cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.15067335
title: Anime vs Cartoon Dataset

description: Description:

The Anime vs Cartoon Dataset is a specialized collection of images designed to differentiate between two popular forms of animation: anime and cartoons. While both anime and cartoons share similarities in being animated visual media, they possess distinct stylistic and structural characteristics that set them apart. This dataset is intended for use in developing and testing convolutional neural networks (CNNs) or other machine learning models for classification tasks, enabling the automated identification of whether an image belongs to the anime or cartoon category.

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Context and Motivation

Anime and cartoons are both beloved forms of entertainment worldwide, yet they originate from different cultural contexts and exhibit unique artistic styles. Anime, typically associated with Japanese culture, often features detailed backgrounds, unique facial expressions, and a wide range of color palettes, while cartoons, more commonly linked to Western culture, tend to have simpler designs, more exaggerated features, and distinct outlines. These differences, though subtle, provide a rich ground for developing image classification models that can automatically distinguish between the two.

Dataset Content

The dataset consists of images categorized into two distinct classes: Anime and Cartoon. The images were carefully collected and labeled to ensure a balanced representation of both categories. The images span various styles and themes within each category, including different character designs, backgrounds, and color schemes, providing a diverse set of examples for model training.



Anime: Images classified as anime, representing the distinctive characteristics of Japanese animation.

Cartoon: Images classified as cartoons, showcasing the unique style typical of Western animation.


Applications

This dataset is ideal for



Developing convolutional neural networks (CNNs) for image classification tasks.

Fine-tuning pre-trained models on a new domain-specific dataset.

Exploring the stylistic differences between anime and cartoon animations.

Building automated systems for content moderation or media sorting based on animation type.


This dataset is sourced from Kaggle.
DOI: 10.5281/zenodo.15067336
title: Anime vs Cartoon Dataset

description: Description:

The Anime vs Cartoon Dataset is a specialized collection of images designed to differentiate between two popular forms of animation: anime and cartoons. While both anime and cartoons share similarities in being animated visual media, they possess distinct stylistic and structural characteristics that set them apart. This dataset is intended for use in developing and testing convolutional neural networks (CNNs) or other machine learning models for classification tasks, enabling the automated identification of whether an image belongs to the anime or cartoon category.

Download Dataset

Context and Motivation

Anime and cartoons are both beloved forms of entertainment worldwide, yet they originate from different cultural contexts and exhibit unique artistic styles. Anime, typically associated with Japanese culture, often features detailed backgrounds, unique facial expressions, and a wide range of color palettes, while cartoons, more commonly linked to Western culture, tend to have simpler designs, more exaggerated features, and distinct outlines. These differences, though subtle, provide a rich ground for developing image classification models that can automatically distinguish between the two.

Dataset Content

The dataset consists of images categorized into two distinct classes: Anime and Cartoon. The images were carefully collected and labeled to ensure a balanced representation of both categories. The images span various styles and themes within each category, including different character designs, backgrounds, and color schemes, providing a diverse set of examples for model training.



Anime: Images classified as anime, representing the distinctive characteristics of Japanese animation.

Cartoon: Images classified as cartoons, showcasing the unique style typical of Western animation.


Applications

This dataset is ideal for



Developing convolutional neural networks (CNNs) for image classification tasks.

Fine-tuning pre-trained models on a new domain-specific dataset.

Exploring the stylistic differences between anime and cartoon animations.

Building automated systems for content moderation or media sorting based on animation type.


This dataset is sourced from Kaggle.
DOI: 10.34740/kaggle/dsv/11123673
title: SUGARCANE DATASET
DOI: 10.15468/dl.9452sc
title: Occurrence Download

description: A dataset containing 68 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Calodera rubens Erichson, 1837",
 "HasGeospatialIssue is false",
 "HasCoordinate is true"
 ]
}

 The dataset includes 68 records from 9 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0021620-250310093411724/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.j7cuke
title: Occurrence Download

description: A dataset containing 2155 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((-64.03877 -18.15813,-63.88296 -18.15813,-63.85676 -18.00609,-63.89993 -17.96446,-63.90075 -17.91636,-63.94355 -17.89242,-63.95487 -17.85531,-64.00805 -17.79922,-64.06927 -17.83017,-63.98877 -18.02045,-64.04159 -18.0647,-64.03877 -18.15813))",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Aves"
 ]
}

 The dataset includes 2155 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0021621-250310093411724/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.34740/kaggle/dsv/11123748
title: ⏳ endoflife.date database (duckdb)
DOI: 10.15468/dl.nehwhy
title: Occurrence Download

description: A dataset containing 343 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Brachymeria podagrica (Fabricius, 1787)",
 "HasGeospatialIssue is false",
 "HasCoordinate is true"
 ]
}

 The dataset includes 343 records from 28 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0021623-250310093411724/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.28643251
title: Supplementary Material from Turning lances into shields: flower mantids stretch their raptorial forelegs to avert and deflect predator attack

description: Videos S1-S5.zip
DOI: 10.6084/m9.figshare.28643251.v1
title: Supplementary Material from Turning lances into shields: flower mantids stretch their raptorial forelegs to avert and deflect predator attack

description: Videos S1-S5.zip
DOI: 10.15468/dl.ew83h8
title: Occurrence Download

description: A dataset containing 61 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Brachycyrtus ornatus Kriechbaumer, 1880",
 "HasGeospatialIssue is false",
 "HasCoordinate is true"
 ]
}

 The dataset includes 61 records from 18 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0021624-250310093411724/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.34740/kaggle/dsv/11017460
title: Steam Games Dataset 2025
DOI: 10.15468/dl.jds8t9
title: Occurrence Download

description: A dataset containing 1733 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Abrus precatorius L., Acanthospermum hispidum DC., Achyranthes aspera L., Ailanthus excelsa Roxb., Alternanthera pungens Kunth, Amaranthus hybridus L., Argemone mexicana L., Argemone ochroleuca Sweet, Bidens bipinnata L., Bidens pilosa L., Blainvillea acmella (L.) Philipson, Cardiospermum grandiflorum Sw., Cenchrus biflorus Roxb., Cenchrus ciliaris L., Centaurea solstitialis L., Commelina benghalensis L., Cryptostegia grandiflora (Roxb.) R.Br., Cuscuta pentagona Engelm., Datura ferox L., Datura innoxia Mill., Datura quercifolia Kunth, Datura stramonium L., Erigeron bonariensis L., Gomphrena celosioides Mart., Guilleminea densa (Willd.) Moq., Jacaranda mimosifolia D.Don, Lagarosiphon major (Ridl.) Moss, Lantana camara L., Launaea intybacea (Jacq.) Beauverd, Leucaena leucocephala (Lam.) de Wit, Melia azedarach L., Mimosa pigra L., Opuntia engelmannii Salm-Dyck ex Engelm., Oxalis corniculata L., Cyperus blepharoleptos Steud., Panicum repens L., Parthenium hysterophorus L., Paspalum scrobiculatum L., Pinus patula Schiede ex Schltdl. & Cham., Portulaca oleracea L., Prosopis glandulosa Torr., Prosopis juliflora (Sw.) DC., Prosopis pallida (Humb. & Bonpl. ex Willd.) Kunth, Prosopis nuda Schinini, Prosopis velutina Wooton, Ricinus communis L., Robinia pseudoacacia L., Rottboellia cochinchinensis (Lour.) Clayton, Salvinia ×molesta D.S.Mitch., Senecio inaequidens DC., Senna obtusifolia (L.) H.S.Irwin & Barneby, Sorghum bicolor (L.) Moench, Tagetes minuta L., Terminalia catappa L., Trapa natans L., Tridax procumbens L.)",
 "BasisOfRecord is one of (Specimen, Human Observation, Observation, Living Specimen, Machine Observation, Literature Occurrence)",
 "Country is one of (Botswana)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 1733 records from 24 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0021625-250310093411724/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.vqqgpc
title: Occurrence Download

description: A dataset containing 614 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Cacopsylla peregrina (Foerster, 1848)",
 "HasGeospatialIssue is false",
 "HasCoordinate is true"
 ]
}

 The dataset includes 614 records from 46 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0021627-250310093411724/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.28424276
title: A bipolar-redox tetraalkynylporphyrin macrocycle cathode with 12-electrons-transfer for high-energy aluminum-organic batteries

description: Atomic coordinates of the optimized structures in Density functional theory (DFT) calculations.The initial and final configurations of molecular dynamics trajectories.
DOI: 10.6084/m9.figshare.28424276.v1
title: A bipolar-redox tetraalkynylporphyrin macrocycle cathode with 12-electrons-transfer for high-energy aluminum-organic batteries

description: Atomic coordinates of the optimized structures in Density functional theory (DFT) calculations.The initial and final configurations of molecular dynamics trajectories.
DOI: 10.6084/m9.figshare.28588511
title: Porcine Macrophage Expression Matrixes

description: Processed_macrophages.h5ad: Porcine Macrophage Expression Matrixes. It can be read with scanpy python package. About 114881 cells are included.
DOI: 10.15468/dl.9f2ery
title: Occurrence Download

description: A dataset containing 4 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Bruchophagus platypterus (Walker, 1834)",
 "HasGeospatialIssue is false",
 "HasCoordinate is true"
 ]
}

 The dataset includes 4 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0021629-250310093411724/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.82ucm8
title: Occurrence Download

description: A dataset containing 394 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((-98.99901 19.35985,-99.04662 19.3609,-99.07817 19.36247,-99.09533 19.36247,-99.10806 19.35411,-99.10308 19.32642,-99.07596 19.31754,-99.03056 19.29299,-99.00344 19.29246,-98.96745 19.30396,-98.95472 19.3212,-98.99901 19.35985))",
 "HasGeospatialIssue is false",
 "TaxonKey is Arachnida"
 ]
}

 The dataset includes 394 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0021630-250310093411724/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.mbyb3m
title: Occurrence Download

description: A dataset containing 717 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((-32.11839 27.06497,35.11839 27.06497,35.11839 53.93503,-32.11839 53.93503,-32.11839 27.06497))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Acinipe Rambur, 1838"
 ]
}

 The dataset includes 717 records from 10 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0021631-250310093411724/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.tehz55
title: Occurrence Download

description: A dataset containing 76314 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Myotis bechsteinii (Kuhl, 1817), Myotis myotis (Borkhausen, 1797), Myotis mystacinus (Kuhl, 1817), Nyctalus leisleri (Kuhl, 1817), Vespertilio murinus Linnaeus, 1758, Capra ibex Linnaeus, 1758, Rhinolophus ferrumequinum (Schreber, 1774), Barbastella barbastellus (Schreber, 1774), Podarcis muralis (Laurenti, 1768), Lacerta agilis Linnaeus, 1758)",
 "HasCoordinate is true",
 "Year is greater than or equal to 2013",
 "Year is less than or equal to 2018",
 "CoordinateUncertaintyInMeters is less than or equal to 1000"
 ]
}

 The dataset includes 76314 records from 632 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0021626-250310093411724/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.gnfu5d
title: Occurrence Download

description: A dataset containing 972 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Acacia holosericea A.Cunn. ex G.Don, Setaria parviflora (Poir.) Kerguélen, Ceratophyllum demersum L., Dioscorea bulbifera L., Pontederia crassipes Mart., Mesosphaerum suaveolens (L.) Kuntze, Imperata cylindrica (L.) Raeusch., Lantana camara L., Leucaena leucocephala (Lam.) de Wit, Martynia annua L., Melia azedarach L., Cyperus blepharoleptos Steud., Paspalum scrobiculatum L., Phragmites australis (Cav.) Trin. ex Steud., Pistia stratiotes L., Prosopis juliflora (Sw.) DC., Rottboellia cochinchinensis (Lour.) Clayton, Salvinia ×molesta D.S.Mitch., Trapa natans L.)",
 "BasisOfRecord is one of (Specimen, Human Observation, Observation, Living Specimen, Machine Observation, Literature Occurrence)",
 "Country is one of (Burkina Faso)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 972 records from 17 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0021632-250310093411724/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.4ns977
title: Occurrence Download

description: A dataset containing 397261343 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Plantae",
 "Year 1902-2025"
 ]
}

 The dataset includes 397261343 records from 14161 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0021622-250310093411724/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.13145/bacdive114355.20241212.9.2
title: Streptomyces sp.

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive114355.20251217.10
title: Streptomyces sp.

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive114356.20241212.9.2
title: Streptomyces sp.

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive114356.20251217.10
title: Streptomyces sp.

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive114357.20241212.9.2
title: Streptomyces sp.

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive114357.20251217.10
title: Streptomyces sp.

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive114358.20241212.9.2
title: Streptomyces sp.

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive114358.20251217.10
title: Streptomyces sp.

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive114359.20241212.9.2
title: Streptomyces sp.

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive114359.20251217.10
title: Streptomyces sp.

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive114360.20241212.9.2
title: Streptomyces sp.

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.15156/bio/sh0106228.10fu
title: SH0106228.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.13145/bacdive114360.20251217.10
title: Streptomyces sp.

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive114361.20241212.9.2
title: Streptomyces sp.

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.15156/bio/sh0106229.10fu
title: SH0106229.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.13145/bacdive114361.20251217.10
title: Streptomyces sp.

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive114362.20241212.9.2
title: Streptomyces sp.

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.15156/bio/sh0106230.10fu
title: SH0106230.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.13145/bacdive114362.20251217.10
title: Streptomyces sp.

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive114363.20241212.9.2
title: Streptomyces sp.

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.