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Feature Extraction and Sun Intersecting Pixels Selection
integration_instructionsResearch softwarekeyboard_double_arrow_right Software 2022Publisher:ZenodoFunded by:NSF | RII Track-1: The New Mexi...
NSF| RII Track-1: The New Mexico SMART Grid Center: Sustainable, Modular, Adaptive, Resilient, and Transactive
Authors: Terrén-Serrano, Guillermo; Martínez-Ramón, Manel;
Terrén-Serrano, Guillermo; Martínez-Ramón, Manel;
doi: 10.5281/zenodo.7011341 , 10.5281/zenodo.7008501
doi: 10.5281/zenodo.7011341 , 10.5281/zenodo.7008501
This repository contains the software necessary for extracting the features and selecting the Sun intersecting cloudy pixels using the functions contained in files posted in other repositories. See preprint article: https://arxiv.org/pdf/2110.05622.pdf See preprint article: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4064631 See realated data: https://doi.org/10.5061/dryad.zcrjdfn9m Additional funding was provided by the King Felipe VI Endowed Chair of the University of New Mexico.
ZENODOarrow_drop_down
ZENODO
Software . 2022
License: http://www.apache.org/licenses/LICENSE-2.0
Data sources: Datacite
ZENODO
Software . 2022
License: http://www.apache.org/licenses/LICENSE-2.0
Data sources: ZENODO
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ZENODO
Software . 2022
License: http://www.apache.org/licenses/LICENSE-2.0
Data sources: Datacite
ZENODO
Software . 2022
License: http://www.apache.org/licenses/LICENSE-2.0
Data sources: ZENODO
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Multi-Task Deep Learning for Intra-Hour Solar Forecasting
integration_instructionsResearch softwarekeyboard_double_arrow_right Software 2022Publisher:ZenodoFunded by:NSF | RII Track-1: The New Mexi...
NSF| RII Track-1: The New Mexico SMART Grid Center: Sustainable, Modular, Adaptive, Resilient, and Transactive
Authors: Terrén-Serrano, Guillermo; Martínez-Ramón, Manel;
Terrén-Serrano, Guillermo; Martínez-Ramón, Manel;
doi: 10.5281/zenodo.7008498 , 10.5281/zenodo.7008347 , 10.5281/zenodo.7008346
doi: 10.5281/zenodo.7008498 , 10.5281/zenodo.7008347 , 10.5281/zenodo.7008346
This repository contains the files implemented for the different experiments carried out to develop an optimal Deep Learning (DL) intra-hour solar forecasting using infrared ground-based images. The model is based on deep recurrent networks architectures. The state-of-the-art is implemented in solarnet.py and sunset.py for comparission purposes. See journal preprint: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4064631 See realated data: https://doi.org/10.5061/dryad.zcrjdfn9m
ZENODOarrow_drop_down
ZENODO
Software . 2022
License: http://www.apache.org/licenses/LICENSE-2.0
Data sources: Datacite
ZENODO
Software . 2022
License: http://www.apache.org/licenses/LICENSE-2.0
Data sources: ZENODO
ZENODO
Software . 2022
License: http://www.apache.org/licenses/LICENSE-2.0
Data sources: ZENODO
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ZENODOarrow_drop_down
ZENODO
Software . 2022
License: http://www.apache.org/licenses/LICENSE-2.0
Data sources: Datacite
ZENODO
Software . 2022
License: http://www.apache.org/licenses/LICENSE-2.0
Data sources: ZENODO
ZENODO
Software . 2022
License: http://www.apache.org/licenses/LICENSE-2.0
Data sources: ZENODO
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Feature Extractiond and Selection of the Sun Intersecting Pixels
integration_instructionsResearch softwarekeyboard_double_arrow_right Software 2022Publisher:ZenodoFunded by:NSF | RII Track-1: The New Mexi...
NSF| RII Track-1: The New Mexico SMART Grid Center: Sustainable, Modular, Adaptive, Resilient, and Transactive
Authors: Guillermo Terrén-Serrano; Manel Martínez-Ramón;
Guillermo Terrén-Serrano; Manel Martínez-Ramón;
doi: 10.5281/zenodo.7008502
doi: 10.5281/zenodo.7008502
This repository contains the software necessary for extracting the features and selecting the Sun intersecting cloudy pixels using the functions contained in files posted in other repositories. See preprint article: https://arxiv.org/pdf/2110.05622.pdf See preprint article: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4064631 See realated data: https://doi.org/10.5061/dryad.zcrjdfn9m Additional funding was provided by the King Felipe VI Endowed Chair of the University of New Mexico.
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ZENODO
Software . 2022
License: http://www.apache.org/licenses/LICENSE-2.0
Data sources: ZENODO
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ZENODO
Software . 2022
License: http://www.apache.org/licenses/LICENSE-2.0
Data sources: ZENODO
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COVID-19 SignSym
integration_instructionsResearch softwarekeyboard_double_arrow_right Software 2021Publisher:bio.toolsFunded by:NIH | CLAMP-CS: a Cloud-based, ..., NIH | Frontiers: University of ...
NIH| CLAMP-CS: a Cloud-based, Service-oriented, high-performance Natural Language Processing Platform for Healthcare ,
NIH| Frontiers: University of Kansas Clinical and Translational Science Institute
Authors: Rouhizadeh, Masoud; Zhang, Yaoyun;
Rouhizadeh, Masoud; Zhang, Yaoyun;
COVID-19 SignSyma is a tool foor fast adaptation of a general clinical NLP tool to identify and normalize COVID-19 signs and symptoms to OMOP common data model.
bio.toolsarrow_drop_down
bio.tools
Software . 2021
Data sources: bio.tools
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bio.tools
Software . 2021
Data sources: bio.tools
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CoronaCentral
integration_instructionsResearch softwarekeyboard_double_arrow_right Software 2021Publisher:bio.toolsFunded by:NIH | Text Mining for High-fide...
NIH| Text Mining for High-fidelity Curation and Discovery of Gene-drug-phenotype Relationships
Authors: Lever, Jake;
Lever, Jake;
CoronaCentral is a tool for analyzing the vast coronavirus literature with CoronaCentral.
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bio.tools
Software . 2021
License: MIT
Data sources: bio.tools
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bio.tools
Software . 2021
License: MIT
Data sources: bio.tools
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COVID-19-CT-CXR
integration_instructionsResearch softwarekeyboard_double_arrow_right Software 2021 Python Publisher:bio.toolsFunded by:NIH | A framework to enhance ra..., NIH | A framework to enhance ra...
NIH| A framework to enhance radiology structured report by invoking NLP and DL: Models and Applications ,
NIH| A framework to enhance radiology structured report by invoking NLP and DL: Models and Applications
Authors: Lu, Zhiyong;
Lu, Zhiyong;
COVID-19-CT-CXR is a public database of COVID-19 CXR and CT images, which are automatically extracted from COVID-19-relevant articles from the PubMed Central Open Access (PMC-OA) Subset.
bio.toolsarrow_drop_down
bio.tools
Software . 2021
License: Freeware
Data sources: bio.tools
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bio.tools
Software . 2021
License: Freeware
Data sources: bio.tools
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Doc2Hpo
integration_instructionsResearch softwarekeyboard_double_arrow_right Software 2019 JavaScript Publisher:bio.toolsFunded by:NIH | Deep phenotyping in Elect...
NIH| Deep phenotyping in Electronic Health Records for Genomic Medicine
Authors: Wang, Kai; Weng, Chunhua;
Wang, Kai; Weng, Chunhua;
Web application for efficient and accurate Human Phenotype Ontology (HPO) concept curation.
bio.toolsarrow_drop_down
bio.tools
Software . 2019
License: Unlicense
Data sources: bio.tools
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bio.tools
Software . 2019
License: Unlicense
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INDRA-IPM
integration_instructionsResearch softwarekeyboard_double_arrow_right Software 2019 JavaScript Publisher:bio.toolsFunded by:NIH | The HMS Laboratory of Sys...
NIH| The HMS Laboratory of Systems Pharmacology
Authors: Sorger, Peter;
Sorger, Peter;
Interactive pathway modeling using natural language with automated assembly.
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bio.tools
Software . 2019
License: BSD-2-Clause
Data sources: bio.tools
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bio.tools
Software . 2019
License: BSD-2-Clause
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ODAE
integration_instructionsResearch softwarekeyboard_double_arrow_right Software 2019Publisher:bio.toolsFunded by:NIH | Ontology-based Informatio...
NIH| Ontology-based Information Network to Support Vaccine Research
Authors: He, Oliver;
He, Oliver;
Ontology-based systematic representation and analysis of drug adverse events and its usage in study of adverse events given different patient age and disease conditions.
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bio.tools
Software . 2019
License: Unlicense
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Software . 2019
License: Unlicense
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BiocPkgTools
integration_instructionsResearch softwarekeyboard_double_arrow_right Software 2019 R Publisher:bio.toolsFunded by:NIH | Cancer Genomics: Integrat..., EC | SOUND, NIH | Accelerating Cancer Genom... +3 projects
NIH| Cancer Genomics: Integrative and Scalable Solutions in R/Bioconductor ,
EC| SOUND ,
NIH| Accelerating Cancer Genomics with Cloud-scale Bioconductor ,
NIH| Bioconductor: An Open Computing Resource for Genomics ,
NIH| ADDRESSING THE ISSUE OF GAP REGIONS IN GENOME SEQUENCING ,
NIH| Cancer Genomics: Integrative and Salable Solutions in R/Bioconductor
Authors: Davis, Sean;
Davis, Sean;
Package that facilitates access to extensive metadata in computable form covering the Bioconductor package ecosystem, facilitating downstream applications such as custom reporting, data and text mining of Bioconductor package text descriptions, graph analytics over package dependencies, and custom search approaches.
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bio.tools
Software . 2019
License: MIT
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Software . 2019
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The following results are related to Digital Humanities and Cultural Heritage. Are you interested to view more results? Visit OpenAIRE - Explore.

Feature Extraction and Sun Intersecting Pixels Selection
integration_instructionsResearch softwarekeyboard_double_arrow_right Software 2022Publisher:ZenodoFunded by:NSF | RII Track-1: The New Mexi...
NSF| RII Track-1: The New Mexico SMART Grid Center: Sustainable, Modular, Adaptive, Resilient, and Transactive
Authors: Terrén-Serrano, Guillermo; Martínez-Ramón, Manel;
Terrén-Serrano, Guillermo; Martínez-Ramón, Manel;
doi: 10.5281/zenodo.7011341 , 10.5281/zenodo.7008501
doi: 10.5281/zenodo.7011341 , 10.5281/zenodo.7008501
This repository contains the software necessary for extracting the features and selecting the Sun intersecting cloudy pixels using the functions contained in files posted in other repositories. See preprint article: https://arxiv.org/pdf/2110.05622.pdf See preprint article: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4064631 See realated data: https://doi.org/10.5061/dryad.zcrjdfn9m Additional funding was provided by the King Felipe VI Endowed Chair of the University of New Mexico.
ZENODOarrow_drop_down
ZENODO
Software . 2022
License: http://www.apache.org/licenses/LICENSE-2.0
Data sources: Datacite
ZENODO
Software . 2022
License: http://www.apache.org/licenses/LICENSE-2.0
Data sources: ZENODO
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ZENODOarrow_drop_down
ZENODO
Software . 2022
License: http://www.apache.org/licenses/LICENSE-2.0
Data sources: Datacite
ZENODO
Software . 2022
License: http://www.apache.org/licenses/LICENSE-2.0
Data sources: ZENODO
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Multi-Task Deep Learning for Intra-Hour Solar Forecasting
integration_instructionsResearch softwarekeyboard_double_arrow_right Software 2022Publisher:ZenodoFunded by:NSF | RII Track-1: The New Mexi...
NSF| RII Track-1: The New Mexico SMART Grid Center: Sustainable, Modular, Adaptive, Resilient, and Transactive
Authors: Terrén-Serrano, Guillermo; Martínez-Ramón, Manel;
Terrén-Serrano, Guillermo; Martínez-Ramón, Manel;
doi: 10.5281/zenodo.7008498 , 10.5281/zenodo.7008347 , 10.5281/zenodo.7008346
doi: 10.5281/zenodo.7008498 , 10.5281/zenodo.7008347 , 10.5281/zenodo.7008346
This repository contains the files implemented for the different experiments carried out to develop an optimal Deep Learning (DL) intra-hour solar forecasting using infrared ground-based images. The model is based on deep recurrent networks architectures. The state-of-the-art is implemented in solarnet.py and sunset.py for comparission purposes. See journal preprint: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4064631 See realated data: https://doi.org/10.5061/dryad.zcrjdfn9m
ZENODOarrow_drop_down
ZENODO
Software . 2022
License: http://www.apache.org/licenses/LICENSE-2.0
Data sources: Datacite
ZENODO
Software . 2022
License: http://www.apache.org/licenses/LICENSE-2.0
Data sources: ZENODO
ZENODO
Software . 2022
License: http://www.apache.org/licenses/LICENSE-2.0
Data sources: ZENODO
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ZENODO
Software . 2022
License: http://www.apache.org/licenses/LICENSE-2.0
Data sources: Datacite
ZENODO
Software . 2022
License: http://www.apache.org/licenses/LICENSE-2.0
Data sources: ZENODO
ZENODO
Software . 2022
License: http://www.apache.org/licenses/LICENSE-2.0
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Feature Extractiond and Selection of the Sun Intersecting Pixels
integration_instructionsResearch softwarekeyboard_double_arrow_right Software 2022Publisher:ZenodoFunded by:NSF | RII Track-1: The New Mexi...
NSF| RII Track-1: The New Mexico SMART Grid Center: Sustainable, Modular, Adaptive, Resilient, and Transactive
Authors: Guillermo Terrén-Serrano; Manel Martínez-Ramón;
Guillermo Terrén-Serrano; Manel Martínez-Ramón;
doi: 10.5281/zenodo.7008502
doi: 10.5281/zenodo.7008502
This repository contains the software necessary for extracting the features and selecting the Sun intersecting cloudy pixels using the functions contained in files posted in other repositories. See preprint article: https://arxiv.org/pdf/2110.05622.pdf See preprint article: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4064631 See realated data: https://doi.org/10.5061/dryad.zcrjdfn9m Additional funding was provided by the King Felipe VI Endowed Chair of the University of New Mexico.
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integration_instructionsResearch softwarekeyboard_double_arrow_right Software 2021Publisher:bio.toolsFunded by:NIH | CLAMP-CS: a Cloud-based, ..., NIH | Frontiers: University of ...
NIH| CLAMP-CS: a Cloud-based, Service-oriented, high-performance Natural Language Processing Platform for Healthcare ,
NIH| Frontiers: University of Kansas Clinical and Translational Science Institute
Authors: Rouhizadeh, Masoud; Zhang, Yaoyun;
Rouhizadeh, Masoud; Zhang, Yaoyun;
COVID-19 SignSyma is a tool foor fast adaptation of a general clinical NLP tool to identify and normalize COVID-19 signs and symptoms to OMOP common data model.
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CoronaCentral is a tool for analyzing the vast coronavirus literature with CoronaCentral.
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integration_instructionsResearch softwarekeyboard_double_arrow_right Software 2021 Python Publisher:bio.toolsFunded by:NIH | A framework to enhance ra..., NIH | A framework to enhance ra...
NIH| A framework to enhance radiology structured report by invoking NLP and DL: Models and Applications ,
NIH| A framework to enhance radiology structured report by invoking NLP and DL: Models and Applications
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Lu, Zhiyong;
COVID-19-CT-CXR is a public database of COVID-19 CXR and CT images, which are automatically extracted from COVID-19-relevant articles from the PubMed Central Open Access (PMC-OA) Subset.
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integration_instructionsResearch softwarekeyboard_double_arrow_right Software 2019 JavaScript Publisher:bio.toolsFunded by:NIH | Deep phenotyping in Elect...
NIH| Deep phenotyping in Electronic Health Records for Genomic Medicine
Authors: Wang, Kai; Weng, Chunhua;
Wang, Kai; Weng, Chunhua;
Web application for efficient and accurate Human Phenotype Ontology (HPO) concept curation.
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NIH| The HMS Laboratory of Systems Pharmacology
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Interactive pathway modeling using natural language with automated assembly.
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NIH| Ontology-based Information Network to Support Vaccine Research
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Ontology-based systematic representation and analysis of drug adverse events and its usage in study of adverse events given different patient age and disease conditions.
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NIH| Cancer Genomics: Integrative and Scalable Solutions in R/Bioconductor ,
EC| SOUND ,
NIH| Accelerating Cancer Genomics with Cloud-scale Bioconductor ,
NIH| Bioconductor: An Open Computing Resource for Genomics ,
NIH| ADDRESSING THE ISSUE OF GAP REGIONS IN GENOME SEQUENCING ,
NIH| Cancer Genomics: Integrative and Salable Solutions in R/Bioconductor
Authors: Davis, Sean;
Davis, Sean;
Package that facilitates access to extensive metadata in computable form covering the Bioconductor package ecosystem, facilitating downstream applications such as custom reporting, data and text mining of Bioconductor package text descriptions, graph analytics over package dependencies, and custom search approaches.
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