Search Results - (( data visualization learning algorithm ) OR ( data evaluation method algorithm ))
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A review on monocular tracking and mapping: from model-based to data-driven methods
Published 2022“…This article starts by introducing the basic sensor systems and analyzing the evolution of monocular tracking and mapping algorithms through bibliometric data. Then, it covers the overview of filtering and bundle adjustment methods, followed by recent advancements in methods using deep learning with the mathematical constraints applied on the networks. …”
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Virtual reality in algorithm programming course: practicality and implications for college students
Published 2024“…The analysis of learning problems shows the unavailability of interactive learning media that can support various learning styles of students in programming algorithm materials. …”
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Evaluation and Comparative Analysis of Feature Extraction Methods on Image Data to increase the Accuracy of Classification Algorithms
Published 2024“…Feature extraction is essential in classification, especially for data sources in the form of images. It involves identifying and isolating relevant information from the images that classification algorithms can use to distinguish between different fruit categories. …”
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Edge assisted crime prediction and evaluation framework for machine learning algorithms
Published 2022“…In particular, this study proposes a crime prediction and evaluation framework for machine learning algorithms of the network edge. …”
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Conference or Workshop Item -
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Musical instrument identification using Convolutional Neural Network (CNN) algorithm / Muhammad Nur Azri Irfan Abdul Rahman
Published 2025“…This approach tried to overcome the limitations of the manual method and traditional algorithm, which tends to fail with the diverse dataset, diverse visual features, and scalability. …”
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Thesis -
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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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Customer mobile behavioral segmentation and analysis in telecom using machine learning
Published 2021“…The study applied analytic pipeline that involved five stages i.e. data generation, data pre-processing, data clustering, clusters analysis, and data visualization. …”
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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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Applications of contemporary artificial intelligence technology in forensic odontology as primary forensic identifier : A scoping review
Published 2022“…Occasionally, transfer learning was used to overcome the limitation of data. …”
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Deep Reinforcement Learning For Control
Published 2021“…The complete project is carried out in the CARLA simulator to determine how to operate in discrete action space using Deep Reinforcement Learning (DRL) algorithms. Gathering and evaluating a large amount of data is time and effortintensive. …”
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Monograph -
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Low-light image analysis and contrast enhancement using gaussian process / Loh Yuen Peng
Published 2018“…The second contribution is an in-depth analysis of the collected data, specifically, by studying the global and local pixel intensities, followed by the performance and visualizations of hand-crafted and learned features. …”
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A Hybrid Artificial Intelligence Model for Detecting Keratoconus
Published 2023“…We compared the proposed method with three other standard unsupervised algorithms including k-means, Kmedoids, and Spectral cluster. …”
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Predictive analytics for the sentiment of malaysian place of interest using machine learning models
Published 2023“…Furthermore, this study also trains three machine learning algorithms to predict the sentiment of textual data. …”
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Undergraduates Project Papers -
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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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High-Resolution Downscaling with Interpretable Relevant Vector Machine: Rainfall Prediction for Case Study in Selangor
Published 2024“…The Principal Component Analysis (PCA) technique was employed to choose relevant environmental variables as input for the machine learning model, and various imputation methods were utilized to manage missing data, such as mean imputation and the KNN algorithm. …”
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Identifying suicidal ideation through twitter sentiment analysis using Naïve Bayes / Annasuha Atie Atirah Alias
Published 2023“…By harnessing natural language processing techniques and data visualization tools, the project seeks to provide user-friendly solution for early detection and prevention of suicidal intentions expressed on social media. …”
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Sentiment analysis on the place of interest in Malaysia
Published 2025“…The dataset was then split into training and testing sets, and three supervised learning algorithms which are Support Vector Machine, Random Forest, and Naive Bayes were employed to evaluate the sentiment analysis models. …”
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EEG-Based Person Authentication Modelling Using Incremental Fuzzy-Rough Nearest Neighbour Technique
Published 2016“…The IncFRNN technique was evaluated using a collected EEG data from 37 subjects. …”
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Intelligent image noise types recognition and denoising system using deep learning / Khaw Hui Ying
Published 2019“…In order to reduce the training time and computational cost of the algorithm, Principal Components Analysis (PCA) pretraining strategy is deployed to obtain data adaptive filter banks. …”
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