cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.t5wr3d
title: Occurrence Download

description: A dataset containing 5029 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Specimen",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Gagea lutea"
 ]
}

 The dataset includes 5029 records from 167 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0027673-250811113504898/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.m8264m
title: Occurrence Download

description: A dataset containing 220 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Specimen",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Gagea tibetica"
 ]
}

 The dataset includes 220 records from 9 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0027675-250811113504898/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.cvh8tc
title: Occurrence Download

description: A dataset containing 3113 species occurrences available in GBIF matching the query:
{
 "and" : [
 "GadmGid is NOR.7.5_1",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Mammalia"
 ]
}

 The dataset includes 3113 records from 12 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0027677-250811113504898/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.5yqrcj
title: Occurrence Download

description: A dataset containing 57 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Cenchrus purpureus",
 "Country is Indonesia",
 "HasCoordinate is true"
 ]
}

 The dataset includes 57 records from 10 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0027676-250811113504898/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.htnnk4
title: Occurrence Download

description: A dataset containing 8 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Cenchrus purpureus",
 "Country is Jamaica",
 "HasCoordinate is true"
 ]
}

 The dataset includes 8 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0027678-250811113504898/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.vfbtrt
title: Occurrence Download

description: A dataset containing 151 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Specimen",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Gagea triflora"
 ]
}

 The dataset includes 151 records from 26 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0027679-250811113504898/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.vr4f8m
title: Occurrence Download

description: A dataset containing 87 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Cenchrus purpureus",
 "Country is Japan",
 "HasCoordinate is true"
 ]
}

 The dataset includes 87 records from 15 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0027680-250811113504898/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.zkczh7
title: Occurrence Download

description: A dataset containing 2 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Cenchrus purpureus",
 "Country is Kiribati",
 "HasCoordinate is true"
 ]
}

 The dataset includes 2 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0027682-250811113504898/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.pqk95s
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Cenchrus purpureus",
 "Country is Lao People’s Democratic Republic",
 "HasCoordinate is true"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0027683-250811113504898/datasets/export for details.
DOI: 10.15468/dl.zws95e
title: Occurrence Download

description: A dataset containing 19382 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "TaxonKey is Stylidium graminifolium"
 ]
}

 The dataset includes 19382 records from 67 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0027684-250811113504898/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.awzcqd
title: Occurrence Download

description: A dataset containing 22 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Cenchrus purpureus",
 "Country is Malaysia",
 "HasCoordinate is true"
 ]
}

 The dataset includes 22 records from 9 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0027685-250811113504898/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.9dc8yb
title: Occurrence Download

description: A dataset listing the 1611 species recorded in GBIF matching the query:
{
 "and" : [
 "Country is India",
 "DatasetKey is one of (EOD – eBird Observation Dataset, iNaturalist Research-grade Observations, India Biodiversity Portal publication grade dataset, SeasonWatch - Tree Phenology Dataset (India), Pelagic sediment metagenome of Gulf of Khambhat, Microbial community structure of sediment microbiome in the pelagic zone of Gulf of Khambhat, Gujarat, India., Pl@ntNet automatically identified occurrences, BirdMap Data - GPS tracking of Storks, Cranes and birds of prey, breeding in Northern and Eastern Europe, Floral Survey of Ahmedabad Metro Phase II, Floral Survey of Surat Metro Rail Phase I)",
 "Geometry POLYGON((71.45008 24.19506,74.0873 15.01537,77.3047 16.48747,74.40376 25.0103,71.45008 24.19506))",
 "HasGeospatialIssue is false",
 "IucnRedListCategory is one of (NE, DD, LC, NT, VU, EN, CR, EW, EX)",
 "OccurrenceStatus is Present",
 "Year 2022-2025"
 ]
}

 The dataset's 1611 records were derived from 7 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0027674-250811113504898/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.7jzrex
title: Occurrence Download

description: A dataset containing 177302 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Populus nigra"
 ]
}

 The dataset includes 177302 records from 1988 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0027596-250811113504898/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/c4x5fpwc23.1
title: Guide in Data and Methodology

description: Given the implementation of the Data Security Law in China, the authors do not have permission to share data. We therefore provide a detailed and replicable guide in data and methodology.
DOI: 10.17632/rp73yg93n8.1
title: Fruits 360 dataset

description: Fruits 360 dataset: A dataset of images containing fruits Version: 2018.09.07.0 The following fruits are included: Apples (different varieties: Golden, Golden-Red, Granny Smith, Red, Red Delicious), Apricot, Avocado, Avocado ripe, Banana (Yellow, Red), Cactus fruit, Cantaloupe (2 varieties), Carambula, Cherry (different varieties, Rainier), Cherry Wax (Yellow, Red, Black), Clementine, Cocos, Dates, Granadilla, Grape (Pink, White, White2), Grapefruit (Pink, White), Guava, Huckleberry, Kiwi, Kaki, Kumsquats, Lemon (normal, Meyer), Lime, Lychee, Mandarine, Mango, Maracuja, Melon Piel de Sapo, Mulberry, Nectarine, Orange, Papaya, Passion fruit, Peach, Pepino, Pear (different varieties, Abate, Monster, Williams), Physalis (normal, with Husk), Pineapple (normal, Mini), Pitahaya Red, Plum, Pomegranate, Quince, Rambutan, Raspberry, Salak, Strawberry (normal, Wedge), Tamarillo, Tangelo, Tomato (different varieties, Maroon, Cherry Red), Walnut. Dataset properties Total number of images: 55244. Training set size: 41322 images (one fruit per image). Test set size: 13877 images (one fruit per image). Multi-fruits set size: 45 images (more than one fruit (or fruit class) per image) Number of classes: 81 (fruits). Image size: 100x100 pixels. Filename format: image_index_100.jpg (e.g. 32_100.jpg) or r_image_index_100.jpg (e.g. r_32_100.jpg) or r2_image_index_100.jpg. "r" stands for rotated fruit. "r2" means that the fruit was rotated around the 3rd axis. "100" comes from image size (100x100 pixels). Different varieties of the same fruit (apple for instance) are stored as belonging to different classes. How we made it Fruits were planted in the shaft of a low speed motor (3 rpm) and a short movie of 20 seconds was recorded. A Logitech C920 camera was used for filming the fruits. This is one of the best webcams available. Behind the fruits we placed a white sheet of paper as background. However due to the variations in the lighting conditions, the background was not uniform and we wrote a dedicated algorithm which extract the fruit from the background. This algorithm is of flood fill type: we start from each edge of the image and we mark all pixels there, then we mark all pixels found in the neighborhood of the already marked pixels for which the distance between colors is less than a prescribed value. We repeat the previous step until no more pixels can be marked. All marked pixels are considered as being background (which is then filled with white) and the rest of pixels are considered as belonging to the object. The maximum value for the distance between 2 neighbor pixels is a parameter of the algorithm and is set (by trial and error) for each movie. Published research papers Horea Muresan, Mihai Oltean, Fruit recognition from images using deep learning, Acta Univ. Sapientiae, Informatica Vol. 10, Issue 1, pp. 26-42, 2018. License MIT License Copyright (c) 2017-2018 Mihai Oltean, Horea Muresan
DOI: 10.17632/rp73yg93n8.2
title: Fruits-360 dataset

description: Fruits-360: A dataset of images containing fruits and vegetables

Version: 2024.08.02.0

A high-quality, dataset of images containing fruits and vegetables. The following fruits and vegetables are included: Apples (different varieties: Crimson Snow, Golden, Golden-Red, Granny Smith, Pink Lady, Red, Red Delicious), Apricot, Avocado, Avocado ripe, Banana (Yellow, Red, Lady Finger), Beetroot Red, Blueberry, Cactus fruit, Cantaloupe (2 varieties), Carambula, Carrot, Cauliflower, Cherry (different varieties, Rainier), Cherry Wax (Yellow, Red, Black), Chestnut, Clementine, Cocos, Corn (with husk), Cucumber (ripened, various), Dates, Eggplant (normal and long), Fig, Ginger Root, Granadilla, Grape (Blue, Pink, White (different varieties)), Grapefruit (Pink, White), Guava, Hazelnut, Huckleberry, Kiwi, Kaki, Kohlrabi, Kumsquats, Lemon (normal, Meyer), Lime, Lychee, Mandarine, Mango (Green, Red), Mangostan, Maracuja, Melon Piel de Sapo, Mulberry, Nectarine (Regular, Flat), Nut (Forest, Pecan), Onion (Red, White), Orange, Papaya, Passion fruit, Peach (different varieties), Pepino, Pear (different varieties, Abate, Forelle, Kaiser, Monster, Red, Stone, Williams), Pepper (Red, Green, Orange, Yellow), Physalis (normal, with Husk), Pineapple (normal, Mini), Pitahaya Red, Plum (different varieties), Pomegranate, Pomelo Sweetie, Potato (Red, Sweet, White), Quince, Rambutan, Raspberry, Redcurrant, Salak, Strawberry (normal, Wedge), Tamarillo, Tangelo, Tomato (different varieties, Maroon, Cherry Red, Yellow, not ripened, Heart), Walnut, Watermelon, Zucchini (white and dark).

Dataset properties
Total number of images: 94110.

Training set size: 70491 images (one fruit or vegetable per image).

Test set size: 23619 images (one fruit or vegetable per image).

Number of classes: 141 (fruits, vegetables and nuts).

Image size: 100x100 pixels.

Filename format: image_index_100.jpg (e.g. 32_100.jpg) or r_image_index_100.jpg (e.g. r_32_100.jpg) or r2_image_index_100.jpg or r3_image_index_100.jpg. "r" stands for rotated fruit. "r2" means that the fruit was rotated around the 3rd axis. "100" comes from image size (100x100 pixels).

Different varieties of the same fruit (apple for instance) are stored as belonging to different classes.

Repository structure
Folders Training and Test contain images for training and testing purposes.

Alternate download
The Fruits-360 dataset can be downloaded from:

https://www.kaggle.com/moltean/fruits

https://github.com/fruits-360

How to cite
Mihai Oltean, Fruits-360 dataset, 2017-.

License: MIT License

Copyright (c) 2017- Mihai Oltean
DOI: 10.17632/rp73yg93n8.3
title: Fruits-360 dataset

description: Fruits-360: A dataset of images containing fruits and vegetables

Version: 2024.08.04.0

A high-quality, dataset of images containing fruits and vegetables. The following fruits and vegetables are included: Apples (different varieties: Crimson Snow, Golden, Golden-Red, Granny Smith, Pink Lady, Red, Red Delicious), Apricot, Avocado, Avocado ripe, Banana (Yellow, Red, Lady Finger), Beetroot Red, Blueberry, Cactus fruit, Cantaloupe (2 varieties), Carambula, Carrot, Cauliflower, Cherry (different varieties, Rainier), Cherry Wax (Yellow, Red, Black), Chestnut, Clementine, Cocos, Corn (with husk), Cucumber (ripened, various), Dates, Eggplant (normal and long), Fig, Ginger Root, Granadilla, Grape (Blue, Pink, White (different varieties)), Grapefruit (Pink, White), Guava, Hazelnut, Huckleberry, Kiwi, Kaki, Kohlrabi, Kumsquats, Lemon (normal, Meyer), Lime, Lychee, Mandarine, Mango (Green, Red), Mangostan, Maracuja, Melon Piel de Sapo, Mulberry, Nectarine (Regular, Flat), Nut (Forest, Pecan), Onion (Red, White), Orange, Papaya, Passion fruit, Peach (different varieties), Pepino, Pear (different varieties, Abate, Forelle, Kaiser, Monster, Red, Stone, Williams), Pepper (Red, Green, Orange, Yellow), Physalis (normal, with Husk), Pineapple (normal, Mini), Pitahaya Red, Plum (different varieties), Pomegranate, Pomelo Sweetie, Potato (Red, Sweet, White), Quince, Rambutan, Raspberry, Redcurrant, Salak, Strawberry (normal, Wedge), Tamarillo, Tangelo, Tomato (different varieties, Maroon, Cherry Red, Yellow, not ripened, Heart), Walnut, Watermelon, Zucchini (white and dark).

Dataset properties
Total number of images: 94110.

Training set size: 70491 images (one fruit or vegetable per image).

Test set size: 23619 images (one fruit or vegetable per image).

Number of classes: 141 (fruits, vegetables and nuts).

Image size: 100x100 pixels.

Filename format: image_index_100.jpg (e.g. 32_100.jpg) or r_image_index_100.jpg (e.g. r_32_100.jpg) or r2_image_index_100.jpg or r3_image_index_100.jpg. "r" stands for rotated fruit. "r2" means that the fruit was rotated around the 3rd axis. "100" comes from image size (100x100 pixels).

Different varieties of the same fruit (apple for instance) are stored as belonging to different classes.

Repository structure
Folders Training and Test contain images for training and testing purposes.

Alternate download
The Fruits-360 dataset can be downloaded from:

https://www.kaggle.com/moltean/fruits

https://github.com/fruits-360

How to cite
Mihai Oltean, Fruits-360 dataset, 2017-.

License: MIT License

Copyright (c) 2017-, Mihai Oltean
DOI: 10.17632/rp73yg93n8.4
title: Fruits-360 dataset

description: Fruits-360: A dataset of images containing fruits and vegetables

Version: 2025.03.11.0

A high-quality, dataset of images containing fruits and vegetables. The following fruits and vegetables are included: Apples (different varieties: Crimson Snow, Golden, Golden-Red, Granny Smith, Pink Lady, Red, Red Delicious), Apricot, Avocado, Avocado ripe, Banana (Yellow, Red, Lady Finger), Beetroot Red, Blueberry, Cactus fruit, Cantaloupe (2 varieties), Carambula, Carrot, Cauliflower, Cherry (different varieties, Rainier), Cherry Wax (Yellow, Red, Black), Chestnut, Clementine, Cocos, Corn (with husk), Cucumber (ripened, various), Dates, Eggplant (normal and long), Fig, Ginger Root, Granadilla, Grape (Blue, Pink, White (different varieties)), Grapefruit (Pink, White), Guava, Hazelnut, Huckleberry, Kiwi, Kaki, Kohlrabi, Kumsquats, Lemon (normal, Meyer), Lime, Lychee, Mandarine, Mango (Green, Red), Mangostan, Maracuja, Melon Piel de Sapo, Mulberry, Nectarine (Regular, Flat), Nut (Forest, Pecan), Onion (Red, White), Orange, Papaya, Passion fruit, Peach (different varieties), Pepino, Pear (different varieties, Abate, Forelle, Kaiser, Monster, Red, Stone, Williams), Pepper (Red, Green, Orange, Yellow), Physalis (normal, with Husk), Pineapple (normal, Mini), Pitahaya Red, Plum (different varieties), Pomegranate, Pomelo Sweetie, Potato (Red, Sweet, White), Quince, Rambutan, Raspberry, Redcurrant, Salak, Strawberry (normal, Wedge), Tamarillo, Tangelo, Tomato (different varieties, Maroon, Cherry Red, Yellow, not ripened, Heart), Walnut, Watermelon, Zucchini (white and dark).

Dataset properties

Total number of images: 106671.

Training set size: 79921 images.

Test set size: 26750 images.

Number of classes: 160 (fruits, vegetables, nuts and seeds).

Image size: 100x100 pixels.

Filename format: image_index_100.jpg (e.g. 32_100.jpg) or r_image_index_100.jpg (e.g. r_32_100.jpg) or r2_image_index_100.jpg or r3_image_index_100.jpg. "r" stands for rotated fruit. "r2" means that the fruit was rotated around the 3rd axis. "100" comes from image size (100x100 pixels).

Different varieties of the same fruit (apple for instance) are stored as belonging to different classes.

Repository structure

Folders Training and Test contain images for training and testing purposes.

Alternate download
The Fruits-360 dataset can be downloaded from:

https://www.kaggle.com/moltean/fruits

https://github.com/fruits-360

How to cite
Mihai Oltean, Fruits-360 dataset, 2017-.

License:

C BY-SA 4.0

Copyright (c) 2017-, Mihai Oltean

You are free to: Share and Adapt.

Under the following terms: Attribution — You must give appropriate credit and ShareAlike.
DOI: 10.17632/rp73yg93n8.5
title: Fruits-360 dataset

description: Fruits-360: A dataset of images containing fruits, vegetables, nuts and seeds

Version: 2025.03.26.0

The following fruits, vegetables, nuts and seeds are included: Apples (different varieties: Crimson Snow, Golden, Golden-Red, Granny Smith, Pink Lady, Red, Red Delicious), Apricot, Avocado, Avocado ripe, Banana (Yellow, Red, Lady Finger), Beans, Beetroot Red, Blackberry, Blueberry, Cabbage, Caju seed, Cactus fruit, Cantaloupe (2 varieties), Carambula, Carrot, Cauliflower, Cherimoya, Cherry (different varieties, Rainier), Cherry Wax (Yellow, Red, Black), Chestnut, Clementine, Cocos, Corn (with husk), Cucumber (ripened, regular), Dates, Eggplant, Fig, Ginger Root, Goosberry, Granadilla, Grape (Blue, Pink, White (different varieties)), Grapefruit (Pink, White), Guava, Hazelnut, Huckleberry, Kiwi, Kaki, Kohlrabi, Kumsquats, Lemon (normal, Meyer), Lime, Lychee, Mandarine, Mango (Green, Red), Mangostan, Maracuja, Melon Piel de Sapo, Mulberry, Nectarine (Regular, Flat), Nut (Forest, Pecan), Onion (Red, White), Orange, Papaya, Passion fruit, Peach (different varieties), Pepino, Pear (different varieties, Abate, Forelle, Kaiser, Monster, Red, Stone, Williams), Pepper (Red, Green, Orange, Yellow), Physalis (normal, with Husk), Pineapple (normal, Mini), Pistachio, Pitahaya Red, Plum (different varieties), Pomegranate, Pomelo Sweetie, Potato (Red, Sweet, White), Quince, Rambutan, Raspberry, Redcurrant, Salak, Strawberry (normal, Wedge), Tamarillo, Tangelo, Tomato (different varieties, Maroon, Cherry Red, Yellow, not ripened, Heart), Walnut, Watermelon, Zucchini (green and dark).
Dataset properties

Total number of images: 115499.

Training set size: 86554 images.

Test set size: 28945 images.

Number of classes: 170 (fruits, vegetables, nuts and seeds).

Image size: 100x100 pixels.

Filename format: image_index_100.jpg (e.g. 32_100.jpg) or r_image_index_100.jpg (e.g. r_32_100.jpg) or r2_image_index_100.jpg or r3_image_index_100.jpg. "r" stands for rotated fruit. "r2" means that the fruit was rotated around the 3rd axis. "100" comes from image size (100x100 pixels).

Different varieties of the same fruit (apple for instance) are stored as belonging to different classes.

Repository structure

Folders Training and Test contain images for training and testing purposes.

Alternate download
The Fruits-360 dataset can be downloaded from:

https://www.kaggle.com/moltean/fruits

https://github.com/fruits-360

How to cite
Mihai Oltean, Fruits-360 dataset, 2017-.

License:

C BY-SA 4.0

Copyright (c) 2017-, Mihai Oltean

You are free to: Share and Adapt.

Under the following terms: Attribution — You must give appropriate credit and ShareAlike.