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Hill-climber based fuzzy-rough feature extraction with an application to cancer classification

Sujata Dash
2013 13th International Conference on Hybrid Intelligent Systems (HIS 2013)  
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

Hongbo Li, Gang Zheng, Kangjian Sun, Zichao Jiang, Yao Li, Heming Jia
2020 IEEE Access  
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

Walaa Ali H. Jumiawi, Ali El-Zaart
2022 Journal of Imaging  
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

Henry Friday Nweke, Ying Wah Teh, Ghulam Mujtaba, Uzoma Rita Alo, Mohammed Ali Al-garadi
2019 Human-Centric Computing and Information Sciences  
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

Turky Alotaiby, Fathi E Abd El-Samie, Saleh A Alshebeili, Ishtiaq Ahmad
2015 EURASIP Journal on Advances in Signal Processing  
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]

Paraskevas Chatzithanos, Grigoris Nikolaou, Rustam Stolkin, Manolis Chiou
2021 arXiv   pre-print
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

Deng Wang, Duoqian Miao, Chen Xie
2011 Expert systems with applications  
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

Vidhya V, U. Raghavendra, Anjan Gudigar, Praneet Kasula, Yashas Chakole, Ajay Hegde, Girish Menon R, Chui Ping Ooi, Edward J. Ciaccio, U. Rajendra Acharya
2022 Informatics  
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


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]

Yuanfei Wang, Fangwei Zhong, Jing Xu, Yizhou Wang
2022 arXiv   pre-print
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

Cai, Chen, Yin
2019 Symmetry  
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

Reza Forghani, Peter Savadjiev, Avishek Chatterjee, Nikesh Muthukrishnan, Caroline Reinhold, Behzad Forghani
2019 Computational and Structural Biotechnology Journal  
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

Guruprasad Somasundaram, Anoop Cherian, Vassilios Morellas, Nikolaos Papanikolopoulos
2014 Computer Vision and Image Understanding  
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

Enida Cero Dinarević, Jasmina Baraković Husić, Sabina Baraković
2019 Sensors  
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

Maham Saeidi, Waldemar Karwowski, Farzad V. Farahani, Krzysztof Fiok, Redha Taiar, P. A. Hancock, Awad Al-Juaid
2021 Brain Sciences  
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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