Search Results - (( model evaluation based algorithm ) OR ( image classification swarm algorithm ))*
Search alternatives:
- image classification »
- classification swarm »
- model evaluation »
- evaluation based »
- swarm algorithm »
-
1
Optimized image enhancement of colour processing for retinal fundus image
Published 2025“…It achieved a 95.034% success rate in classification accuracy. The study introduces a new colour correction model and an optimized image enhancement model, significantly improving retinal fundus image quality and establishing the most effective model for image quality enhancement…”
Get full text
Get full text
Get full text
Get full text
Thesis -
2
Optimized image enhancement of colour processing for retinal fundus image
Published 2025“…It achieved a 95.034% success rate in classification accuracy. The study introduces a new colour correction model and an optimized image enhancement model, significantly improving retinal fundus image quality and establishing the most effective model for image quality enhancement…”
Get full text
Get full text
Get full text
Get full text
Thesis -
3
Automatic Segmentation and Classification of Skin Lesions in Dermoscopic Images
Published 2024“…For segmentation, the first proposed algorithm is based on the boundary condition model, which is tested over the ISIC dataset and achieved 96% of accuracy. …”
Get full text
Get full text
Get full text
Get full text
Thesis -
4
An ensemble learning method for spam email detection system based on metaheuristic algorithms
Published 2015“…Recently, various techniques based on different algorithms have been developed. …”
Get full text
Get full text
Thesis -
5
Intelligent image noise types recognition and denoising system using deep learning / Khaw Hui Ying
Published 2019“…Based on the final denoised images, the model has proven its reliability, in terms of both visual quality and quantitative evaluation. …”
Get full text
Get full text
Get full text
Thesis -
6
Optimized techniques for landslide detection and characteristics using LiDAR data
Published 2018“…The segmentation process was optimized using Fuzzy-based Segmentation Parameter. Also, six techniques: Ant Colony Optimization (ACO), Gain Ratio (GR), Particle Swarm Optimization (PSO) and Genetic Algorithm (GA), Random forest (RF), and Correlation-based Feature Selection (CFS) were used for the feature selection. …”
Get full text
Get full text
Get full text
Thesis -
7
Sauvola Segmentation and Support Vector Machine-Salp Swarm Algorithm Approach for Identifying Nutrient Deficiencies in Citrus Reticulata Leaves
Published 2024“…In the next phase, the datasets are optimized using the Salp Swarm Algorithm (SSA), which improves classification accuracy. …”
Get full text
Get full text
Get full text
Get full text
Thesis -
8
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. …”
Get full text
Get full text
Thesis -
9
A new hybrid technique for nosologic segmentation of primary brain tumors / Shafaf Ibrahim
Published 2015“…This study presents an algorithm for nosologic segmentation of primary brain tumors on Magnetic Resonance Imaging (MRI) brain images. …”
Get full text
Get full text
Book Section -
10
STATISTICAL FEATURE LEARNING THROUGH ENHANCED DELAUNAY CLUSTERING AND ENSEMBLE CLASSIFIERS FOR SKIN LESION SEGMENTATION AND CLASSIFICATION
Published 2021“…Moreover, skin lesion images are clustered based on fused color, pattern and shape based features. …”
Get full text
Get full text
Get full text
Article -
11
Whale Optimisation Freeman Chain Code (WO-FCC) extraction algorithm for handwritten character recognition
Published 2021“…In order to improve the classification accuracy in the field of handwriting character recognition (HCR), the number of derivative algorithms has improved and the interest in feature extraction has increased. …”
Get full text
Get full text
Get full text
Conference or Workshop Item -
12
Liver segmentation on CT images using random walkers and fuzzy c-means for treatment planning and monitoring of tumors in liver cancer patients
Published 2017“…This is followed by the clustering of the liver tissues using particle swarm optimized spatial FCM algorithm. Then, these tissues are classified into tumors and blood vessels by an AdaBoost classification method based on tissue features extracted utilizing first, second and higher order image features selected by a minimal-redundancy maximalrelevance feature selection approach. …”
Get full text
Get full text
Get full text
Thesis -
13
Face Recognition Approach using an Enhanced Particle Swarm Optimization and Support Vector Machine
Published 2019“…In the feature extraction process, the PCA algorithm is used for that purpose and the resulted features are delivered to the proposed technique in order to classify the face images. …”
Get full text
Get full text
Get full text
Get full text
Article -
14
Enhancing land cover classification in remote sensing imagery using an optimal deep learning model
Published 2023“…The current study presents an Improved Sand Cat Swarm Optimization with Deep Learning-based Land Cover Classification (ISCSODL-LCC) approach on the RSIs. …”
Get full text
Get full text
Get full text
Get full text
Get full text
Article -
15
Automated diagnosis of focal liver lesions using bidirectional empirical mode decomposition features
Published 2018“…After which, the extracted features were subjected to particle swarm optimization (PSO) technique for the selection of a set of optimized features for classification. …”
Get full text
Get full text
Article -
16
An Optimized Semantic Segmentation Framework for Human Skin Detection
Published 2024“…Existing approaches used complex and various heuristic designs of image processing algorithms and deep models customized for skin detection problems. …”
Get full text
Get full text
Get full text
Article -
17
-
18
-
19
Incorporating the range-based method into GridSim for modeling task and resource heterogeneity
Published 2017“…As heterogeneity is one of the unique characteristics of Grid computing, which induces additional challenges in designing heuristic-based scheduling algorithms, the main concern when performing simulation experiments for evaluating the performance of scheduling algorithms is how to model and simulate different Grid scheduling scenarios or cases that capture the inherent nature of heterogeneity of Grid computing environment. …”
Get full text
Get full text
Get full text
Article -
20
Dynamic Bayesian networks and variable length genetic algorithm for designing cue-based model for dialogue act recognition
Published 2010“…In this paper, a new cue-based model for dialogue act recognition is presented. …”
Get full text
Get full text
Article
