engineering strategies, to improve the recognition of minority sentiment classes. …”
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PREDICTION OF HFMD DISEASE OUTBREAK FROM TWITTER
Published 2019“…On the other hand, Naive Bayes and SVM algorithm is using in classification of the tweets related with HFMD disease. …”
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Final Year Project Report / IMRAD -
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Unsupervised classification of multi-class chart images: A comparison of customized CNNs and transfer learning techniques
Published 2025“…Visualization through charts has become a crucial method for presenting complex data in a clear and structured format, surpassing traditional representation techniques in both clarity and interpretability. …”
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Predicting 30-day mortality after an acute coronary syndrome (ACS) using machine learning methods for feature selection, classification and visualization
Published 2021“…Hybrid combinations of feature selection, classification and visualisation using machine learning (ML) methods have the potential for enhanced understanding and 30-day mortality prediction of patients with cardiovascular disease using population-specific data. …”
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Identifying the mechanism to forecast the progression of Alzheimer’s disease from mild cognitive impairment using deep learning
Published 2022“…This study also implemented a CNN algorithm based on 3D ResNet-18 model using weights from ImageNet for the classification task of CN vs AD and sMCI vs pMCI. …”
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Final Year Project / Dissertation / Thesis -
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Segmentation Assisted Object Distinction For Direct Volume Rendering
Published 2013“…A set of image processing techniques are creatively employed in the design of K-means based hybrid segmentation algorithm.…”
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Edge assisted crime prediction and evaluation framework for machine learning algorithms
Published 2022“…To anticipate occurrences, ML methods such as Decision Trees, Neural Networks, K-Nearest Neighbors, and Impact Learning are being utilized, and their performance is compared based on the data processing and modification used. …”
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Processing and classification of landsat and sentinel images for oil palm plantation detection
Published 2022“…It first focuses on the correction algorithm needed to estimate the true surface reflectance value of the satellite image data before the image is filtered to reduce any noise. …”
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Exploring frogeye leaf spot disease severity in soybean through hyperspectral data analysis and machine learning with Orange Data Mining
Published 2025“…Objectives: The main objective of the study is to classify the severity level of FLS disease in soybean using hyperspectral reflectance data and machine learning algorithms. Materials and Methods: We used hyperspectral reflectance data from healthy and FLS of soybeans. …”
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