Search Results - (( intelligence valid mapping algorithm ) OR ( intelligence based training algorithm ))
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Development of an accurate AI-based dermatology assistant for skin disease recognition using YOLOv8 models
Published 2024“…After 500 training epochs, the YOLOv8 Small Model was the most accurate, achieving a precision of 84%, a recall of 77.1%, and a mean average precision (mAP) of 84%. …”
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Proceeding Paper -
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Enhancing Driving Assistance System with YOLO V8-Based Normal Visual Camera Sensor
Published 2023“…After conducting a performance validation, the system achieved a mean average precision (mAP) of 88.2% on train dataset and was able to detect different types of vehicles such as cars, motorcycles, and traffic lights. …”
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Article -
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Stereo Camera-Based Aerial Target Geolocation in a Ground-Based Platform Environment
Published 2024thesis::master thesis -
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Disease detection of solanaceous crops using deep learning for robot vision
Published 2022“…The total dataset of all 23 classes is 16580 images divided into three parts: training set, validation set, and testing set. The dataset used for training is 88% of the total dataset (15000 images), 8% of the dataset performed a validation process (1400 images), and the rest of the 4% dataset is for the test process (699 images). …”
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Dental Age Estimation Using a Convolutional Neural Network Algorithm on Panoramic Radiographs: A Pilot Study in Indonesia
Published 2025journal::journal article -
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Retinal Microvascular Feature Extraction Using Faster Region-based Convolutional Neural Network
Published 2021“…The retinal images were taken from the different public databases to train, test, and validate the performance of this proposed method. …”
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Thesis -
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Optimization and discretization of dragonfly algorithm for solving continuous and discrete optimization problems
Published 2024“…The ANNs trained by the optimized DA also achieve higher accuracy than those trained by some other swarm intelligence algorithms. …”
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Integration of dual intelligent algorithms in shunt active power filter
Published 2013“…This paper presents an integration of dual intelligent algorithms: artificial neural network (ANN) based fundamental component extraction algorithm and fuzzy logic based DC-link voltage self-charging algorithm (fuzzy self-charging algorithm), in a three-phase three-wire shunt active power filter (SAPF). …”
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Conference or Workshop Item -
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Effect of input variables selection on energy demand prediction based on intelligent hybrid neural networks
Published 2015“…The efficacy of these models depends upon many factors such as, neural network architecture, type of training algorithm, input training and testing data set and initial values of synaptic weights. …”
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Development of Machine Learning Algorithm for Acquiring Machining Data in Turning Process
Published 2004“…The design network is trained by presenting several target machining data that the network must learn according to a learning rule (algorithm). …”
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Thesis -
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Optimising neural network training efficiency through spectral parameter-based multiple adaptive learning rates
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Intelligent grading of agarwood essential oil quality using artificial neural network (ANN) / Noratikah Zawani Mahabob
Published 2022“…The training and validation of the ANN was based on optimization of its training parameters and guided by the convergence of the mean squared errors (MSE). …”
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Thesis -
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Tacit knowledge for business intelligence framework using cognitive-based approach
Published 2022“…The framework is validated through Power BI and reviewed by seven experts. …”
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Hybrid Intelligent Warning System for Boiler tube Leak Trips
Published 2017“…The first intelligent warning system (IWS-1) represents the use of pure artificial neural network system whereas the second intelligent warning system (IWS-2) represents merging of genetic algorithms and artificial neural networks as a hybrid intelligent system. …”
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Embedded Artificial Intelligent (AI) To Navigate Cart Follower
Published 2018“…The weights and biases generated through the training process is depended on the training algorithm, initial weights and biases for training and the dataset used in the process. …”
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