Search Results - (( using optimization sensor algorithm ) OR ( a classification using algorithm ))
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1
Whale optimization algorithm based on tent chaotic map for feature selection in soft sensors
Published 2025“…One of the powerful optimization algorithms that is used for feature selection is the Whale Optimization Algorithm (WOA), which is a nature-inspired metaheuristic optimization algorithm that mimics the social behavior of humpback whales. …”
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2
Investigation of the optimal sensor location and classifier for human motion classification
Published 2022“…In addition, this study seeks to find the best classification algorithm for human daily activities. The data recorded at these three locations were analysed using several classification algorithms in both Orange software and MATLAB. …”
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3
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“…Many features were explored by using a DM algorithm, which created the classification rules as a decision tree (DT) structure from the first study area. …”
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4
Smart phone sensor data: Comparative analysis of various classification methods for task of human activity recognition
Published 2018“…Human Activity Recognition has a long history of research and requires further exploration to produce useful and optimal outcomes. Areas such as medicine, daily routine, and security are some benefits that smartphone enables via embedded sensors. …”
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Proceedings -
5
Class binarization with self-adaptive algorithm to improve human activity recognition
Published 2018“…Therefore, feature selection using Relief-f with self-adaptive Differential Evolution (rsaDE) algorithm is proposed to select the most significant features. …”
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6
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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7
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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3D LiDAR Vehicle Perception and Classification Using 3D Machine Learning Algorithm
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Photogrammetric low-cost unmanned aerial vehicle for pothole detection mapping / Shahrul Nizan Abd Mukti
Published 2022“…The study set four main objectives to achieve its aim: (1) To analyse RGB and multispectral sensor calibration, (2) To evaluate the optimal flight parameters for pothole modelling production using RGB imagery, (3) To investigate various classifier algorithms and band combinations for pothole region areas using multispectral imagery and (4) To validate geometric information from the extracted pothole. …”
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10
Flash floods prediction using real time data: an implementation of ANN-PSO with less false alarm
Published 2019“…A suitable combination of the sensors will give the benefit of better precision and improved accuracy when compare to the use of a single sensor. …”
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Proceeding Paper -
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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“…It is well known that the use of a gas sensor array and pattern recognition system offers an effective technique for the identification of volatile organic molecules because of the poor selectivity of a lot of other gas sensors. …”
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Research Reports -
12
Study of hand gesture recognition using impulse radio ultra wideband (IRUWB) radar sensor
Published 2023“…The work begins by providing insights into the state of the art in hand gesture recognition and IR-UWB radar sensor technology. Data collection experiments yield a diverse dataset of hand gestures, including variations in speed, essential for algorithm development. …”
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13
Anfis Modelling On Diabetic Ketoacidosis For Unrestricted Food Intake Conditions
Published 2017“…Odor sensors assembled into Electrical Nose (E-nose) system is used as self-diagnostics pre-test for diabetic’s analysis. …”
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14
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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15
Drowsiness Detection Using Ocular Indices from EEG Signal
Published 2022“…In this study, we examined the possibility of extracting features from the EEG ocular artifacts themselves to perform classification between alert and drowsy states. In this study, we used the BLINKER algorithm to extract 25 blink-related features from a public dataset comprising raw EEG signals collected from 12 participants. …”
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Ensemble Filter Based Feature Selection Technique for Classification of Human Activity Recognition
Published 2025“…An ensemble Random Forest (RF) was used as the base classifier to evaluate the performance of the hybrid algorithm. …”
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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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Configuration and analysis of piezoelectric-based in socket sensory system for transfemoral prosthetic Gait detection / Farahiyah Jasni
Published 2018“…The methodology comprised of selecting: (a) the best piezoelectric sensor to be used in terms of the material, size and shape, (b) the method of mounting the sensors onto the socket, and (c) the placement of the sensors. …”
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19
Framework for pedestrian walking behaviour recognition to minimize road accident
Published 2021“…The results indicate the following: (1) From 262 samples, 66.80% and 48.10% of respondents use mobile phones for calling and chatting, respectively. (2) 263 samples of participants are obtained and analysed, and 90 features are extracted from each sample. (3) 100% classification accuracy are obtained for each class (normal walking, calling, chatting, and running) using the grid optimiser method in machine learning. (4) The precision of classification using Euclidean algorithm for normal walking and calling is 70%. …”
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20
Framework for pedestrian walking behaviour recognition to minimize road accident
Published 2021“…The results indicate the following: (1) From 262 samples, 66.80% and 48.10% of respondents use mobile phones for calling and chatting, respectively. (2) 263 samples of participants are obtained and analysed, and 90 features are extracted from each sample. (3) 100% classification accuracy are obtained for each class (normal walking, calling, chatting, and running) using the grid optimiser method in machine learning. (4) The precision of classification using Euclidean algorithm for normal walking and calling is 70%. …”
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