Search Results - (( java implication bat algorithm ) OR ( parameter segmentation means algorithm ))
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1
Using a novel algorithm in ultrasound images to detect renal stones
Published 2021“…The pre-processed image is taken as input for the segmentation process. Fuzzy C-means, K-means, and Expectation–Maximization algorithms are used to segment the renal calculi from the kidney ultrasound image; further region parameters are extracted from the segmented region. …”
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Proceedings -
2
Individual-tree segmentation and extraction based on LiDAR point cloud data
Published 2024“…Utilizing LiDAR point cloud data and ground-measured data from 30 plots, we examined the sensitivity of individual tree segmentation to key parameters by varying the grid values of the point cloud distance discriminant clustering algorithm and adjusting the canopy height resolution (CHR) of the watershed algorithm. …”
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Article -
3
A hyper-heuristic based strategy for image segmentation using multilevel thresholding
Published 2025“…Although effective, these algorithms get stuck in local optima and need proper parameter tuning for solving optimisation problems. …”
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4
A hyper-heuristic based strategy for image segmentation using multilevel thresholding
Published 2025“…Although effective, these algorithms get stuck in local optima and need proper parameter tuning for solving optimisation problems. …”
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5
Model-based hybrid variational level set method applied to lung cancer detection
Published 2024“…The improved multi-scale mean filter approximates the image’s offset field, effectively reducing gray-scale inhomogeneity and eliminating the influence of scale parameter selection on segmentation. …”
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Article -
6
Non-invasive gliomas grading using swarm intelligence algorithm / Muhammad Harith Ramli
Published 2017“…Bat algorithm is chosen for the development of the prototype for segmentation and classification purpose. …”
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Thesis -
7
Development of hippocampus MRI image segmentation algorithm for progression detection of alzheimer’s disease (AD)
Published 2022“…The algorithm will be able to identify the parameters, such as the number of pixels, area pixels, and mean value, by extracting the hippocampal shape. …”
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Thesis -
8
Model-based hybrid variational level set method applied to object detection in grey scale images
Published 2024“…This algorithm leverages an improved multi-scale mean filter to mitigate grayscale inhomogeneity while reducing the impact of scale parameter selection. …”
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Thesis -
9
Color image enhancement of acute leukemia cells in blood microscopic image for leukemia detection sample
Published 2020“…The segmentation algorithm uses saturation S-component based on Hue, Saturation, Intensity (HSI) color model. …”
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Conference or Workshop Item -
10
Extremal region selection for MSER detection in food recognition
Published 2021“…Therefore, this research proposes an Extremal Region Selection (ERS) algorithm to improve MSER detection by reducing the number of irrelevant extremal regions by using unsupervised learning based on the k-means algorithm. …”
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Article -
11
Digital segmentation of skin diseases / Hadzli Hashim and Razali Abdul Hadi
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Research Reports -
12
Extremal Region Selection for MSER Detection in Food Recognition
Published 2021“…Therefore, this research proposes an Extremal Region Selection (ERS) algorithm to improve MSER detection by reducing the number of irrelevant extremal regions by using unsupervised learning based on the k-means algorithm. …”
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Article -
13
Implementation of YOLOv8-seg on store products to speed up the scanning process at point of sales
Published 2024“…The method used here is object detection and segmentation of these objects, a combination of detection and segmentation called instance segmentation. …”
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14
HEP-2 CELL IMAGES CLASSIFICATION BASED ON STATISTICAL TEXTURE ANALYSIS AND FUZZY LOGIC
Published 2014“…The algorithm gives a mean accuracy of 84% out of 125 test images.…”
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Final Year Project -
15
Hyper-heuristic approaches for data stream-based iIntrusion detection in the Internet of Things
Published 2022“…Hence, the algorithm must overcome the problem of dynamic updates in the internal parameters or counter the concept drift. …”
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Thesis -
16
Local gray level S-curve transformation – A generalized contrast enhancement technique for medical images
Published 2017“…The performance of the proposed technique is determined by measuring several parameters namely, edge content (improvement in image gradient), enhancement measure (degree of contrast enhancement), absolute mean brightness error (luminance distortion caused by the enhancement), and feature similarity index measure (preservation of the original image features). …”
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17
Acoustic Performance Study Of 3d Printed Micro-Perforated Panel
Published 2021“…The capture images were processed in graph-cut image segmentation algorithm. The circularity of each hole is measured using the processed images and evaluated based on the probability outcomes of specified circularities. …”
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Monograph -
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Development of gender and race recognition system using speech and recognition by using frequency spectrum
Published 2009“…The formant frequencies are obtained by finding a set of predictor coefficient that minimizes the mean square error over a short segment of speech waveform. …”
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Learning Object -
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Data stream clustering by divide and conquer approach based on vector model
Published 2016“…The continuous effort on data stream clustering method has one common goal which is to achieve an accurate clustering algorithm. However, there are some issues that are overlooked by the previous works in proposing data stream clustering solutions; (1) clustering dataset including big segments of repetitive data, (2) monitoring clustering structure for ordinal data streams and (3) determining important parameters such as k number of exact clusters in stream of data. …”
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Article -
20
Lumped parameter modelling in femoral popliteal artery for normal and severe conditions
Published 2018“…In conclusion, the obtained waveform propagation from the linear analysis of the lumped parameter modelling shows that the periodic mean pressures and flow rate distributions in large arteries are highly depend on the resistances and the compliances. …”
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