cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.8dsxt4
title: Occurrence Download

description: A dataset containing 831 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Mexico",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Storeria storerioides (Cope, 1866)"
 ]
}

 The dataset includes 831 records from 35 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0005541-230828120925497/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.25549/independent-c69-27315
title: General counsel pleadings, vol. 1 (3 of 6), 1991 Apr. 30 - June 10

description: Transcripts form the court case "The people of the state of California vs. Laurence M Powell, Timother E Wind, Theodore J Briseno and Stacey C Koon - vol 12. PART OF A SERIES: The series pertains to the work of Munger, Tolles & Olson, the firm responsible for coordinating the activities and proceedings of the Independent Commission's legal counsel. Included are legal briefs, court transcripts, and memoranda; press releases and article clippings about the Rodney King incident and the subsequent creation of the Independent Commission; summaries of witness interviews; analyses of legislation regarding the role and purview of peace officers; work plans and outlines developed by Commission staff; draft copies developed for all sections of the Commission report; supplemental materials for the report, including a copy of the Rodney King arrest log, law enforcement literature, and public opinion surveys; materials distributed and reviewed during Commission meetings; letters of interest submitted to Chairman Christopher from prospective Commission members and organizations; and lists of bills and Commission expenditures.
DOI: 10.15468/dl.c9dnw3
title: Occurrence Download

description: A dataset containing 97 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((62.62 -26.97,62.62 33.97,184.38 33.97,184.38 -26.97,62.62 -26.97))",
 "HasCoordinate is true",
 "TaxonKey is Dysoxylum excelsum Blume",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 97 records from 8 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002889-170826194755519/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.25549/independent-c69-27517
title: General counsel pleadings, vol. 1 (4 of 6), 1991 Apr. 30 - June 10

description: Transcripts form the court case "The people of the state of California vs. Laurence M Powell, Timother E Wind, Theodore J Briseno and Stacey C Koon - vol 12. PART OF A SERIES: The series pertains to the work of Munger, Tolles & Olson, the firm responsible for coordinating the activities and proceedings of the Independent Commission's legal counsel. Included are legal briefs, court transcripts, and memoranda; press releases and article clippings about the Rodney King incident and the subsequent creation of the Independent Commission; summaries of witness interviews; analyses of legislation regarding the role and purview of peace officers; work plans and outlines developed by Commission staff; draft copies developed for all sections of the Commission report; supplemental materials for the report, including a copy of the Rodney King arrest log, law enforcement literature, and public opinion surveys; materials distributed and reviewed during Commission meetings; letters of interest submitted to Chairman Christopher from prospective Commission members and organizations; and lists of bills and Commission expenditures.
DOI: 10.15468/dl.2jsrcn
title: Occurrence Download

description: A dataset containing 40803 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Pedicularis palustris L.",
 "HasCoordinate is true",
 "Continent is Europe",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 2000",
 "CoordinateUncertaintyInMeters is less than 10000"
 ]
}

 The dataset includes 40803 records from 206 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0027668-240216155721649/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.s2nqty
title: Occurrence Download

description: A dataset containing 1030565 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is one of (Observation, Machine Observation, Human Observation, Occurrence evidence)",
 "OccurrenceStatus is Present",
 "TaxonKey is Testudines"
 ]
}

 The dataset includes 1030565 records from 1942 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0054940-231002084531237/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.6084/m9.figshare.28216061
title: Daily runoff and baseflow

description: Daily hydrological data from 3 small forested catchment.
DOI: 10.6084/m9.figshare.28216061.v1
title: Daily runoff and baseflow

description: Daily hydrological data from 3 small forested catchment.
DOI: 10.5281/zenodo.10794702
title: ToneTwist AFx Dataset: Flamma Analog Comp

description:  

Settings




Volume
Comp
Eq


10
1
5


10
5
1


10
5
5


10
5
10


10
10
5




Dry with markers

Dry inputs are a selection of clean guitar and bass recordings from different sources:



IDMT-SMT-GUITAR - dataset 2 (7:23 min)

IDMT-SMT-GUITAR - dataset 4 - Career SG (6:08 min)

IDMT-SMT-GUITAR - dataset 4 - Ibanez 2820 (5:14 min)

IDMT-SMT-Bass-Single-Track - (5:58 min)

NAM: Neural Amp Modeler - (3:11 min)

Private Guitar Data - (5:19 min)

YouTube Bass Recordings - (10:09 min)


Pre-processing:



All:



synchronization markers (2 impulses) added at start and end of every file



IDMT-SMT-GUITAR - dataset 2:



peak normalized to -6dBFS



NAM:



no pre-processing



Others:



peak normalized to -0.1dBFS

signal multiplied by random number every 5 seconds (uniform distribution [0.1, 1.0] = [-20dB, 0dB])






Authors

Marco Comunità - Centre for Digital Music, Queen Mary University of London

Github

https://github.com/mcomunita/tonetwist-afx-dataset

Reference

If you make use of AUDIO-EFFECTS-DATASET, please cite the following publication:

@misc{comunità2025nablafxframeworkdifferentiableblackbox,
      title={NablAFx: A Framework for Differentiable Black-box and Gray-box Modeling of Audio Effects}, 
      author={Marco Comunità and Christian J. Steinmetz and Joshua D. Reiss},
      year={2025},
      eprint={2502.11668},
      archivePrefix={arXiv},
      primaryClass={cs.SD},
      url={https://arxiv.org/abs/2502.11668}, 
}
DOI: 10.5281/zenodo.10794703
title: ToneTwist AFx Dataset: Flamma Analog Comp

description:  

Settings




Volume
Comp
Eq


10
1
5


10
5
1


10
5
5


10
5
10


10
10
5




Dry with markers

Dry inputs are a selection of clean guitar and bass recordings from different sources:



IDMT-SMT-GUITAR - dataset 2 (7:23 min)

IDMT-SMT-GUITAR - dataset 4 - Career SG (6:08 min)

IDMT-SMT-GUITAR - dataset 4 - Ibanez 2820 (5:14 min)

IDMT-SMT-Bass-Single-Track - (5:58 min)

NAM: Neural Amp Modeler - (3:11 min)

Private Guitar Data - (5:19 min)

YouTube Bass Recordings - (10:09 min)


Pre-processing:



All:



synchronization markers (2 impulses) added at start and end of every file



IDMT-SMT-GUITAR - dataset 2:



peak normalized to -6dBFS



NAM:



no pre-processing



Others:



peak normalized to -0.1dBFS

signal multiplied by random number every 5 seconds (uniform distribution [0.1, 1.0] = [-20dB, 0dB])






Authors

Marco Comunità - Centre for Digital Music, Queen Mary University of London

Github

https://github.com/mcomunita/tonetwist-afx-dataset

Reference

If you make use of AUDIO-EFFECTS-DATASET, please cite the following publication:

@misc{comunità2025nablafxframeworkdifferentiableblackbox,
      title={NablAFx: A Framework for Differentiable Black-box and Gray-box Modeling of Audio Effects}, 
      author={Marco Comunità and Christian J. Steinmetz and Joshua D. Reiss},
      year={2025},
      eprint={2502.11668},
      archivePrefix={arXiv},
      primaryClass={cs.SD},
      url={https://arxiv.org/abs/2502.11668}, 
}
DOI: 10.5281/zenodo.10794658
title: ToneTwist AFx Dataset: Electro Harmonix Metal Muff

description: Settings




Volume
Gate
Distortion
Treble
Mid
Bass


10
0
1
5
5
5


10
0
5
5
5
5


10
0
10
5
5
5




Dry with markers


Dry inputs are a selection of clean guitar and bass recordings from different sources:



IDMT-SMT-GUITAR - dataset 2 (7:23 min)

IDMT-SMT-GUITAR - dataset 4 - Career SG (6:08 min)

IDMT-SMT-GUITAR - dataset 4 - Ibanez 2820 (5:14 min)

IDMT-SMT-Bass-Single-Track - (5:58 min)

NAM: Neural Amp Modeler - (3:11 min)

Private Guitar Data - (5:19 min)

YouTube Bass Recordings - (10:09 min)


Pre-processing:



All:



synchronization markers (2 impulses) added at start and end of every file



IDMT-SMT-GUITAR - dataset 2:



peak normalized to -6dBFS



NAM:



no pre-processing



Others:



peak normalized to -0.1dBFS

signal multiplied by random number every 5 seconds (uniform distribution [0.1, 1.0] = [-20dB, 0dB])






Authors

Marco Comunità - Centre for Digital Music, Queen Mary University of London

Github

https://github.com/mcomunita/tonetwist-afx-dataset

Reference

If you make use of AUDIO-EFFECTS-DATASET, please cite the following publication:

@misc{comunità2025nablafxframeworkdifferentiableblackbox,
      title={NablAFx: A Framework for Differentiable Black-box and Gray-box Modeling of Audio Effects}, 
      author={Marco Comunità and Christian J. Steinmetz and Joshua D. Reiss},
      year={2025},
      eprint={2502.11668},
      archivePrefix={arXiv},
      primaryClass={cs.SD},
      url={https://arxiv.org/abs/2502.11668}, 
}
DOI: 10.5281/zenodo.10794659
title: ToneTwist AFx Dataset: Electro Harmonix Metal Muff

description: Settings




Volume
Gate
Distortion
Treble
Mid
Bass


10
0
1
5
5
5


10
0
5
5
5
5


10
0
10
5
5
5




Dry with markers


Dry inputs are a selection of clean guitar and bass recordings from different sources:



IDMT-SMT-GUITAR - dataset 2 (7:23 min)

IDMT-SMT-GUITAR - dataset 4 - Career SG (6:08 min)

IDMT-SMT-GUITAR - dataset 4 - Ibanez 2820 (5:14 min)

IDMT-SMT-Bass-Single-Track - (5:58 min)

NAM: Neural Amp Modeler - (3:11 min)

Private Guitar Data - (5:19 min)

YouTube Bass Recordings - (10:09 min)


Pre-processing:



All:



synchronization markers (2 impulses) added at start and end of every file



IDMT-SMT-GUITAR - dataset 2:



peak normalized to -6dBFS



NAM:



no pre-processing



Others:



peak normalized to -0.1dBFS

signal multiplied by random number every 5 seconds (uniform distribution [0.1, 1.0] = [-20dB, 0dB])






Authors

Marco Comunità - Centre for Digital Music, Queen Mary University of London

Github

https://github.com/mcomunita/tonetwist-afx-dataset

Reference

If you make use of AUDIO-EFFECTS-DATASET, please cite the following publication:

@misc{comunità2025nablafxframeworkdifferentiableblackbox,
      title={NablAFx: A Framework for Differentiable Black-box and Gray-box Modeling of Audio Effects}, 
      author={Marco Comunità and Christian J. Steinmetz and Joshua D. Reiss},
      year={2025},
      eprint={2502.11668},
      archivePrefix={arXiv},
      primaryClass={cs.SD},
      url={https://arxiv.org/abs/2502.11668}, 
}
DOI: 10.5281/zenodo.10796408
title: ToneTwist AFx Dataset: Landlord Brewers Droop Chorus

description: Settings




Level
Depth
Speed


5
10
5


8
10
10




Dry with markers


Dry inputs are a selection of clean guitar and bass recordings from different sources:



IDMT-SMT-GUITAR - dataset 2 (7:23 min)

IDMT-SMT-GUITAR - dataset 4 - Career SG (6:08 min)

IDMT-SMT-GUITAR - dataset 4 - Ibanez 2820 (5:14 min)

IDMT-SMT-Bass-Single-Track - (5:58 min)

NAM: Neural Amp Modeler - (3:11 min)

Private Guitar Data - (5:19 min)

YouTube Bass Recordings - (10:09 min)


Pre-processing:



All:



synchronization markers (2 impulses) added at start and end of every file



IDMT-SMT-GUITAR - dataset 2:



peak normalized to -6dBFS



NAM:



no pre-processing



Others:



peak normalized to -0.1dBFS

signal multiplied by random number every 5 seconds (uniform distribution [0.1, 1.0] = [-20dB, 0dB])






Authors

Marco Comunità - Centre for Digital Music, Queen Mary University of London

Github

https://github.com/mcomunita/tonetwist-afx-dataset

Reference

If you make use of AUDIO-EFFECTS-DATASET, please cite the following publication:

@misc{comunità2025nablafxframeworkdifferentiableblackbox,
      title={NablAFx: A Framework for Differentiable Black-box and Gray-box Modeling of Audio Effects}, 
      author={Marco Comunità and Christian J. Steinmetz and Joshua D. Reiss},
      year={2025},
      eprint={2502.11668},
      archivePrefix={arXiv},
      primaryClass={cs.SD},
      url={https://arxiv.org/abs/2502.11668}, 
}
DOI: 10.5281/zenodo.10796407
title: ToneTwist AFx Dataset: Landlord Brewers Droop Chorus

description: Settings




Level
Depth
Speed


5
10
5


8
10
10




Dry with markers


Dry inputs are a selection of clean guitar and bass recordings from different sources:



IDMT-SMT-GUITAR - dataset 2 (7:23 min)

IDMT-SMT-GUITAR - dataset 4 - Career SG (6:08 min)

IDMT-SMT-GUITAR - dataset 4 - Ibanez 2820 (5:14 min)

IDMT-SMT-Bass-Single-Track - (5:58 min)

NAM: Neural Amp Modeler - (3:11 min)

Private Guitar Data - (5:19 min)

YouTube Bass Recordings - (10:09 min)


Pre-processing:



All:



synchronization markers (2 impulses) added at start and end of every file



IDMT-SMT-GUITAR - dataset 2:



peak normalized to -6dBFS



NAM:



no pre-processing



Others:



peak normalized to -0.1dBFS

signal multiplied by random number every 5 seconds (uniform distribution [0.1, 1.0] = [-20dB, 0dB])






Authors

Marco Comunità - Centre for Digital Music, Queen Mary University of London

Github

https://github.com/mcomunita/tonetwist-afx-dataset

Reference

If you make use of AUDIO-EFFECTS-DATASET, please cite the following publication:

@misc{comunità2025nablafxframeworkdifferentiableblackbox,
      title={NablAFx: A Framework for Differentiable Black-box and Gray-box Modeling of Audio Effects}, 
      author={Marco Comunità and Christian J. Steinmetz and Joshua D. Reiss},
      year={2025},
      eprint={2502.11668},
      archivePrefix={arXiv},
      primaryClass={cs.SD},
      url={https://arxiv.org/abs/2502.11668}, 
}
DOI: 10.15468/dl.2nkmj3
title: Occurrence Download

description: A dataset containing 949 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is one of (Spain, Portugal)",
 "TaxonKey is Salmo salar Linnaeus, 1758"
 ]
}

 The dataset includes 949 records from 17 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004399-250214102907787/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.10796321
title: ToneTwist AFx Dataset: Harley Benton Fuzzy Logic

description: Settings




Volume
Fuzz


10
1


10
5


10
10




Dry with markers


Dry inputs are a selection of clean guitar and bass recordings from different sources:



IDMT-SMT-GUITAR - dataset 2 (7:23 min)

IDMT-SMT-GUITAR - dataset 4 - Career SG (6:08 min)

IDMT-SMT-GUITAR - dataset 4 - Ibanez 2820 (5:14 min)

IDMT-SMT-Bass-Single-Track - (5:58 min)

NAM: Neural Amp Modeler - (3:11 min)

Private Guitar Data - (5:19 min)

YouTube Bass Recordings - (10:09 min)


Pre-processing:



All:



synchronization markers (2 impulses) added at start and end of every file



IDMT-SMT-GUITAR - dataset 2:



peak normalized to -6dBFS



NAM:



no pre-processing



Others:



peak normalized to -0.1dBFS

signal multiplied by random number every 5 seconds (uniform distribution [0.1, 1.0] = [-20dB, 0dB])






Authors

Marco Comunità - Centre for Digital Music, Queen Mary University of London

Github

https://github.com/mcomunita/tonetwist-afx-dataset

Reference

If you make use of AUDIO-EFFECTS-DATASET, please cite the following publication:

@misc{comunità2025nablafxframeworkdifferentiableblackbox,
      title={NablAFx: A Framework for Differentiable Black-box and Gray-box Modeling of Audio Effects}, 
      author={Marco Comunità and Christian J. Steinmetz and Joshua D. Reiss},
      year={2025},
      eprint={2502.11668},
      archivePrefix={arXiv},
      primaryClass={cs.SD},
      url={https://arxiv.org/abs/2502.11668}, 
}
DOI: 10.5281/zenodo.10796322
title: ToneTwist AFx Dataset: Harley Benton Fuzzy Logic

description: Settings




Volume
Fuzz


10
1


10
5


10
10




Dry with markers


Dry inputs are a selection of clean guitar and bass recordings from different sources:



IDMT-SMT-GUITAR - dataset 2 (7:23 min)

IDMT-SMT-GUITAR - dataset 4 - Career SG (6:08 min)

IDMT-SMT-GUITAR - dataset 4 - Ibanez 2820 (5:14 min)

IDMT-SMT-Bass-Single-Track - (5:58 min)

NAM: Neural Amp Modeler - (3:11 min)

Private Guitar Data - (5:19 min)

YouTube Bass Recordings - (10:09 min)


Pre-processing:



All:



synchronization markers (2 impulses) added at start and end of every file



IDMT-SMT-GUITAR - dataset 2:



peak normalized to -6dBFS



NAM:



no pre-processing



Others:



peak normalized to -0.1dBFS

signal multiplied by random number every 5 seconds (uniform distribution [0.1, 1.0] = [-20dB, 0dB])






Authors

Marco Comunità - Centre for Digital Music, Queen Mary University of London

Github

https://github.com/mcomunita/tonetwist-afx-dataset

Reference

If you make use of AUDIO-EFFECTS-DATASET, please cite the following publication:

@misc{comunità2025nablafxframeworkdifferentiableblackbox,
      title={NablAFx: A Framework for Differentiable Black-box and Gray-box Modeling of Audio Effects}, 
      author={Marco Comunità and Christian J. Steinmetz and Joshua D. Reiss},
      year={2025},
      eprint={2502.11668},
      archivePrefix={arXiv},
      primaryClass={cs.SD},
      url={https://arxiv.org/abs/2502.11668}, 
}
DOI: 10.5281/zenodo.10455729
title: ToneTwist AFx Dataset: Dry with markers

description: Dry inputs are a selection of clean guitar and bass recordings from different sources:



IDMT-SMT-GUITAR - dataset 2 (7:23 min)

IDMT-SMT-GUITAR - dataset 4 - Career SG (6:08 min)

IDMT-SMT-GUITAR - dataset 4 - Ibanez 2820 (5:14 min)

IDMT-SMT-Bass-Single-Track - (5:58 min)

NAM: Neural Amp Modeler - (3:11 min)

Private Guitar Data - (5:19 min)

YouTube Bass Recordings - (10:09 min)


Pre-processing:



All:



synchronization markers (2 impulses) added at start and end of every file



IDMT-SMT-GUITAR - dataset 2:



peak normalized to -6dBFS



NAM:



no pre-processing



Others:



peak normalized to -0.1dBFS

signal multiplied by random number every 5 seconds (uniform distribution [0.1, 1.0] = [-20dB, 0dB])






Authors

Marco Comunità - Centre for Digital Music, Queen Mary University of London

Github

https://github.com/mcomunita/tonetwist-afx-dataset

Reference

If you make use of this dataset, please cite the following publications:

@misc{comunità2025nablafxframeworkdifferentiableblackbox,
      title={NablAFx: A Framework for Differentiable Black-box and Gray-box Modeling of Audio Effects}, 
      author={Marco Comunità and Christian J. Steinmetz and Joshua D. Reiss},
      year={2025},
      eprint={2502.11668},
      archivePrefix={arXiv},
      primaryClass={cs.SD},
      url={https://arxiv.org/abs/2502.11668}, 
}
DOI: 10.5281/zenodo.10455730
title: ToneTwist AFx Dataset: Dry with markers

description: Dry inputs are a selection of clean guitar and bass recordings from different sources:



IDMT-SMT-GUITAR - dataset 2 (7:23 min)

IDMT-SMT-GUITAR - dataset 4 - Career SG (6:08 min)

IDMT-SMT-GUITAR - dataset 4 - Ibanez 2820 (5:14 min)

IDMT-SMT-Bass-Single-Track - (5:58 min)

NAM: Neural Amp Modeler - (3:11 min)

Private Guitar Data - (5:19 min)

YouTube Bass Recordings - (10:09 min)


Pre-processing:



All:



synchronization markers (2 impulses) added at start and end of every file



IDMT-SMT-GUITAR - dataset 2:



peak normalized to -6dBFS



NAM:



no pre-processing



Others:



peak normalized to -0.1dBFS

signal multiplied by random number every 5 seconds (uniform distribution [0.1, 1.0] = [-20dB, 0dB])






Authors

Marco Comunità - Centre for Digital Music, Queen Mary University of London

Github

https://github.com/mcomunita/tonetwist-afx-dataset

Reference

If you make use of this dataset, please cite the following publications:

@misc{comunità2025nablafxframeworkdifferentiableblackbox,
      title={NablAFx: A Framework for Differentiable Black-box and Gray-box Modeling of Audio Effects}, 
      author={Marco Comunità and Christian J. Steinmetz and Joshua D. Reiss},
      year={2025},
      eprint={2502.11668},
      archivePrefix={arXiv},
      primaryClass={cs.SD},
      url={https://arxiv.org/abs/2502.11668}, 
}
DOI: 10.20350/digitalcsic/3860
title: 1762

description: 1 .pdf (1 Pag.) con texto descriptivo y 1 Fig. This EEAD-CSIC database – Variedades frutales de hueso y pepita is made available under the Open Database License: http://opendatacommons.org/licenses/odbl/1.0/. Any rights in individual contents of the database are licensed under the Database Contents License: http://opendatacommons.org/licenses/dbcl/1.0/.
description: [ES] Caracterización pomológica, período de maduración e ilustración del fruto de esta variedad de manzano descrita en la Cartografía de frutales de hueso y pepita (Herrero J et al., 1964).
description: [EN] Pomological characterization, maturation time and fruit figure of apple cultivar described in “Cartografía de frutales de hueso y pepita” (Herrero J et al., 1964).
DOI: 10.5281/zenodo.10798150
title: ToneTwist AFx Dataset - External: Universal Audio 6176 Vintage Channel Strip - 1176LN Limiter

description: Dry



Dry inputs are from:







IDMT-SMT-Audio-Effects





Settings












Attack






Release










Input












Output












Ratio






10
10
4
7
All





 

From source publication:





1176LN Limiter: Similarly, the wildly used field-effect transistor limiter 1176LN is sampled from the same 6176 Vintage Channel Strip unit. The limiter samples are recorded with the following settings: attack 800us, release 1100 ms, input level 4, output level 7 and ratio ALL. We use the slowest attack and release settings in order to further test the long-term memory of the models. The compression ratio value of ALL corresponds to all the ratio buttons of an original 1176 being pushed simultaneously. Thus, this setting also introduces distortion due to the variation of attack and release times.


Github

https://github.com/mcomunita/tonetwist-afx-dataset



Source



@article{martinez2020deep,
  title={Deep learning for black-box modeling of audio effects},
  author={Mart{\'\i}nez Ram{\'\i}rez, Marco A and Benetos, Emmanouil and Reiss, Joshua D},
  journal={Applied Sciences},
  volume={10},
  number={2},
  pages={638},
  year={2020},
  publisher={MDPI}}


Web



https://mchijmma.github.io/DL-AFx


Code

N.A.

Original Data





https://zenodo.org/records/3562442