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Hill-climber based fuzzy-rough feature extraction with an application to cancer classification
2013
13th International Conference on Hybrid Intelligent Systems (HIS 2013)
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To overcome this problem, this paper presents an efficient approach to predict the dominant genes using fuzzy-rough boundary region-based feature selection in combination with a heuristic hill-climber ...
search method. ...
The performance may also be improved using evolutionary algorithms as search method. ...
doi:10.1109/his.2013.6920499
dblp:conf/his/Dash13
fatcat:tsmuzwnkujemxaekwwj4pp2wtm
A Logistic Chaotic Barnacles Mating Optimizer with Masi Entropy for Color Image Multilevel Thresholding Segmentation
2020
IEEE Access
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Mousavirad published the human mental to search the optimal threshold to increase segmentation efficiency [56] . ...
Gill exploits minimize cross entropy as the objective function, and uses teaching-learning-based optimization algorithm to select multilevel threshold values. ...
doi:10.1109/access.2020.3040177
fatcat:mrmo7kyn5bgzzk4kfko7uaytvm
A Boosted Minimum Cross Entropy Thresholding for Medical Images Segmentation Based on Heterogeneous Mean Filters Approaches
2022
Journal of Imaging
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Minimum cross entropy thresholding (MCET) is one of the frequently used mean-based thresholding methods for medical image segmentation. ...
The proposed model estimates an optimized mean by excluding the negative influence of noise, local outliers, and gray intensity levels; thus, obtaining new mean values for the MCET's objective function ...
Acknowledgments: The authors would like to express their sincere gratitude to Soha Rawas at Beirut Arab University for her valuable advice. ...
doi:10.3390/jimaging8020043
pmid:35200745
pmcid:PMC8877883
fatcat:ya3nwqjbgjayhmeltvgymaot7a
Multi-sensor fusion based on multiple classifier systems for human activity identification
2019
Human-Centric Computing and Information Sciences
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The aim of this study is to propose an innovative multi-sensor fusion framework to improve human activity detection performances and reduce misrecognition rate. ...
To this end, computationally efficient classification algorithms such as decision tree, logistic regression and k-Nearest Neighbors were used to implement diverse, flexible and dynamic human activity detection ...
Acknowledgements The authors would like to thank University of Malaya for sponsoring the paper through the BKP Special grants and researchers that collected the datasets that were used to support this ...
doi:10.1186/s13673-019-0194-5
fatcat:oif3o7dfhzdwhcqeept7t5jypq
A review of channel selection algorithms for EEG signal processing
2015
EURASIP Journal on Advances in Signal Processing
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With the large number of EEG channels acquired, it has become apparent that efficient channel selection algorithms are needed with varying importance from one application to another. ...
In addition, different evaluation approaches such as filtering, wrapper, embedded, hybrid, and human-based techniques have been widely used for the evaluation of the selected subset of channels. ...
[39] presented an automated channel selection method based on CSP in BCI systems. The CSP algorithm is commonly used to derive spatial filters for the multi-channel EEG signals. ...
doi:10.1186/s13634-015-0251-9
fatcat:vdp2xjlvavczrg4l3rvibuyt5m
Fessonia: a Method for Real-Time Estimation of Human Operator Workload Using Behavioural Entropy
[article]
2021
arXiv
pre-print
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We propose a method, named Fessonia, for real-time cognitive workload estimation from multiple parameters of an operator's driving behaviour via the use of behavioural entropy. ...
Fessonia is comprised of: a method to calculate the entropy (i.e. unpredictability) of the operator driving behaviour profile; the Driver Profile Update algorithm which adapts the entropy calculations ...
This work was supported by the UKRI-EPSRC grant EP/R02572X/1 (UK National Centre for Nuclear Robotics). ...
arXiv:2110.01940v1
fatcat:6p5okiidjvh55ffyhz7d5d3szi
Best basis-based wavelet packet entropy feature extraction and hierarchical EEG classification for epileptic detection
2011
Expert systems with applications
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ii) cross-validation (CV) method together with k-Nearest Neighbor (k-NN) classifier used in the training stage to hierarchical knowledge base (HKB) construction, and (iii) in the testing stage, computing ...
The system includes the following three stages: (i) original EEG signals representation by wavelet packet coefficients and feature extraction using the best basis-based wavelet packet entropy method, ( ...
Thanks are also given to the anonymous reviewers for their kind comments improving the quality and presentation of the paper. ...
doi:10.1016/j.eswa.2011.05.096
fatcat:joruptqncncr3oi54gy5eqrxfm
Automated Intracranial Hematoma Classification in Traumatic Brain Injury (TBI) Patients Using Meta-Heuristic Optimization Techniques
2022
Informatics
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The synthetic samples are generated using ADASYN to compensate for the data imbalance. ...
In this study, the Gray Level Occurrence Matrix (GLCM), the Gray Level Run Length Matrix (GLRLM), and Hu moments are used to generate the texture features. ...
Acknowledgments: The authors would like to thank the Manipal Academy of Higher Education (MAHE) for providing the required facility to carry out this research. ...
doi:10.3390/informatics9010004
fatcat:b66ctceshrbtfoqfbjfxfjjdcm
RELIEFF FEATURE SELECTION BASED ALZHEIMER DISEASE CLASSIFICATION USING HYBRID FEATURES AND SUPPORT VECTOR MACHINE IN MAGNETIC RESONANCE IMAGING
2019
INTERNATIONAL JOURNAL OF COMPUTER ENGINEERING & TECHNOLOGY
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After hybrid feature extraction, reliefF feature selection was used for selecting the optimal feature subsets or to reject the irrelevant feature vectors. ...
Then, hybrid feature extraction (Histogram of Oriented Gradients (HOG), Local Binary Patterns (LBP), and Gray-Level Co-Occurrence Matrix (GLCM)) was performed for extracting the feature values from the ...
Initially, the reliefF algorithm randomly selects an instance and then searches for nearest neighbor for the same class is named as nearest hit and for dissimilar classes is named as nearest ...
doi:10.34218/ijcet.10.1.2019.015
fatcat:35wzoi66mng6ne4djws3qqvtbe
ToM2C: Target-oriented Multi-agent Communication and Cooperation with Theory of Mind
[article]
2022
arXiv
pre-print
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It is also crucial for distributed multi-agent systems, where agents are required to communicate and cooperate. In this paper, we introduce such an important social-cognitive skill, i.e. ...
Being able to predict the mental states of others is a key factor to effective social interaction. ...
ACKNOWLEDGEMENTS This work was supported by MOST-2018AAA0102004, NSFC-62061136001, China National Postdoctoral Program for Innovative Talents (Grant No. BX2021008), Qualcomm University Research Grant. ...
arXiv:2111.09189v2
fatcat:2hiqsvhcendybi2itc6nivde3u
Multiple Transferable Recursive Feature Elimination Technique for Emotion Recognition Based on EEG Signals
2019
Symmetry
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However, classical feature selection methods pay little attention to transferring cross-subject information for emotions. ...
To perform cross-subject emotion recognition, a classifier able to utilize EEG data to train a general model suitable for different subjects is needed. ...
Acknowledgments: The authors would like to give our sincere gratitude to Wenwei Yan and Jielin Yan, who have provided a lot of help to polish this article. ...
doi:10.3390/sym11050683
fatcat:lspqtnrwdrhbhkzh4jjyozd26a
Radiomics and artificial intelligence for biomarker and prediction model development in oncology
2019
Computational and Structural Biotechnology Journal
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A crude but consistent method of segmenting a dataset (e.g., by using an edge detection algorithm or using fixed threshold segmentation or growing a region from a user-defined seed) has to be weighed against ...
However, unlike wrapper methods which use the classification method as an external black box to rank features, here the variable selection is an inherent part of the learning algorithm itself [50] . ...
doi:10.1016/j.csbj.2019.07.001
pmid:31388413
pmcid:PMC6667772
fatcat:zj2uwgasqbew3nyxmbg7s3tbqa
Action recognition using global spatio-temporal features derived from sparse representations
2014
Computer Vision and Image Understanding
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In contrast to existing methods that use local spatio-temporal feature detectors along with descriptors (such as HOG, HOG3D, HOF, etc.), dictionary learning helps consider the saliency in a global setting ...
Recognizing actions is one of the important challenges in computer vision with respect to video data, with applications to surveillance, diagnostics of mental disorders, and video retrieval. ...
We propose to use a dictionary learning and sparse coding model for MDL, which we show affords a simple and efficient algorithm for estimating the self-similarity of video data. ...
doi:10.1016/j.cviu.2014.01.002
fatcat:byknkngbhneenjrnbd2kxgh7cy
Step by Step Towards Effective Human Activity Recognition: A Balance between Energy Consumption and Latency in Health and Wellbeing Applications
2019
Sensors
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Human activity recognition (HAR) is a classification process that is used for recognizing human motions. ...
It highlights various methods for the optimization of energy consumption and latency in each stage of HAR that has been used in literature and was analyzed in order to provide direction for the implementation ...
Acknowledgments: The authors would like to thank the anonymous reviewers for their valuable comments and suggestions, which significantly improved the quality of this paper. ...
doi:10.3390/s19235206
pmid:31783705
pmcid:PMC6928889
fatcat:wwdj276lrnhydkopycx7rlabya
Neural Decoding of EEG Signals with Machine Learning: A Systematic Review
2021
Brain Sciences
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Wavelet transform was found to be the most common feature extraction method used for all types of tasks. ...
To this end, several academic databases were searched to explore relevant studies from the year 2000 to the present. ...
Acknowledgments: The authors would like to thank Pamela K. Douglas for providing valuable comments and suggestions. ...
doi:10.3390/brainsci11111525
pmid:34827524
pmcid:PMC8615531
fatcat:4ia7yrcptvgqhla7ccozb46xia
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