Search Results - (( java implementation among algorithm ) OR ( spatial visualization learning algorithm ))
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1
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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2
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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3
Plagiarism Detection System for Java Programming Assignments by Using Greedy String-Tilling Algorithm
Published 2008“…The prototype system, known as Java Plagiarism Detection System (JPDS) implements the Greedy-String-Tiling algorithm to detect similarities among tokens in a Java source code files. …”
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Thesis -
4
Direct approach for mining association rules from structured XML data
Published 2012“…The thesis also provides a two different implementation of the modified FLEX algorithm using a java based parsers and XQuery implementation. …”
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5
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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6
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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7
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 -
8
A Toolkit for Simulation of Desktop Grid Environment
Published 2014“…A simulator for desktop grid environment has been developed using Java as the implementation language due to its wide popularity. …”
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Final Year Project -
9
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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OPTIMIZED MIN-MIN TASK SCHEDULING ALGORITHM FOR SCIENTIFIC WORKFLOWS IN A CLOUD ENVIRONMENT
Published 2023“…According to the simulation results, the proposed algorithm produces the best solution among all algorithms in the proposed cases. � 2021 Little Lion Scientific…”
Review -
11
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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Monograph -
12
Network game (Literati) / Chung Mei Kuen
Published 2003“…The main aspect of this thesis is to produce a networked gaming system, which process players. requested to play the game and enabling users to play the graphical game with people through the network. The algorithm design and implementation method must not only be workable, but also highly efficient in terms of execution speed and response time. …”
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13
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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14
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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16
Attribute reduction based scheduling algorithm with enhanced hybrid genetic algorithm and particle swarm optimization for optimal device selection
Published 2022“…The simulation is implemented with iFogSim and java programming language. …”
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17
Enhancing the Yolov8 algorithm for real-time dental segmentation
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18
Comparison of performances of Jaya Algorithm and Cuckoo Search algorithm using benchmark functions
Published 2022“…CS and JA have implemented in the same platform (Intellij IDEA Community Edition 2020.2.3) using the same language (Java). …”
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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 -
20
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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