Search Results - (( using function sensor algorithm ) OR ( using classification using algorithm ))
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1
Jogging activity recognition using k-NN algorithm
Published 2022“…Jogging activity recognition using the k-NN algorithm is a system that can help users collect information data of user speed movement using speed sensor and give the classification of jogging activity to the user. …”
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2
The application of neural network data mining algorithm into mixed pixel classification in geographic information system environment
Published 2007“…Region growing segmentation and radial basis function algorithms are considered a powerful tool to minimize the mixed pixel classification error.…”
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3
ESS-IoT: The Smart Waste Management System for General Household
Published 2024“…Waste collection is triggered by the overflow alarm mechanism that employs ultrasonic and tracker sensors. On the other hand, the waste classification is implemented using two classification algorithms: Random Forest (RF) prediction model and Convolutional Neural Network (CNN) prediction model. …”
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4
Development of rheumatoid arthritis classification from electronic image sensor using ensemble method
Published 2020“…Three ensemble algorithms such as bagging, Adaboost, and random subspace were used in the study. …”
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5
Smart fall detection by enhanced SVM with fuzzy logic membership function
Published 2023“…In addition, they use thresholds to identify falls based on artificial experiences or machine learning (ML) algorithms. …”
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6
Improvement of land cover mapping using Sentinel 2 and Landsat 8 imageries via non-parametric classification
Published 2020“…Nevertheless, AC is not required for LCM if the original multi-spectral image is used. The last phase involves developing a new fusion algorithm using SVM and Fuzzy K-Means Clustering (FKM) algorithms for Sentinel 2 data to enhance LCM accuracy. …”
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7
Development of drift conversion algorithm for ISFET based pH sensor for continuous measurement system
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8
Anomaly detection in ICS datasets with machine learning algorithms
Published 2021“…The features of flow-based network traffic are extracted for behavior analysis with port-wise profiling based on the data baseline, and anomaly detection classification and prediction using machine learning algorithms are performed.…”
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Learner’s emotion prediction using production rules classification algorithm through brain computer interface tool
Published 2018“…From the data analysis using WEKA software, the production rules classifier (PART) is found to be the most accurate classification algorithm in classifying the emotion which yields the highest precision percentage of 99.6% compared to J48 (99.5%) and Naïve Bayes (96.2%). …”
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10
Development of electromyography-controlled 3D printed robot hand and supervised machine learning for signal classification
Published 2019“…The current study of the hand posture classification requires a higher number of EMG sensor used to achieve an accurate classification performance that leads the system to be complicated. …”
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11
E-nose for basal stem rot detection
Published 2010“…An electronic nose is an intelligent device, able to mimic human olfaction functions and may be used for detection, recognition and classification of volatile compounds and odours. …”
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12
Anfis Modelling On Diabetic Ketoacidosis For Unrestricted Food Intake Conditions
Published 2017“…The fuzzy inference model will be used to capture both fasting and non-fasting membership functions before feeding the results for classification to the neural network model. …”
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13
Terahertz sensing analysis for early detection of ganoderma boninense disease using near infrared (NIR) spectrometer
Published 2023“…In classification, four different ML algorithms: K-Nearest Neighbour (kNN), Naïve Bayes (NB), Support Vector Machine (SVM) and Decision Tree (DT) are tested to classify healthy and infected oil palm samples. …”
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14
Performance evaluation for compression-accuracy trade-off using compressive sensing for EEG-based epileptic seizure detection in wireless tele-monitoring
Published 2013“…A reconstructed algorithm derived from DCT of daubechie’s wavelet 6 is used to decompose the EEG signal at different levels. …”
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15
Study of hand gesture recognition using impulse radio ultra wideband (IRUWB) radar sensor
Published 2023“…The developed algorithms interpret raw IR-UWB radar sensor data and associate it with specific hand gestures, addressing the core objective of gesture recognition. …”
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16
Development of a new robust hybrid automata algorithm based on surface electromyography (SEMG) signal for instrumented wheelchair control
Published 2020“…Meanwhile, pattern recognition is using Probability Density Function (PDF) to determine MUAP according to type of activities. …”
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17
Identification of autism subtypes based on wavelet coherence of BOLD FMRI signals using convolutional neural network
Published 2021“…The dynamic FC patterns of wavelet coherence scalogram represent phase synchronization between the pairs of BOLD signals. Classification algorithms are developed using CNN and the wavelet coherence scalograms for binary and multi-class identification were trained and tested using cross-validation and leave-one-out techniques. …”
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18
Identification of autism subtypes based on wavelet coherence of BOLD FMRI signals using convolutional neural network
Published 2021“…The dynamic FC patterns of wavelet coherence scalogram represent phase synchronization between the pairs of BOLD signals. Classification algorithms are developed using CNN and the wavelet coherence scalograms for binary and multi-class identification were trained and tested using cross-validation and leave-one-out techniques. …”
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Improving multi-resident activity recognition in smart home using multi label classification with adaptive profiling
Published 2018“…Furthermore, there is tendency that multi label classifications used instead of traditional single label classification technique. …”
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20
Forensic language of property theft genre based on mathematical formulae and machine learning algorithms / Hana' Abd Razak
Published 2020“…Convolution Neural Network (CNN) using deep learning algorithm is chosen in identifying frequency of movement and execution time of housebreaking crime. …”
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