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Experimental study of urban growth pattern classification using moving window algorithm
Published 2023“…Urban growth pattern can be generally categorized as either infill, expansion or outlying growth. Moving window algorithm determines urban growth pattern based on moving window analysis and a set of classification rules. …”
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Heavy Transportation Shortest Route using Dijkstra’s algorithm (HETRO) / Nurul Aqilah Ahmad Nezer
Published 2017“…The development tools used in developing this project is NetBeans by using Java for the implementation of the coding. The methodology that used for developing this system is the Dijkstra’s algorithm. …”
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Overview of metaheuristic: classification of population and trajectory
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Embedded system for indoor guidance parking with Dijkstra’s algorithm and ant colony optimization
Published 2019“…BST inserts the nodes in the way that the Dijkstra’s can find the empty parking in fastest way. Dijkstra’s algorithm initials the paths to finding the shortest path while ACO optimizes the paths. …”
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Path planning for unmanned aerial vehicle (UAV) using rotated accelerated method in static outdoor environment
Published 2021“…In this study, a fast iterative method known as Rotated Successive Over-Relaxation (RSOR) is introduced. The algorithm is implemented in a self-developed 2D Java tool, UAV Planner. …”
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Fair bandwidth distribution marking and scheduling algorithm in network traffic classification
Published 2019“…Second, propose an Optimized Time Sliding Window based Three Colour Marker. Finally, propose a new method of obtaining optimal parameters dropping functions for Random Early Detection (RED) algorithm. …”
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Smart appointment organizer for mobile application / Mohd Syafiq Adam
Published 2009“…The main component of this prototype is the use of Dijkstra algorithm to compute the shortest path from source of appointment to the 6 points of destinations within UiTM Shah Alam. …”
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Non-fiducial based electrocardiogram biometrics with kernel methods
Published 2017“…The effectiveness of this algorithm is investigated by comparing with other AC based feature extraction algorithms involving AC/LDA (Linear Discriminant Analysis) and AC/PCA (Principal Component Analysis). …”
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Random subspace K-NN based ensemble classifier for driver fatigue detection utilizing selected EEG channels
Published 2021“…In the present framework, a new channel selection algorithm based on correlation coefficients and an ensemble classifier based on random subspace k-nearest neighbour (k-NN) has been presented to enhance the classification performance of EEG data for driver fatigue detection. …”
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Block Motion Estimation Using Directional Adaptive Search Window
Published 2006“…This classification and the direction of the motion vectors, are used to dynamically adjust the search window size and general orientation. …”
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Arabic Speaker Identification System for Forensic Authentication Using K-NN Algorithm
Published 2023Conference Paper -
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UAV-based RGB/NIR aerial imaging for the detection of Ganoderma disease in oil palm plantation / Ezzati Bahrom
Published 2018“…This study demonstrated classification from UAV-based imagery can be improved using filters for Ganoderma disease detection mapping in oil palm plantation. …”
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Deep learning object detector using a combination of Convolutional Neural Network (CNN) architecture (MiniVGGNet) and classic object detection algorithm
Published 2020“…Based on the experiment result, the percentage of classification accuracy of the network is 80% to 90% and the time for the system to detect the object is less than 15sec/frame. …”
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Direct least squares fitting of ellipses segmentation and prioritized rules classification for curve-shaped chart patterns
Published 2021“…These methods are implemented based on the principles of sliding windows, turning points, and bottom-up piece wise linear approximation. …”
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Block motion estimation using directional adaptive search window
Published 2007“…This classification and the direction of the motion vectors, are used to dynamically adjust the search window size and general orientation. …”
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Automatic microsleep detection based on KNN classifier utilizing selected and effective EEG channels
Published 2024“…The selection of an optimum channel and the use of a competent classification algorithm are crucial for effective microsleep detection. …”
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