Search Results - (( model evaluation based algorithm ) OR ( parameter automation model algorithm ))
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1
Reactive approach for automating exploration and exploitation in ant colony optimization
Published 2016“…The third component is the ACO-based adaptive parameter selection algorithm to solve the parameterization problem which relies on quality, exploration and unified criteria in assigning rewards to promising parameters. …”
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2
Deep Learning Based image segmentation for expensive soil desiccation crack recognition and qualification
Published 2025“…The objectives of the study included designing soil desiccation experiment setup for desiccation crack image acquisition, evaluating crack imaging analysis based on deep learning algorithms, and quantifying desiccation cracks through image processing techniques. …”
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3
Prediction of Oil Palm Yield Using Machine Learning in the Perspective of Fluctuating Weather and Soil Moisture Conditions: Evaluation of a Generic Workflow
Published 2023“…Multisource data and conventional machine learning techniques were coupled with an automated model selection process. The performance of two top regression models, namely Extra Tree and AdaBoost was evaluated using six statistical evaluation metrics. …”
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4
Optimize and deploy machine learning algorithms on embedded devices for manufacturing applications
Published 2025“…On the other hand, network compression and acceleration techniques such as pruning and quantization also been the focus of the studies for light-weight algorithms in embedded system. While in our studies, we primarily focusing on the deployment and fine-tuning of deep learning model which is YOLOv5 for PCB defects detection. …”
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5
A Novel Hybrid Deep Learning Model Based on Simulated Annealing and Cuckoo Search Algorithms for Automatic Radiomics-Based COVID-19 Diagnosis
Published 2025“…Given that the specificity for discriminating between the causes of conventional pulmonary features is lower than its sensitivity, the primary goal of this study is to develop and evaluate a CT-based radiomics model capable of distinguishing between COVID-19 and other lung diseases. …”
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6
Optimal model order selection for transient error autoregressive moving average (TERA) MRI reconstruction method
Published 2008“…These criteria were evaluated on MRI data sets based on the method of Transient Error Reconstruction Algorithm (TERA). …”
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7
Adaptive linux-based TCP congestion control algorithm for high-speed networks
Published 2017“…Further, we propose a novel mathematical model to calculate the average throughput of the AF-based CCA. …”
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8
Classification of diabetic retinopathy clinical features using image enhancement technique and convolutional neural network / Abdul Hafiz Abu Samah
Published 2021“…Based on investigation different architecture and parameter, the suitable deep learning model has been presented to get optimize best result and testing time. …”
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9
Stereo Camera-Based Aerial Target Geolocation in a Ground-Based Platform Environment
Published 2024thesis::master thesis -
10
Experimental and AI-driven enhancements in gas-phase photocatalytic CO2 conversion over synthesized highly ordered anodic TiO2 nanotubes
Published 2025“…Compared to other ML models, the artificial neural networks (ANN) model showed an outstanding rating of performance evaluation metrics, including R2, MSE, RMSE, and MRE. …”
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11
Applications of contemporary artificial intelligence technology in forensic odontology as primary forensic identifier : A scoping review
Published 2022“…Objective: This article aims to evaluate current artificial intelligence applications and discuss their performance concerning the algorithm architecture used in forensic odontology. …”
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12
Real-time oil palm fruit bunch ripeness grading system using image processing techniques
Published 2013“…These results are optimal based on the thorns model. A new approach was developed using expert rules-based system. …”
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13
Automated-tuned hyper-parameter deep neural network by using arithmetic optimization algorithm for Lorenz chaotic system
Published 2023“…Deep neural networks (DNNs) are very dependent on their parameterization and require experts to determine which method to implement and modify the hyper-parameters value. This study proposes an automated-tuned hyper�parameter for DNN using a metaheuristic optimization algorithm, arithmetic optimization algorithm (AOA). …”
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14
Automated Model Generation Approach Using MATLAB
Published 2011“…An estimation algorithm is then required in order to obtain parameters for these models. …”
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15
Automated-tuned hyper-parameter deep neural network by using arithmetic optimization algorithm for Lorenz chaotic system
Published 2023“…Deep neural networks (DNNs) are very dependent on their parameterization and require experts to determine which method to implement and modify the hyper-parameters value. This study proposes an automated-tuned hyper-parameter for DNN using a metaheuristic optimization algorithm, arithmetic optimization algorithm (AOA). …”
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16
Using simulated annealing algorithm for optimization of quay cranes and automated guided vehicles scheduling
Published 2011“…In this paper, an integrated scheduling of quay cranes and automated guided vehicles is formulated as a mixed integer linear programming model. …”
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17
Improving multi-resident activity recognition in smart home using multi label classification with adaptive profiling
Published 2018“…In addition, three days of house A from ARAS dataset is also selected to evaluate its effectiveness. LC-RF is tested with other base classifiers such as k-NN, SVM and HMM. …”
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18
Different mutation and crossover set of genetic programming in an automated machine learning
Published 2020“…The function of Genetic Programming is to optimize the best combination of solutions from the possible pipelines of machine learning modelling, including selection of algorithms and parameters optimization of the selected algorithm. …”
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19
Different mutation and crossover set of genetic programming in an automated machine learning
Published 2020“…The function of Genetic Programming is to optimize the best combination of solutions from the possible pipelines of machine learning modelling, including selection of algorithms and parameters optimization of the selected algorithm. …”
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20
Spectral and prosodic feature extractions for classical Arabic accents recognition among Malay speakers / Noor Jamaliah Ibrahim
Published 2021“…Our aim was to make use of the Gaussian Mixture Models-Universal Background Model (GMM-UBM) for automated classification of speech and make comparison with the conventional Gaussian Mixture Model (GMM). …”
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