cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.10728861
title: R-CAUSTIC: Rippling CAUSTICs underwater Image dataset

description: Description
Rippling caustics seem to be the main factor degrading the underwater RGB image quality and affecting the image- based 3D reconstruction process in very shallow waters. These effects are adversely affecting image matching algorithms by throwing off most of them, leading to less accurate matches and causing issues in the Simultaneous Localization and Mapping (SLAM) based navigation of the Remotely Operated Vehicles (ROV) and Autonomous Underwater Vehicles (AUV) on shallow waters. Also, they are the main cause for dissimilarities in the generated textures and orthoimages. In order to fill the gap in the literature regading underwater rippling caustics imagery with real ground truth and reference images, the first real-world underwater caustics benchmark dataset which contains 1465 underwater images is presented. Together with the RGB imagery, the corresponding generated ground truth images are delivered for facilitating the training and testing of machine learning and deep learning methods for image classification. R-CAUSTIC dataset also provides the necessary data to evaluate, at least to some extent, the performance of 3D reconstruction approaches. Data were acquired using a GoPro Hero 4 Black action camera with image dimensions of 4000 x 3000 pixels, focal length of 2.77mm and pixel size of 1.55μm and a tripod. Action cameras are widely used for underwater image acquisition. The dataset was captured in near-shore underwater sites at depths varying from 0.5 to 2m. No artificial light sources were used. Due to the wind, the turbulent surface of the water created dynamic rippling caustics on the seabed. In total 1465 RGB images were collected, separated in 7 different datasets; five of them containing stereo images, one of them tri-stereo images and one consists of multi-stereo imagery acquired in 7 different camera poses.
 
Publication
The paper is availbale in Open Access here: https://ieeexplore.ieee.org/document/10172291
If you use this dataset please cite it as R-CAUSTIC [Reference].[Reference]: P. Agrafiotis, K. Karantzalos and A. Georgopoulos, "Seafloor-Invariant Caustics Removal From Underwater Imagery," in IEEE Journal of Oceanic Engineering, vol. 48, no. 4, pp. 1300-1321, Oct. 2023, doi: 10.1109/JOE.2023.3277168.
BibTeX:
@ARTICLE{10172291,
  author={Agrafiotis, Panagiotis and Karantzalos, Konstantinos and Georgopoulos, Andreas},
  journal={IEEE Journal of Oceanic Engineering}, 
  title={Seafloor-Invariant Caustics Removal From Underwater Imagery}, 
  year={2023},
  volume={48},
  number={4},
  pages={1300-1321},
  doi={10.1109/JOE.2023.3277168}}
DOI: 10.15468/dl.rmrhia
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "or" : [
 "ScientificName is × Epixochia amarantina (Regel) G.D.Rowley",
 "ScientificName is × Epixochia amarantina",
 "ScientificName is x Epixochia amarantina",
 "ScientificName is × Epixochia amarantina (Regel) G.D.Rowley",
 "ScientificName is × Epixochia amarantina (Regel) G.D.Rowley",
 "ScientificName is × Epixochia amarantina (Regel) G.D.Rowley"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0006207-160803222355964/datasets/export for details.
DOI: 10.5281/zenodo.6467282
title: R-CAUSTIC: Rippling CAUSTICs underwater Image dataset

description: Description
Rippling caustics seem to be the main factor degrading the underwater RGB image quality and affecting the image- based 3D reconstruction process in very shallow waters. These effects are adversely affecting image matching algorithms by throwing off most of them, leading to less accurate matches and causing issues in the Simultaneous Localization and Mapping (SLAM) based navigation of the Remotely Operated Vehicles (ROV) and Autonomous Underwater Vehicles (AUV) on shallow waters. Also, they are the main cause for dissimilarities in the generated textures and orthoimages. In order to fill the gap in the literature regading underwater rippling caustics imagery with real ground truth and reference images, the first real-world underwater caustics benchmark dataset which contains 1465 underwater images is presented. Together with the RGB imagery, the corresponding generated ground truth images are delivered for facilitating the training and testing of machine learning and deep learning methods for image classification. R-CAUSTIC dataset also provides the necessary data to evaluate, at least to some extent, the performance of 3D reconstruction approaches. Data were acquired using a GoPro Hero 4 Black action camera with image dimensions of 4000 x 3000 pixels, focal length of 2.77mm and pixel size of 1.55μm and a tripod. Action cameras are widely used for underwater image acquisition. The dataset was captured in near-shore underwater sites at depths varying from 0.5 to 2m. No artificial light sources were used. Due to the wind, the turbulent surface of the water created dynamic rippling caustics on the seabed. In total 1465 RGB images were collected, separated in 7 different datasets; five of them containing stereo images, one of them tri-stereo images and one consists of multi-stereo imagery acquired in 7 different camera poses.
 
Publication
The paper is availbale in Open Access here: https://ieeexplore.ieee.org/document/10172291
If you use this dataset please cite it as R-CAUSTIC [Reference].[Reference]: P. Agrafiotis, K. Karantzalos and A. Georgopoulos, "Seafloor-Invariant Caustics Removal From Underwater Imagery," in IEEE Journal of Oceanic Engineering, vol. 48, no. 4, pp. 1300-1321, Oct. 2023, doi: 10.1109/JOE.2023.3277168.
BibTeX:
@ARTICLE{10172291,
  author={Agrafiotis, Panagiotis and Karantzalos, Konstantinos and Georgopoulos, Andreas},
  journal={IEEE Journal of Oceanic Engineering}, 
  title={Seafloor-Invariant Caustics Removal From Underwater Imagery}, 
  year={2023},
  volume={48},
  number={4},
  pages={1300-1321},
  doi={10.1109/JOE.2023.3277168}}
DOI: 10.5281/zenodo.6467283
title: R-CAUSTIC: Rippling CAUSTICs underwater Image dataset

description:  

Version 2 available! Please make sure to download the latest version of the dataset! 

 

Description

Rippling caustics seem to be the main factor degrading the underwater RGB image quality and affecting the image- based 3D reconstruction process in very shallow waters. These effects are adversely affecting image matching algorithms by throwing off most of them, leading to less accurate matches and causing issues in the Simultaneous Localization and Mapping (SLAM) based navigation of the Remotely Operated Vehicles (ROV) and Autonomous Underwater Vehicles (AUV) on shallow waters. Also, they are the main cause for dissimilarities in the generated textures and orthoimages. In order to fill the gap in the literature regading underwater rippling caustics imagery with real ground truth and reference images, the first real-world underwater caustics benchmark dataset which contains 1465 underwater images is presented. Together with the RGB imagery, the corresponding generated ground truth images are delivered for facilitating the training and testing of machine learning and deep learning methods for image classification. R-CAUSTIC dataset also provides the necessary data to evaluate, at least to some extent, the performance of 3D reconstruction approaches. Data were acquired using a GoPro Hero 4 Black action camera with image dimensions of 4000 x 3000 pixels, focal length of 2.77mm and pixel size of 1.55μm and a tripod. Action cameras are widely used for underwater image acquisition. The dataset was captured in near-shore underwater sites at depths varying from 0.5 to 2m. No artificial light sources were used. Due to the wind, the turbulent surface of the water created dynamic rippling caustics on the seabed. In total 1465 RGB images were collected, separated in 7 different datasets; five of them containing stereo images, one of them tri-stereo images and one consists of multi-stereo imagery acquired in 7 different camera poses.

 

Publication

The paper is availbale in Open Access here: https://ieeexplore.ieee.org/document/10172291

If you use this dataset please cite it as R-CAUSTIC [Reference].[Reference]: P. Agrafiotis, K. Karantzalos and A. Georgopoulos, "Seafloor-Invariant Caustics Removal From Underwater Imagery," in IEEE Journal of Oceanic Engineering, vol. 48, no. 4, pp. 1300-1321, Oct. 2023, doi: 10.1109/JOE.2023.3277168.

BibTeX:

@ARTICLE{10172291,  author={Agrafiotis, Panagiotis and Karantzalos, Konstantinos and Georgopoulos, Andreas},  journal={IEEE Journal of Oceanic Engineering},  title={Seafloor-Invariant Caustics Removal From Underwater Imagery},  year={2023},  volume={48},  number={4},  pages={1300-1321},  doi={10.1109/JOE.2023.3277168}}
DOI: 10.15468/dl.yq4swp
title: Occurrence Download

description: A dataset containing 216 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Eriastrum brandegeae Mason"
 ]
}

 The dataset includes 216 records from 38 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0199734-230224095556074/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.5gffez
title: Occurrence Download

description: A dataset containing 16 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Myrcia depressa (Urb.) K.Campbell & Peguero"
 ]
}

 The dataset includes 16 records from 10 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0178550-240321170329656/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.6j7kbq
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "or" : [
 "ScientificName is Gymnocalycium × heidiae Neuhuber",
 "ScientificName is Gymnocalycium × heidiae",
 "ScientificName is Gymnocalycium x heidiae",
 "ScientificName is Gymnocalycium x heidiae Neuhuber",
 "ScientificName is Gymnocalycium xheidiae Neuhuber",
 "ScientificName is Gymnocalycium heidiae Neuhuber"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0006311-160803222355964/datasets/export for details.
DOI: 10.15468/dl.upnxxt
title: Occurrence Download

description: A dataset containing 201 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is China",
 "TaxonKey is Diplazium maximum (D.Don) C.Chr."
 ]
}

 The dataset includes 201 records from 21 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0410372-210914110416597/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17026/dans-246-8e9p
title: IVO-P Bogardeind Geldrop Inventarisend Veldonderzoek d.m.v. Proefsleuven. Bogardeind-Laarstraat (TOPA-terrein) te Geldrop

description: &lt;p&gt;NB in het rapport staat een foutief onderzoeksmeldingsnummerIn oktober 2017 heeft Antea Group, in opdracht van Moeskops’ Bouwbedrijf een Inventariserend Veldonderzoek door middel van proefsleuven, uitgevoerd ter plaatse van het plangebied Bogardeind-Laarstraat (TOPA-terrein) te Geldrop.Aanleiding voor het onderzoek is de herontwikkeling van de locatie tot onder andere woningbouw. Binnen het plangebied werden op voorhand resten verwacht van een historische landroute die vanaf de eerste historische kaarten in het plangebied gesitueerd werd.Het proefsleuvenonderzoek heeft van deze landroute inderdaad twee fasen van de begeleidende westgreppel opgeleverd. Tegelijkertijd is vastgesteld dat honderd jaar bouwen en slopen binnen het plangebied tot een bodemroering heeft geleidt die zich plaatselijk uitstrekt tot diep in de top van de C-Horizont en waarbij vermoedelijk de bovenste dertig tot veertig centimeter van de oorspronkelijk top zijn verloren. De aangetroffen archeologische sporen bevestigen dit vermoeden en laten zien dat alleen de onderste onderkanten van de diepste sporen bewaard zijn gebleven. Op verzoek van de ODZOB is de eerste conceptversie van de rapportage op onderdelen aangevuld. Revisie 01 is hiervan het gevolg.Geadviseerd wordt om het plangebied voor wat betreft archeologie vrij te geven ten gunste van de voorgenomen herontwikkeling. De implementatie van de bovenstaande aanbeveling is afhankelijk van het oordeel van de bevoegde overheid, in dezen de gemeente Geldrop-Mierlo. Deze dient een selectiebesluit te nemen. Een dergelijk besluit kan afwijken van het bovenstaande (selectie)advies. Het selectiebesluit van het bevoegd gezag stelt dat de archeologische verwachtingswaarde kan worden bijgesteld naar laag en het plangebied kan wat betreft archeologie worden vrijgegeven. Omdat er echter nog wel een kans bestaat op het aantreffen van losse archeologische vondsten of grondsporen, welke informatie kunnen geven over de historie van dit deel van Geldrop, wordt door de gemeente verzocht om de start van toekomstige graafwerkzaamheden te melden bij de regioarcheoloog Ria Berkvens van de Omgevingsdienst Zuidoost-Brabant.&lt;/p&gt;
DOI: 10.5281/zenodo.17103738
title: Cryo-EM structure and dynamic catalytic mechanisms of prokaryotic single-subunit acetyl-CoA carboxylase

description: Thank you for your interest in our work. All data and input files required to reproduce the molecular dynamics (MD) simulations and subsequent analyses are provided. The .tpr files necessary to rerun the simulations are available in the md_run_and_MMPBSA_input_files directory, while the corresponding trajectories are deposited in MD_results. Analysis scripts in the form of Jupyter notebooks (.ipynb) for reproducing MD analyses and predicted-structure clustering are provided in MD_analysis and predicted_structure_clustering, respectively. Results of structural comparison and ligand binding are supplied as PyMOL session files (.pse) in structure_comparation_and_ligands_binding.
DOI: 10.5281/zenodo.17103739
title: Cryo-EM structure and dynamic catalytic mechanisms of prokaryotic single-subunit acetyl-CoA carboxylase

description: Thank you for your interest in our work. All data and input files required to reproduce the molecular dynamics (MD) simulations and subsequent analyses are provided. The .tpr files necessary to rerun the simulations are available in the md_run_and_MMPBSA_input_files directory, while the corresponding trajectories are deposited in MD_results. Analysis scripts in the form of Jupyter notebooks (.ipynb) for reproducing MD analyses and predicted-structure clustering are provided in MD_analysis and predicted_structure_clustering, respectively. Results of structural comparison and ligand binding are supplied as PyMOL session files (.pse) in structure_comparation_and_ligands_binding.
DOI: 10.15468/dl.h3s3sn
title: Occurrence Download

description: A dataset containing 29413 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Specimen",
 "Country is Ecuador",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Squamata"
 ]
}

 The dataset includes 29413 records from 44 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002011-230828120925497/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.c4jwua
title: Occurrence Download

description: A dataset containing 8 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Ololygon jureia (Pombal & Gordo, 1991)"
 ]
}

 The dataset includes 8 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0298074-210914110416597/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.b66ggh
title: Occurrence Download

description: A dataset containing 25 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Xerophyta arabica (Baker) N.L.Menezes"
 ]
}

 The dataset includes 25 records from 6 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0034856-230810091245214/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.32ue68
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Choerophryne multisyllaba Günther & Richards, 2017"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0307395-210914110416597/datasets/export for details.
DOI: 10.15468/dl.caga5v
title: Occurrence Download

description: A dataset containing 81 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Xerophyta suaveolens (Greves) N.L.Menezes"
 ]
}

 The dataset includes 81 records from 13 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0034869-230810091245214/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.25650924
title: <b>Sustainability of global small-scale constructed wetlands for multiple pollutant control</b>

description: 196 qualified publications involving 364 CW sites were used to extract information related to water quality parameters. The following information from each original paper: (1) location, including latitude, longitude, country, and continent; (2) CW types, i.e., free water surface flow CWs (FWSCWs), subsurface flow CWs (SSFCWs), floating CWs (FCWs) and hybrid CWs (HCWs)<sup>8,57</sup>; (3) area (m<sup>2</sup>); (4) removal efficiency (%) and loading rate (g m<sup>-2</sup> d<sup>-1</sup>) of TN, TP, COD, and NH<sub>4</sub><sup>+</sup>-N.
DOI: 10.6084/m9.figshare.25650924.v1
title: <b>Sustainability of global small-scale constructed wetlands for multiple pollutant control</b>

description: 196 qualified publications involving 364 CW sites were used to extract information related to water quality parameters. The following information from each original paper: (1) location, including latitude, longitude, country, and continent; (2) CW types, i.e., free water surface flow CWs (FWSCWs), subsurface flow CWs (SSFCWs), floating CWs (FCWs) and hybrid CWs (HCWs)<sup>8,57</sup>; (3) area (m<sup>2</sup>); (4) removal efficiency (%) and loading rate (g m<sup>-2</sup> d<sup>-1</sup>) of TN, TP, COD, and NH<sub>4</sub><sup>+</sup>-N.
DOI: 10.15468/dl.fsdrnh
title: Occurrence Download

description: A dataset containing 90 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Peromyscus polius Osgood, 1904"
 ]
}

 The dataset includes 90 records from 10 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0230078-210914110416597/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.e7byzb
title: Occurrence Download

description: A dataset containing 1025 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((-194.76481 69.0494,-243.0925 44.37898,-258.58215 15.36084,-79.52189 9.31111,-102.44656 21.81655,-114.21867 32.80125,-125.99081 54.77102,-140.24128 71.55229,-171.22056 73.5913,-194.76481 69.0494))",
 "HasGeospatialIssue is false",
 "Month is March",
 "TaxonKey is Megaptera novaeangliae (Borowski, 1781)",
 "Year 2021-2021"
 ]
}

 The dataset includes 1025 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0022993-231002084531237/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.qf7yf3
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Dasineura gleditchiae (Osten Sacken, 1866)",
 {
 "not" : {
 "DatasetKey" : [
 "is Global database of alien macrofungi"
 ]
 }
 },
 {
 "or" : [
 "Country is Poland",
 "Country is Poland"
 ]
 }
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0385402-210914110416597/datasets/export for details.
DOI: 10.15468/dl.wsv9f7
title: Occurrence Download

description: A dataset containing 10354647 species occurrences available in GBIF matching the query:
{
 "Country" : [
 "is China"
 ]
}

 The dataset includes 10354647 records from 5084 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002010-230828120925497/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.3x6x5r
title: Occurrence Download

description: A dataset containing 1590 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Clibanornis rectirostris (M.Wied-Neuwied, 1831)"
 ]
}

 The dataset includes 1590 records from 13 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0131502-210914110416597/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ah8zzk
title: Occurrence Download

description: A dataset containing 688 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON ((-74.1546045000000049 40.7653388000000021, -74.1546045000000049 40.7694874600000006, -74.1546045000000049 40.7723596200000031, -74.1546045000000049 40.7755508999999989, -74.1546045000000049 40.7777847899999983, -74.1546045000000049 40.7804973799999999, -74.1546045000000049 40.7820930199999978, -74.1546045000000049 40.7852843000000007, -74.1510984899999954 40.7852843000000007, -74.1467956599999951 40.7852843000000007, -74.1423334699999970 40.7852843000000007, -74.1386681000000038 40.7852843000000007, -74.1386681000000038 40.7828908400000003, -74.1386681000000038 40.7808165100000011, -74.1386681000000038 40.7771465399999968, -74.1386681000000038 40.7734765599999989, -74.1386681000000038 40.7701257200000029, -74.1386681000000038 40.7677322600000025, -74.1386681000000038 40.7653388000000021, -74.1408992000000069 40.7653388000000021, -74.1437677499999950 40.7653388000000021, -74.1485486699999967 40.7653388000000021, -74.1507797600000060 40.7653388000000021, -74.1546045000000049 40.7653388000000021))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 1932",
 "BasisOfRecord is one of (Human Observation, Living Specimen, Observation, Specimen, Machine Observation)"
 ]
}

 The dataset includes 688 records from 8 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0094106-210914110416597/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.p542cs
title: Occurrence Download

description: A dataset containing 452 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Prosopis nigra (Griseb.) Hieron."
 ]
}

 The dataset includes 452 records from 55 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0210030-200613084148143/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.4osxrk
title: Occurrence Download

description: A dataset containing 520 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Secale montanum Guss."
 ]
}

 The dataset includes 520 records from 55 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0014306-200127171203522/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.