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Selecting critical features for data classification based on machine learning methods

Rung-Ching Chen, Christine Dewi, Su-Wen Huang, Rezzy Eko Caraka
<span title="2020-07-23">2020</span> <i title="Springer Science and Business Media LLC"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/pkhnkszyprhb3orbf6g7tqmgiu" style="color: black;">Journal of Big Data</a> </i> &nbsp;
In this paper, we show how significant the features selection in Bank Marketing dataset, car evaluation dataset, and Human Activity Recognition using smartphones dataset.  ...  In this paper, we use three popular datasets with a higher number of variables (Bank Marketing, Car Evaluation Database, Human Activity Recognition Using Smartphones) to conduct the experiment.  ...  The important measure for each variable of Human Activity Recognition Using Smartphones Dataset using Recursive Features Elimination Fig. 12 12 The important measure for each variable of Human Activity  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1186/s40537-020-00327-4">doi:10.1186/s40537-020-00327-4</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/volleohr3zflpiqyrs6es5nuv4">fatcat:volleohr3zflpiqyrs6es5nuv4</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20200724190557/https://journalofbigdata.springeropen.com/track/pdf/10.1186/s40537-020-00327-4" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/11/44/114416dd846671dd046b46092867e7466a868d44.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1186/s40537-020-00327-4"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> springer.com </button> </a>

A Novel Wearable Sensor-Based Human Activity Recognition Approach Using Artificial Hydrocarbon Networks

Hiram Ponce, María Martínez-Villaseñor, Luis Miralles-Pechuán
<span title="2016-07-05">2016</span> <i title="MDPI AG"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/taedaf6aozg7vitz5dpgkojane" style="color: black;">Sensors</a> </i> &nbsp;
There are many examples of health systems improved by human activity recognition. Nevertheless, the human activity recognition classification process is not an easy task.  ...  In order to develop a successful activity recognition system, it is necessary to use stable and robust machine learning techniques capable of dealing with noisy data.  ...  a feature reduction over the feature set of the previous case, using the well-known recursive feature elimination (RFE) method [34, 35] .  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3390/s16071033">doi:10.3390/s16071033</a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pubmed/27399696">pmid:27399696</a> <a target="_blank" rel="external noopener" href="https://pubmed.ncbi.nlm.nih.gov/PMC4970082/">pmcid:PMC4970082</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/gqwz6vdhlbcjbhjrlmujntcjvm">fatcat:gqwz6vdhlbcjbhjrlmujntcjvm</a> </span>
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Identifying Gender from Images of Face

A. Gayathri
<span title="2021-06-30">2021</span> <i title="International Journal for Research in Applied Science and Engineering Technology (IJRASET)"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/hsp44774azcezeyiq4kuzpfh5a" style="color: black;">International Journal for Research in Applied Science and Engineering Technology</a> </i> &nbsp;
The gender classification algorithm uses machine learning technique (supervised learning). In this case the algorithm is trained on a set of male and female faces and then used to classify new data.  ...  by comparing selected facial features from a given image with faces within a database.  ...  In many fields such as face recognition, facial expression analysis, tracking and surveillance, human-computer interaction, biometric, gender recognition applications can be seen.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.22214/ijraset.2021.36030">doi:10.22214/ijraset.2021.36030</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/4qyrz5l7mvhyrfkxgxswphncou">fatcat:4qyrz5l7mvhyrfkxgxswphncou</a> </span>
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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
<span title="2019-09-09">2019</span> <i title="Springer Science and Business Media LLC"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/7vmvy44msfazpg7esvwjkcglla" style="color: black;">Human-Centric Computing and Information Sciences</a> </i> &nbsp;
To provide compact feature vector representation, we studied hybrid bio-inspired evolutionary search algorithm and correlation-based feature selection method and evaluate their impact on extracted feature  ...  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  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1186/s13673-019-0194-5">doi:10.1186/s13673-019-0194-5</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/oif3o7dfhzdwhcqeept7t5jypq">fatcat:oif3o7dfhzdwhcqeept7t5jypq</a> </span>
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A Review of the Recent Developments in Integrating Machine Learning Models with Sensor Devices in the Smart Buildings Sector with a View to Attaining Enhanced Sensing, Energy Efficiency, and Optimal Building Management

Dana-Mihaela Petroșanu, George Căruțașu, Nicoleta Luminița Căruțașu, Alexandru Pîrjan
<span title="2019-12-12">2019</span> <i title="MDPI AG"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/a2yvk5xhdnhpxjnk6yd33uudqq" style="color: black;">Energies</a> </i> &nbsp;
After processing the obtained papers, we finally obtained, on the basis of our devised methodology, a reliable, eloquent and representative pool of 146 papers scientific works that would be useful for  ...  buildings sector, improving life quality within smart homes, assessing the occupancy status information, detecting human behavior with a view to assisted living, maintaining environmental health, and  ...  In [148] , the authors developed an Activity Recognition (AR) model based on Deep Learning for two cases: one-layer Denoising Autoencoder (DAE) and two-layer Stacked Denoising Autoencoder (SDAE).  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3390/en12244745">doi:10.3390/en12244745</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/eix222pupjcmddolute2qh4wia">fatcat:eix222pupjcmddolute2qh4wia</a> </span>
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Audio-Visual Biometric Recognition and Presentation Attack Detection: A Comprehensive Survey [article]

Hareesh Mandalapu, Aravinda Reddy P N, Raghavendra Ramachandra, K Sreenivasa Rao, Pabitra Mitra, S R Mahadeva Prasanna, Christoph Busch
<span title="2021-01-24">2021</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
This paper made a comprehensive survey on existing state-of-the-art audio-visual recognition techniques, publicly available databases for benchmarking, and Presentation Attack Detection (PAD) algorithms  ...  Biometric recognition is a trending technology that uses unique characteristics data to identify or verify/authenticate security applications.  ...  LBPs features are used for face recognition using a semi-supervised discriminant analysis as an extension to linear discriminant analysis (LDA) [145] .  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/2101.09725v1">arXiv:2101.09725v1</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/huejyfaeojhzddlckqt5nfivlq">fatcat:huejyfaeojhzddlckqt5nfivlq</a> </span>
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Audio-Visual Biometric Recognition and Presentation Attack Detection: A Comprehensive Survey

Hareesh Mandalapu, Aravinda Reddy P N, Raghavendra Ramachandra, Krothapalli Sreenivasa Rao, Pabitra Mitra, S. R. Mahadeva Prasanna, Christoph Busch
<span title="">2021</span> <i title="Institute of Electrical and Electronics Engineers (IEEE)"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/q7qi7j4ckfac7ehf3mjbso4hne" style="color: black;">IEEE Access</a> </i> &nbsp;
This paper made a comprehensive survey on existing state-of-the-art audio-visual recognition techniques, publicly available databases for benchmarking, and Presentation Attack Detection (PAD) algorithms  ...  Biometric recognition is a trending technology that uses unique characteristics data to identify or verify/authenticate security applications.  ...  LBPs features are used for face recognition using a semi-supervised discriminant analysis as an extension to linear discriminant analysis (LDA) [145] .  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/access.2021.3063031">doi:10.1109/access.2021.3063031</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/q6emam55frhlzp53t7lxb4qz3e">fatcat:q6emam55frhlzp53t7lxb4qz3e</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20210717193119/https://ieeexplore.ieee.org/ielx7/6287639/9312710/09366483.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/49/cb/49cb5fd4eb4f2ce75ad07b4332cb30e603a38709.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/access.2021.3063031"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> ieee.com </button> </a>

Sensors of Smart Devices in the Internet of Everything (IoE) Era: Big Opportunities and Massive Doubts

Mohammad Masoud, Yousef Jaradat, Ahmad Manasrah, Ismael Jannoud
<span title="2019-05-15">2019</span> <i title="Hindawi Limited"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/zlknqk4ahbcsthbafxw55emm7a" style="color: black;">Journal of Sensors</a> </i> &nbsp;
In addition, different useful machine learning applications based on smartphones' sensors data are shown.  ...  Sensors are added to enhance the usability of these devices and improve the quality of experience through data collection and analysis.  ...  Principal component analysis (PCA) and recursive feature elimination (RFE) have been used for the feature reduction process.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1155/2019/6514520">doi:10.1155/2019/6514520</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/lxlva7xfbra7flwt6jby7dc5xy">fatcat:lxlva7xfbra7flwt6jby7dc5xy</a> </span>
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BigEAR: Inferring the Ambient and Emotional Correlates from Smartphone-Based Acoustic Big Data

Harishchandra Dubey, Matthias R. Mehl, Kunal Mankodiya
<span title="">2016</span> <i title="IEEE"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/x225ffdwnfaydpbhcmdzjaqo4a" style="color: black;">2016 IEEE First International Conference on Connected Health: Applications, Systems and Engineering Technologies (CHASE)</a> </i> &nbsp;
The BigEAR framework automates the audio analysis. We computed the accuracy of BigEAR with respect to the ground truth obtained from a human rater.  ...  The overarching goal of BigEAR is to identify moods of the wearer from various activities such as laughing, singing, crying, arguing, and sighing.  ...  The proposed approach relies on a semi-supervised version of Fisher linear discriminant analysis (FLD) and utilizes the sequential structure of speech signal.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/chase.2016.46">doi:10.1109/chase.2016.46</a> <a target="_blank" rel="external noopener" href="https://dblp.org/rec/conf/chase/DubeyMM16.html">dblp:conf/chase/DubeyMM16</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/5c2nc76vfba7xoutyt4zeud7ja">fatcat:5c2nc76vfba7xoutyt4zeud7ja</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20190428004246/https://digitalcommons.uri.edu/cgi/viewcontent.cgi?article=1072&amp;context=ele_facpubs" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/12/fa/12fac81910643a05b7c529fa0855a8550f24a26b.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/chase.2016.46"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> ieee.com </button> </a>

English Pronunciation Standards Based on Multimodal Acoustic Sensors

Lingyi Zhu, Guolong Shi
<span title="2021-09-16">2021</span> <i title="Hindawi Limited"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/zlknqk4ahbcsthbafxw55emm7a" style="color: black;">Journal of Sensors</a> </i> &nbsp;
The lip syllable frames are obtained by video frame splitting, the syllables are denoised, the key point information of the lips is obtained using a gradient enhancement-based regression tree algorithm  ...  To address the shortcomings of the current lip feature extraction algorithm which is too complicated and not enough characterization ability, a feature extraction scheme based on the lip opening and closing  ...  by decision trees and linear discriminant analysis.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1155/2021/3633896">doi:10.1155/2021/3633896</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/t3qr3uwghna7bnoethgrt7dyz4">fatcat:t3qr3uwghna7bnoethgrt7dyz4</a> </span>
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Result Oriented Based Face Recognition using Neural Network with Erosion and Dilation Technique

Ms Prachi
<span title="">2015</span> <i title="Auricle Technologies, Pvt., Ltd."> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/xzi23k3yufelpolr4dcpkbpjke" style="color: black;">International Journal on Recent and Innovation Trends in Computing and Communication</a> </i> &nbsp;
In This , we gives study on Face Recognition After Plastic Surgery (FRAPS )and after wearing the spec/glasses with careful analysis of the effects on face appearance and its challenges to face recognition  ...  With this Edge Detection also used genetic algorithm to optimize weight using artificial neural network (ANN)and save that ANN file to database .And use that ANN file to compare face recognition in future  ...  Computerized human face recognition has been an active research area for the last 20 years.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.17762/ijritcc2321-8169.150419">doi:10.17762/ijritcc2321-8169.150419</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/6feyyh52hbdyxczzpeiknuh4ta">fatcat:6feyyh52hbdyxczzpeiknuh4ta</a> </span>
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Human Activity Recognition for Production and Logistics—A Systematic Literature Review

Christopher Reining, Friedrich Niemann, Fernando Moya Rueda, Gernot A. Fink, Michael ten Hompel
<span title="2019-07-24">2019</span> <i title="MDPI AG"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/dmr4kpn2yreovpdxpdiqtjcrnu" style="color: black;">Information</a> </i> &nbsp;
This contribution provides a systematic literature review of Human Activity Recognition for Production and Logistics.  ...  This review is focused on applications that use marker-based Motion Capturing or Inertial Measurement Units.  ...  Kernel Discriminant Analysis (KDA) is a non-linear discriminating approach based on kernel techniques to find non-linear discriminating features, used in [29, 47, 47] .  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3390/info10080245">doi:10.3390/info10080245</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/aqseclsbg5cxxhis3ylguomvsu">fatcat:aqseclsbg5cxxhis3ylguomvsu</a> </span>
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From Data Acquisition to Data Fusion: A Comprehensive Review and a Roadmap for the Identification of Activities of Daily Living Using Mobile Devices

Ivan Pires, Nuno Garcia, Nuno Pombo, Francisco Flórez-Revuelta
<span title="2016-02-02">2016</span> <i title="MDPI AG"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/taedaf6aozg7vitz5dpgkojane" style="color: black;">Sensors</a> </i> &nbsp;
Sensor data fusion techniques are used to consolidate the data collected from several sensors, increasing the reliability of the algorithms for the identification of the different activities.  ...  The number and type of available sensors depend on the selected mobile platform, with variants imposed by the manufacturer, operating system and model.  ...  The authors would also like to acknowledge the contribution of the COST Action IC1303-AAPELE -Architectures, Algorithms and Protocols for Enhanced Living Environments.  ... 
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Robust human activity recognition using single accelerometer via wavelet energy spectrum features and ensemble feature selection

Yiming Tian, Jie Zhang, Jie Wang, Yanli Geng, Xitai Wang
<span title="2020-01-01">2020</span> <i title="Informa UK Limited"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/rnlwm3kn4rgthcfppt43f6ld5i" style="color: black;">Systems Science &amp; Control Engineering</a> </i> &nbsp;
Wearable sensor-based human activity recognition has been widely used in many fields.  ...  Experiment results show that the wavelet energy spectrum features can increase the discrimination between different activities and significantly and improve the activity recognition accuracy.  ...  Besides, the acceleration signal of human activity has the characteristics of non-linearity.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1080/21642583.2020.1723142">doi:10.1080/21642583.2020.1723142</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/5dpqn5lx2jdovjqzkuhbh7wqki">fatcat:5dpqn5lx2jdovjqzkuhbh7wqki</a> </span>
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A Comprehensive Survey on ECG signals as New Biometric Modality for Human Authentication: Recent Advances and Future Challenges

Anthony Ngozichukwuka Uwaechia, Dzati Athiar Ramli
<span title="">2021</span> <i title="Institute of Electrical and Electronics Engineers (IEEE)"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/q7qi7j4ckfac7ehf3mjbso4hne" style="color: black;">IEEE Access</a> </i> &nbsp;
selection, backward feature elimination, recursive feature elimination.  ...  In [359] , a kNN linear SVM and neural network were used as the classifier model for ECG-based human recognition on MIT-BIH and ECG-ID database.  ... 
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