Search Results - (( spatial visualization learning algorithm ) OR ( java application learning algorithm ))
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Lightweight spatial attentive network for vehicular visual odometry estimation in urban environments
Published 2022“…Traditional visual odometry algorithms require the careful fabrication of state-of-the-art building blocks based on geometry. …”
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Lightweight spatial attentive network for vehicular visual odometry estimation in urban environments
Published 2022“…Traditional visual odometry algorithms require the careful fabrication of state-of-the-art building blocks based on geometry. …”
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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, instead of concatenating feature vectors together and send to classifier, sparse coding and dictionary learning methods are used and instead of considering all features as one view (visual feature), K-SVD algorithm that is one of the famous algorithms for sparse representation is optimized and developed to multi-view model.The experimental results prove that the proposed methods has improved accuracy by 53.77% compared to concatenating features and classic K-SVD dictionary learning model as well.…”
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Thesis -
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The comparison of interactive 3D visualization between static and animated approaches for learning binary tree topic / Mohd Zulhisam Yaakub
Published 2016“…This shows that both 3D visualization methods implemented in this study can increase the student learning achievements and spatial abilities. …”
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A hybrid spiking neural network model for multivariate data classification and visualization.
Published 2011“…SOM is one of the most prominent unsupervised learning algorithms. Recently, many extensions for SOM have been proposed for temporal processing. …”
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Proceeding -
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A review of machine learning in hyperspectral imaging for food safety
Published 2025“…To address these limitations, advances in non-destructive monitoring techniques with the implementation of machine learning (ML) algorithms can be alternative solutions. …”
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Kernerlized Correlation Filters Parameters Optimization For Enhanced Visual Tracking
Published 2017“…A lot of researches have been conducted and many types of state-of-the-art methods and modifications such as sparse representation, online similarity learning, self-expressive, spatial kernel phase correlation filter and others are proposed in order to increase the robustness of the tracking. …”
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An Educational Tool Aimed at Learning Metaheuristics
Published 2020“…In this paper, we introduce an education tool for learning metaheuristic algorithms that allows displaying the convergence speed of the corresponding metaheuristic upon setting/changing the dependable parameters. …”
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A Feature Ranking Algorithm in Pragmatic Quality Factor Model for Software Quality Assessment
Published 2013“…The methodology used consists of theoretical study, design of formal framework on intelligent software quality, identification of Feature Ranking Technique (FRT), construction and evaluation of FRA algorithm. The assessment of quality attributes has been improved using FRA algorithm enriched with a formula to calculate the priority of attributes and followed by learning adaptation through Java Library for Multi Label Learning (MULAN) application. …”
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Coherent crowd analysis with visual attributes / Nurul Japar
Published 2022“…Therefore, contextual information from visual attributes is essential in learning semantic relations among individuals. …”
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Clustering Based on Customers’ Behaviour in Accepting Personal Loan using Unsupervised Machine Learning
Published 2023“…Focusing on clustering algorithms, the study employs popular methods like K-Means Clustering, Density-Based Spatial Clustering of Applications with Noise (DBSCAN), Agglomerative Hierarchical Clustering, and Mean Shift Clustering to understand customer characteristics and behaviors. …”
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Predicting saliency existence using reduced salient features based on compactness and boundary cues
Published 2020“…The selected salient features were trained, tested and compared on 3 learning algorithms which included generalised linear regression, Naïve Bayes, and Support Vector Machine. …”
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Thesis -
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Adoption of machine learning algorithm for analysing supporters and non supporters feedback on political posts / Ogunfolajin Maruff Tunde
Published 2022“…This thesis is based on the application of sentiment classification algorithm to tweet data with the goal of classifying messages based on the polarity of sentiment towards a particular topic (or subject matter). …”
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Real-Time Flood Inundation Map Generation Using Decision Tree Machine Learning Method: Case Study of Kelantan River Basins
Published 2024“…To forecast unexpected flood occurrences, faster flood prediction necessitates computational prediction models such as Machine Learning (ML) algorithms, which are extensively utilized around the world. …”
Book chapter -
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Extremal region detection and selection with fuzzy encoding for food recognition
Published 2019“…By decreasing the quantity of interest regions, the time efficiency of feature encoding can thus be improved without sacrificing classification accuracy. The ERS algorithm is performed using unsupervised learning to determine the spatial information of the interest regions detected, indicating whether they are from the image background, and can thus be removed as noise. …”
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Classification of labour pain using electroencephalogram signal based on wavelet method / Sai Chong Yeh
Published 2020“…Supervised and unsupervised machine learning algorithms particularly the Support Vector Machine (SVM) and Density Based Spatial Clustering of Application with Noise (DBSCAN) are used in this study. …”
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Thesis -
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Development Of Machine Learning User Interface For Pump Diagnostics
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Monograph -
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AI powered asthma prediction towards treatment formulation: an android app approach
Published 2022“…TensorFlow is utilized to integrate machine learning with an Android application. We accomplished asthma therapy using an Android application developed in Java and running on the Android Studio platform.…”
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