Search Results - (( based evaluation step algorithm ) OR ( level classification _ algorithm ))
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1
Autism Spectrum Disorder Classification Using Deep Learning
Published 2021“…Finally, the effectiveness of the algorithm is evaluated based on the accuracy performance. …”
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2
Evaluation and Comparative Analysis of Feature Extraction Methods on Image Data to increase the Accuracy of Classification Algorithms
Published 2024“…The classification algorithm used in this research is the Convolutional Neural Network (CNN) algorithm. …”
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3
Analyzing CT images for detecting lung cancer by applying the computational intelligence-based optimization techniques
Published 2022“…Finally, the lung cancer is identified using Autoencoder based Recurrent Neural Network (ARNN) classification algorithm, successfully recognizing the lung cancer features. …”
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4
Feature engineering techniques to classify cause of death from forensic autopsy reports / Ghulam Mujtaba
Published 2018“…These master feature vectors were fed as input to six machine learning algorithms to construct and evaluate the classification models. …”
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5
Satellite Image Segmentation Using Thresholding Technique
Published 2017“…The basic idea of automatic thresholding is to automatically select an optimal or several optimal grey-level threshold values for separating objects of interest in an image from the background based on their grey-level distribution. …”
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6
Exploring frogeye leaf spot disease severity in soybean through hyperspectral data analysis and machine learning with Orange Data Mining
Published 2025“…Objectives: The main objective of the study is to classify the severity level of FLS disease in soybean using hyperspectral reflectance data and machine learning algorithms. …”
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7
A hybrid unsupervised approach toward EEG epileptic spikes detection
Published 2018“…Moreover, since epileptic spike detection is a vital component of epilepsy source localization, therefore this algorithm can be utilized for EEG-based pre-surgical evaluation of epilepsy.…”
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Intelligent image noise types recognition and denoising system using deep learning / Khaw Hui Ying
Published 2019“…It is equally, if not more crucial, to characterize the type and level of the noises present in the images based on its nature and distribution, so that appropriate denoising tools can be applied, achieving a restored image of higher quality. …”
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9
Internal defect detection and reconstruction framework for laminated glass fibre reinforced polymer composite materials
Published 2013“…Therefore, by removmg the low frequency signals, the intemal defect detectability can be improved. Moreover, the classification of an input pattem based on the closest neighbours of the point of interest provides more accurate defect detection in comparison with the classification based on experience data as the defect pattems vary on circumstances in ultrasonic NDE problems.…”
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10
Biometric identification and recognition for iris using failure rejection rate (FRR) / Musab A. M. Ali
Published 2016“…Hence, the objectives of this research are new algorithms development significantly for iris segmentation specifically the proposed Fusion of Profile and Mask Technique (FPM) specifically in getting the actual center of the pupil with high level of accuracy prior to iris localization task, followed by a particular enhancement in iris normalization that is the application of quarter size of an iris image (instead of processing a whole or half size of an iris image) and for better precision and faster recognition with the robust Support Vector Machine (SVM) as classifier. …”
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11
Bacterial image analysis using multi-task deep learning approaches for clinical microscopy
Published 2024“…The performance of the DL techniques is evaluated using the quantitative assessment method based on mean average precision (mAP), precision, recall, and F1-score. …”
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12
Multi-Class Multi-Level Classification of Mental Health Disorders Based on Textual Data from Social Media
Published 2024“…The results of the experiments show that the MCML classification algorithm successfully performs detailed classification and produces promising results for each classification level. …”
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13
Symmetric Key Size for Different Level of Information Classification
Published 2006“…Confidential information can be categorized into various levels of classification. The classification depends on the level of damage to an organization or to national security when the information is disclosed. …”
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14
Minimizing Classification Errors in Imbalanced Dataset Using Means of Sampling
Published 2023“…Classification (of information); Learning algorithms; Students; Class imbalance; Data level; Over sampling; Performance prediction; SMOTE; Spread subsampling; Student performance; Student performance prediction; Under-sampling; Machine learning…”
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15
Novel Adaptive Bacterial Foraging Algorithms for Global Optimisation with Application to Modelling of a TRS
Published 2015“…The constant step size in the original bacterial foraging algorithm causes oscillation in the convergence graph where bacteria are not able to reach the optimum location with large step size, hence reducing the accuracy of the final solution. …”
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16
Iterative And Single-Step Solutions Of Two Dimensional Time-Domain Inverse Scattering Problem Featuring Ultra Wide Band Sensors
Published 2010“…The image reconstruction algorithm was based on the gradient minimization of an augmented cost function defined as the difference between measured and calculated fields. …”
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17
Performance analysis of machine learning algorithms for classification of infection severity levels on rubber leaves
Published 2023“…This work shows that the spectroscopic measurement combined with classification techniques are promising strategy to classify severity level of WRD based on the spectral data of the rubber leaves.…”
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18
Multistep forecasting for highly volatile data using new algorithm of Box-Jenkins and GARCH
Published 2018“…In evaluating the performance of the multistep ahead forecast, the proposed algorithm is employed to daily world gold price series of 5-year data. …”
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19
Algorithmic approaches in model selection of the air passengers flows data
Published 2015“…Algorithm is an important element in any problem solving situation.In statistical modelling strategy, the algorithm provides a step by step process in model building, model testing, choosing the ‘best’ model and even forecasting using the chosen model.Tacit knowledge has contributed to the existence of a huge variability in manual modelling process especially between expert and non-expert modellers.Many algorithms (automated model selection) have been developed to bridge the gap either through single or multiple equation modelling.This study aims to evaluate the forecasting performances of several selected algorithms on air passengers flow data based on Root Mean Square Error (RMSE) and Geometric Root Mean Square Error (GRMSE).The findings show that multiple models selection performed well in one and two step-ahead forecast but was outperformed by single model in three step-ahead forecasts.…”
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20
Effects of Different Superpixel Algorithms on Interactive Segmentations
Published 2022“…Though employed as pre-processing step in many interactive segmentation algorithms, to date, no study has been conducted to assess the effects of such incorporations on the segmentation algorithms. …”
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