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Self-Training Classification Framework with Spatial-Contextual Information for Local Climate Zones
2019
Remote Sensing
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LCZ mapping based on the remote sensing classification method is a fundamental task, and the protocol proposed by the World Urban Database and Access Portal Tools (WUDAPT) project, which consists of random ...
Moreover, in the unary potentials of CRF modeling, pseudo-label selection using a self-training process is used to train the classifier, which fuses the regional spatial information through segmentation ...
Acknowledgments: The authors are particularly grateful to the 2017 Data Fusion Contest for providing the datasets.
Conflicts of Interest: The authors declare no conflict of interest. ...
doi:10.3390/rs11232828
fatcat:hp2dte2q6ngrlo5x3cioomdqoy
A Design of Peak to Average Power Ratio Based SWIPT System in 180 nm CMOS Process for IoT Sensor Applications
2022
IEEE Access
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A digital controller was designed to control the demodulation of the PAPR based modulated signal and retrieve the digital information. ...
An adaptive power splitter (APS) smartly regulates the distribution of received radio frequency (RF) signals between the energy harvesting (EH) path and the information decoding (ID) path. ...
Based on received PAPR values of RF signal, data bit stream is recovered. Fig. 14 shows the structure of the frame in the PAPR modulated signal. ...
doi:10.1109/access.2022.3168779
fatcat:kwxfgyre3zcjbppfcggx7avjc4
An Efficient Brain Tumor Classification Based on SOBS Method for MRI Brain Images
2019
International Journal of Engineering and Advanced Technology
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The proposed segmentation method is named as Self Organisation Based Segmentation (SOBS) method. It is compared with some of the deformable models in literature. ...
From the investigational outcomes, the classification accuracy was found to be very high using the proposed segmentation method SOBS with the Random Forest (RF) Classifier. ...
Abdelsamea et al. provided a survey of SOM based Active Contour Models for image segmentation in which to facilitate improving the healthiness of edge based ACMs to the blur and ill defined edge information ...
doi:10.35940/ijeat.a9379.109119
fatcat:lgvxizd7fvh7naurmspp225fem
Categorization based Relevance Feedback Search Engine for Earth Observation Images Repositories
2006
2006 IEEE International Symposium on Geoscience and Remote Sensing
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Presently Earth Observation (EO) satellites acquire huge volumes of high resolution images very much over-passing the capacity of the users to access the information content of the acquired data. ...
This article presents a categorisation based Relevance Feedback (RF) search engine for EO images repositories The developed method is presented as well results obtained for a SPOT5 satellite image database ...
ACKNOWLEDGMENT The work was performed within The CNES/DLR/ENST Competence Centre on Information Extraction and Image Understanding for Earth Observation SPOT5 images have been provided by "Centre National ...
doi:10.1109/igarss.2006.8
dblp:conf/igarss/CostacheMD06
fatcat:34mkoimgiffb7prstfk3egaaqq
Statistical representation models for mutation information within genomic data
2019
BMC Bioinformatics
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The highest accuracy (76.44%) and f-score (76.95%) are achieved with the BM25-tf-rf based data representation. ...
Inspired from the field of information retrieval, we propose using the term frequency (tf) and BM25 term weighting measures with the inverse document frequency (idf) and relevance frequency (rf) measures ...
We would also like to thank Hamdi Erkut, an MS student in our department, for downloading the selected files from TCGA system [26] and Rıza Özçelik, an MS student in our department, for annotating the ...
doi:10.1186/s12859-019-2868-4
fatcat:hj6lavzgizbz3llaoqz64kkaiq
Sweet spot matching: A thin-layer chromatography-based countercurrent solvent system selection strategy
2017
Journal of Chromatography A
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Defining a range of practically matching Rf values that are useful to predict the sweet spot K values, becomes the key in any TLC-based SS selection strategy. ...
Out of 62 correlations, 45 resulted in matched Rf and K values. Based on this study, practical guidelines for the TLC-based prediction strategy are provided. ...
bioautography through grant R21 AI093919, all from the National Institutes of Health. ...
doi:10.1016/j.chroma.2017.04.055
pmid:28506498
pmcid:PMC5511999
fatcat:zs6xlfm7krfhtg7soizz2npo44
Classification of Control and Neurodegenerative Disease Subjects Using Tree Based Classifiers
2020
Journal of Pharmaceutical Research International
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It is concluded that selected features encode adequate information about neural control of the gait. ...
Three tree based machine learning algorithms (RF, J48 and REPTree) were used to classify the control and NDD subjects. ...
MAE is an indication of
the average deviation of the predicted values
from the corresponding observed values. MAE
present information on long term performance of
the models. ...
doi:10.9734/jpri/2020/v32i1130546
fatcat:fvfiyn2oo5cr5op46juocitlfa
An Efficient Downscaling Scheme for High-Resolution Precipitation Estimates over a High Mountainous Watershed
2021
Remote Sensing
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The results indicated that the RF model showed little improvement in the accuracy of IMERG-based precipitation downscaling. Including residual modification could improve the results of the RF model. ...
The application of more rain gauges improves the performance of the combined RF and residual modification methods, with the MAE and RMSE values reduced by 8% and 9%, respectively. ...
Informed Consent Statement: Not applicable. Data Availability Statement: The data are not publicly available due to the confidentiality of the research projects. ...
doi:10.3390/rs13020234
fatcat:xkbosnre55gprf3qx7rzcowniq
Prediction of DNA-binding residues from protein sequence information using random forests
2009
BMC Genomics
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Conclusion: The results suggest that the RF-based approach gives rise to more accurate prediction of DNA-binding residues than previous studies. ...
The use of evolutionary information was found to significantly improve classifier performance. ...
The full contents of the supplement are available online at http://www.biomedcentral.com/1471-2164/ 10?issue=S1. ...
doi:10.1186/1471-2164-10-s1-s1
pmid:19594868
pmcid:PMC2709252
fatcat:6j6tdw7otnemjffmtkvn6w4h2u
Assessing the information content of structural and protein–ligand interaction representations for the classification of kinase inhibitor binding modes via machine learning and active learning
2020
Journal of Cheminformatics
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An active learning strategy applying information entropy-based selection of training instances was applied as a diagnostic approach to assess the relative information content of distinct representations ...
By contrast, for atom environment fingerprints, the derivation of accurate models via active learning depended on entropy-based selection of informative training compounds. ...
Acknowledgements The authors thank the OpenEye Scientific Software, Inc., for providing a free academic license of the OpenEye toolkit and Dr. Martin Vogt for helpful discussions. ...
doi:10.1186/s13321-020-00434-7
pmid:33431025
fatcat:7urlhfacxnbtfooa4x5jzxihrq
Handling Missing Phenotype Data With Random Forests For Diabetes Risk Prognosis
2016
Zenodo
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However, the datasets use to have a lot of missing information. ...
Machine learning techniques are the cornerstone to handle the amounts of information available for building comprehensive models for decision support in medical practice. ...
Acknowledgment This project has received funding from the grant of the University of Girona 2016-2018 (MPCUdG2016) and the European Unions Hori- ...
doi:10.5281/zenodo.427979
fatcat:zvhlqhbdrnbv5arwhve775thuu
Assessing the information content of structural and protein-ligand interaction representations for the classification of kinase inhibitor binding modes via machine learning and active learning
2020
Zenodo
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
An active learning strategy applying information entropy-based selection of training instances was applied as a diagnostic approach to assess the relative information content of distinct representations ...
By contrast, for atom environment fingerprints, the derivation of accurate models via active learning depended on entropy-based selection of informative training compounds. ...
Acknowledgements The authors thank the OpenEye Scientific Software, Inc., for providing a free academic license of the OpenEye toolkit and Dr. Martin Vogt for helpful discussions. ...
doi:10.5281/zenodo.3759400
fatcat:wsuqcgc2yret3jehsuc3cfb3iu
Overestimation of serum levels of rheumatoid factor caused by the presence of an incorrect calibrator in the Dade Behring kit
2007
Modern Rheumatology
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All of the past samples from one RF-negative RA patient were also judged as RF-negative based on the Because our fi ndings suggested that RF levels had become abnormally high at around May of 2003, we ...
According to the notifi cation, DB had re-evaluated the traceability of RF on the basis of ISO/EN17511 (quantifi cation of biological samples -traceability for the indicated values of standard preparations ...
doi:10.3109/s10165-007-0623-6
pmid:17929143
fatcat:xldo7zmbavhirjeivtzcsqjjlq
Performance and efficiency of machine learning algorithms for analyzing rectangular biomedical data
[article]
2020
bioRxiv
pre-print
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Based on the information entropy and information gain of feature values, we optimized dimension reduction (i.e. reduce the number of features in models). ...
Dimension reduction based on information gain will significantly increase efficiency while maintaining classification accuracy of the models. ...
After tuning the models, we set the nTrees parameter to 500 in RF-based analyses with the best Mtry node value of 7 (Supplementary Table 2 ). ...
doi:10.1101/2020.09.13.295592
fatcat:okuckeiigrgatc25krtvro3xky
Use of relevancy and complementary information for discriminatory gene selection from high-dimensional gene expression data
2021
PLoS ONE
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Addressing these issues, we proposed Mutual information based Gene Selection method (MGS) for selecting informative genes. ...
For identifying the key genes from gene expression data, among the existing literature, mutual information (MI) is one of the most successful criteria. ...
It is because of the selection of informative genes based on the RF classifier. ...
doi:10.1371/journal.pone.0230164
pmid:34613963
pmcid:PMC8494339
fatcat:y5dgxwjuaffdvftopoc6cwjzxe
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