Search Results - (( based optimization method algorithm ) OR ( based classification sensor algorithm ))
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Integrated approach using data mining-based decision tree and object-based image analysis for high-resolution urban mapping of WorldView-2 satellite sensor data
Published 2016“…The developed DT algorithm was applied to object-based classifications in the first study area. …”
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Activity recognition using optimized reduced kernel extreme learning machine (OPT-RKELM) / Yang Dong Rui
Published 2019“…One of the major research problems is the computation resources required by machine learning algorithm used for classification for HAR. Numerous researchers have tried different methods to enhance the algorithm to improve performance, some of these methods include Support Vector Machine (SVM), Decision Trees, Extreme Learning Machine (ELM), Kernel Extreme Learning Machine (KELM), and Deng’s Reduced Kernel Extreme Learning Machine (RKELM). …”
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Class binarization with self-adaptive algorithm to improve human activity recognition
Published 2018“…To enhance the selection of most highly ranking features, irrelevant features are ‘pruned’ based on determined boundary threshold. In order to estimate the quality of ‘pruned’ features, self-adaptive DE algorithm is proposed. …”
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3D LiDAR Vehicle Perception and Classification Using 3D Machine Learning Algorithm
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Classification of Agarwood using ANN
Published 2012“…The network developed based on three layers feed forward network and the back propagation learning algorithm was used in executing the network training. …”
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Study of hand gesture recognition using impulse radio ultra wideband (IRUWB) radar sensor
Published 2023“…First objective is to determine the optimal setup for IR-UWB radar sensor data acquisition, considering factors such as sensor placement and configuration. …”
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Classification of agarwood using ANN / Muhammad Sharfi Najib ...[et al.]
Published 2012“…The network developed based on three layers feed forward network and the back propagation learning algorithm was used in executing the network training. …”
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A performance comparison study of pattern recognition systems for volatile organic compounds detection / Emilia Noorsal, Muhammad Khusairi Osman and Norfadzilah Mokhtar
Published 2007“…The optimum structure of the neural network was determined by trial and error method to obtain the optimized hidden neuron and weight values. …”
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Configuration and analysis of piezoelectric-based in socket sensory system for transfemoral prosthetic Gait detection / Farahiyah Jasni
Published 2018“…Findings from the simulation study suggested that Polyvinylidene Fluoride (PVDF)-based, small rectangular piezoelectric sensor yielded the highest output voltage. …”
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Development of electromyography-controlled 3D printed robot hand and supervised machine learning for signal classification
Published 2019“…However, the current research state is unsatisfactory, especially in terms of structural design, robot system and the robot control method. In this research, an EMG controlled 3D printed robot hand prototype with improved features and advance hand posture classification method based on EMG signal pattern were proposed. …”
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Drowsiness Detection Using Ocular Indices from EEG Signal
Published 2022“…Different machine learning classification models, including the decision tree, the support vector machine (SVM), the K-nearest neighbor (KNN) method, and the bagged and boosted tree models, were trained based on the seven selected features. …”
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Pothole detection using multispectral sensor and unmanned aerial vehicle imagery / Muhammad Hafiz Aizuddin Mohd Zaidi
Published 2024“…The aim of this study is to evaluate the effects of multispectral sensors on pothole detection using very high-resolution images captured by Unmanned Aerial Vehicles (UAVs) based on the structure-from-motion photogrammetry approach. …”
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Performance comparison of classification algorithms for EEG-based remote epileptic seizure detection in wireless sensor networks
Published 2014“…Identification of epileptic seizure remotely by analyzing the electroencephalography (EEG) signal is very important for scalable sensor-based health systems.Classification is the most important technique for wide-ranging applications to categorize the items according to its features with respect to predefined set of classes.In this paper, we conduct a performance evaluation based on the noiseless and noisy EEG-based epileptic seizure data using various classification algorithms including BayesNet, DecisionTable, IBK, J48/C4.5, and VFI.The reconstructed and noisy EEG data are decomposed with discrete cosine transform into several sub-bands.In addition, some of statistical features are extracted from the wavelet coefficients to represent the whole EEG data inputs into the classifiers.Benchmark on widely used dataset is utilized for automatic epileptic seizure detection including both normal and epileptic EEG datasets.The classification accuracy results confirm that the selected classifiers have greater potentiality to identify the noisy epileptic disorders.…”
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The Potential of a Classification-based Algorithm to Calculate Calories in Real-Time Via Pattern Recognition
Published 2016“…While the algorithm helped to classify different types of wavelengths produced from the sensor, a classification-based algorithm via Pattern Recognition Method will be used to classify and match the food components. …”
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Combining data mining algorithm and object-based image analysis for detailed urban mapping of hyperspectral images
Published 2014“…The high accuracy of object-based classification can be linked to the knowledge discovery produced by the DM algorithm. …”
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Development of rheumatoid arthritis classification from electronic image sensor using ensemble method
Published 2020“…The performance was also measured based on the comparison of the overall classification accuracy rate between different ensembles classifiers and the base learners. …”
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AUTONOMOUS MOBILE ROBOT VISION BASED SYSTEM: HUMAN DETECTION BY COLOR
Published 2013“…There have two part are involve which is mobile robot platform and classification algorithms by color. The core of the classification of color are comprise into two process; offline and online. …”
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A review: radar-based fall detection sensor / Hidayatusherlina Razali ... [et al.]
Published 2024“…Radar-based sensors can accurately capture Doppler frequency variations from human motion by utilising time-frequency representations and classification algorithms. …”
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