cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.3535/b0q-1tb-q26
title: Machaerium stipitatum Vogel

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/7fw-5n7-vjl
title: Caesalpinia Plum. ex L.

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/dk3-h9k-0pt
title: Lotus corniculatus L.

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/mxz-fg9-edf
title: Geranium pyrenaicum subsp. pyrenaicum

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/cgd-sp3-rsa
title: Myosotis sparsiflora J. C. Mikan ex Pohl

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/zgc-7x4-efd
title: Lamium album L.

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/pxw-qfd-dcz
title: Rhynchocorys orientalis (L.) Benth.

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/6k3-let-7t9
title: Drimys winteri J. R. Forst. & G. Forst.

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/vvg-xwp-rgq
title: Alyssum alyssoides (L.) L.

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/plc-bg6-1xr
title: Trifolium Tourn. ex L.

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/tc0-25r-vph
title: Pyrus takhtadzhianii Fed.

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/mqx-qxz-myd
title: Hyoscyamus niger L.

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/ef1-1z6-cjc
title: Xeranthemum squarrosum Boiss.

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/m63-ds1-9ms
title: Tripleurospermum sevanense (Manden.) Pobed.

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/k43-gm1-t8x
title: Selaginella P. Beauv.

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/yz7-3rn-tp7
title: Vicia abbreviata Fisch. ex Spreng.

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.15468/dl.v39vn2
title: Occurrence Download

description: A dataset containing 4675 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Turdus subalaris)",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "License is one of (CC-BY 4.0, CC0 1.0)"
 ]
}

 The dataset includes 4675 records from 8 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0072780-250717081556266/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.3535/2ta-xkk-rk5
title: Alchemilla languida Buser

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/5v6-3ft-qdp
title: Lamiaceae

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/2h2-lb4-byx
title: Myosotis alpestris F. W. Schmidt

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/71c-f8v-hz4
title: Festuca valesiaca Schleich. ex Gaudin

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/zhn-dht-jhr
title: Drimys winteri J. R. Forst. & G. Forst.

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/99r-ckt-re3
title: Dichodon davuricum (Fisch. ex Spreng.) Á. Löve & D. Löve

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/b2v-sr0-2pa
title: Plantago major L.

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/661-d6a-rdg
title: Alchemilla dura Buser

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/v2x-k02-cd3
title: Sedum L.

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/jex-ghg-1ty
title: Bistorta carnea (K. Koch) Kom.

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/jm3-jtg-bc6
title: Bromus variegatus M.Bieb.

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/0c2-p3a-nec
title: Minuartia hirsuta subsp. oreina Mattf.

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/lws-82r-50c
title: Rhinanthus rumelicus Velen.

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/ls1-n2x-h3l
title: Stellaria L.

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/yhk-ddg-936
title: Poa iberica Fisch., C.A.Mey. & Avé-Lall.

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/2dg-aaw-nyd
title: Lomelosia rotata (M. Bieb.) Greuter & Burdet

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/ekr-l91-5pz
title: Agropyron cristatum (L.) Gaertn.

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/3w2-a2r-zec
title: Astragalus galegiformis L.

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/xbc-rbv-ebe
title: Geranium tuberosum L.

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/vlq-x77-b4a
title: Verbascum L.

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/lgk-zdc-m4s
title: Scutellaria orientalis L.

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/wjc-zem-aa1
title: Sorbus aucuparia L.

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.15468/dl.7vzmbd
title: Occurrence Download

description: A dataset containing 9807 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Turdus unicolor)",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "License is one of (CC-BY 4.0, CC0 1.0)"
 ]
}

 The dataset includes 9807 records from 18 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0072782-250717081556266/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.3535/acj-1gs-nw5
title: Osyris daruma Parsa

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/qet-f8a-536
title: Veronica filiformis Sm.

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/0sb-e67-cjn
title: Vaccinium myrtillus L.

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.5281/zenodo.15853475
title: 【Vision in Action】Beyond Strong Baseline - Training Data

description: 🏁 Beyond Strong Baseline: Multi-UAV Tracking Competition ₊˚⊹

🎯 COMPETITION LINK: Codabench

⬇️ DOWNLOAD: Training Data | Test Data (BB2P_02_corrected) | Sample Submission

📹 VIDEOS: Overview | Training Videos | Test Videos

This project provides the training data for the upcoming multi-UAV tracking evaluation event.

The dataset has been carefully curated from 200 publicly released training videos.

To ensure fairness and minimize the risk of information leakage into the evaluation phase, we:



Renamed, resplit, and resampled the original videos. 

Selected 102 videos to serve as the training data.



Takeoff - UAV launch phase: 1 video.

L - Larger UAV target: 8 videos.

C - Cloud background: 20 videos.

CF - Cloud (Fewer UAVs): 9 videos.

T - Tree background: 34 videos.

TF - Tree (Fewer UAVs): 7 videos.

B - Scene with buildings: 6 videos.

BB1 - Building Background 1: 2 videos.

BB2 - Building Background 2: 9 videos.

BB2P - Building Background 2 (UAV partially out of view): 4 videos.

Landing - UAV landing phase: 2 videos.



Ensured that both the training and test sets are balanced across all scenario types to support robust evaluation.

The total number of frames across training sequences, whether from images or videos, is 77,293.


⚠️ Important Guidelines: Participants must train their models using only this dataset. Using external data may lead to overfitting or unreliable evaluation results.

📁 Folder Structure: The dataset is organized into three folders as below.



.├── TrainImages│       └── B_00│                 ├── 00000.jpg│                 ├── 00001.jpg│                 ├── 00002.jpg│                 └── ...├── TrainLabels│       ├── B_00.txt│       └── ...└── TrainVideos          ├── B_00.mp4          └── ...




📂 Data Format: The data contains:







.mp4: Raw videos for each sequence.


.jpg: Extracted frames from each video.



.txt: Frame-by-frame object annotations in MOT format.



Each .txt file contains annotations in the following format:







frame_id, object_id, x1, y1, w, h, confidence, class, visibility








frame_id: Index of the frame in the video (starting from 1).




object_id: Unique ID assigned to each object across frames.


x1, y1: Top-left coordinates of the bounding box.

w, h: Width and height of the bounding box.

confidence: Confidence score.

class: Integer label for the object class.

visibility: Visibility ratio.



Example:







1,1,330.31,10.11,9.050000000000011,5.59,1,1,1.0

1,2,360.93,13.96,9.370000000000005,5.34,1,1,1.0





🙌 Feel free to reach out in the GitHub Issues section if you have any questions. Let us improve the tracking performance together. Have fun!
DOI: 10.5281/zenodo.15853476
title: 【Vision in Action】Beyond Strong Baseline - Training Data

description: 🏁 Beyond Strong Baseline: Multi-UAV Tracking Competition ₊˚⊹

🎯 COMPETITION LINK: Codabench

⬇️ DOWNLOAD: Training Data | Test Data (BB2P_02_corrected) | Sample Submission

📹 VIDEOS: Overview | Training Videos | Test Videos

This project provides the training data for the upcoming multi-UAV tracking evaluation event.

The dataset has been carefully curated from 200 publicly released training videos.

To ensure fairness and minimize the risk of information leakage into the evaluation phase, we:



Renamed, resplit, and resampled the original videos. 

Selected 102 videos to serve as the training data.



Takeoff - UAV launch phase: 1 video.

L - Larger UAV target: 8 videos.

C - Cloud background: 20 videos.

CF - Cloud (Fewer UAVs): 9 videos.

T - Tree background: 34 videos.

TF - Tree (Fewer UAVs): 7 videos.

B - Scene with buildings: 6 videos.

BB1 - Building Background 1: 2 videos.

BB2 - Building Background 2: 9 videos.

BB2P - Building Background 2 (UAV partially out of view): 4 videos.

Landing - UAV landing phase: 2 videos.



Ensured that both the training and test sets are balanced across all scenario types to support robust evaluation.

The total number of frames across training sequences, whether from images or videos, is 77,293.


⚠️ Important Guidelines: Participants must train their models using only this dataset. Using external data may lead to overfitting or unreliable evaluation results.

📁 Folder Structure: The dataset is organized into three folders as below.



.├── TrainImages│       └── B_00│                 ├── 00000.jpg│                 ├── 00001.jpg│                 ├── 00002.jpg│                 └── ...├── TrainLabels│       ├── B_00.txt│       └── ...└── TrainVideos          ├── B_00.mp4          └── ...




📂 Data Format: The data contains:







.mp4: Raw videos for each sequence.


.jpg: Extracted frames from each video.



.txt: Frame-by-frame object annotations in MOT format.



Each .txt file contains annotations in the following format:







frame_id, object_id, x1, y1, w, h, confidence, class, visibility








frame_id: Index of the frame in the video (starting from 1).




object_id: Unique ID assigned to each object across frames.


x1, y1: Top-left coordinates of the bounding box.

w, h: Width and height of the bounding box.

confidence: Confidence score.

class: Integer label for the object class.

visibility: Visibility ratio.



Example:







1,1,330.31,10.11,9.050000000000011,5.59,1,1,1.0

1,2,360.93,13.96,9.370000000000005,5.34,1,1,1.0





🙌 Feel free to reach out in the GitHub Issues section if you have any questions. Let us improve the tracking performance together. Have fun!
DOI: 10.3535/d5n-50y-0v0
title: Ajuga genevensis L.

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/gyn-883-g25
title: Nepeta nuda L.

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/6bf-7sf-kq6
title: Melilotus Mill.

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/njl-lk4-rfl
title: Nymphaea alba L.

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/bam-d2f-94t
title: Bryonia aspera Steven

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/y2n-sqc-p7r
title: Nepeta betonicifolia C.A.Mey.

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/e11-w5h-zh1
title: Alopecurus L.

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/g5t-vb9-7an
title: Polygala major Jacq.

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.5281/zenodo.16299533
title: 【Vision in Action】Beyond Strong Baseline - Test Data

description: 🏁 Beyond Strong Baseline: Multi-UAV Tracking Competition ₊˚⊹

🎯 COMPETITION LINK: Codabench

⬇️ DOWNLOAD: Training Data | Test Data (BB2P_02_corrected) | Sample Submission

📹 VIDEOS: Overview | Training Videos | Test Videos

This project provides the training data for the upcoming multi-UAV tracking evaluation event.

The dataset has been carefully curated from 200 publicly released training videos.

To ensure fairness and minimize the risk of information leakage into the evaluation phase, we:



Renamed, resplit, and resampled the original videos. 

Selected 98 videos to serve as the training data.



Takeoff - UAV launch phase: 1 video.

L - Larger UAV target: 7 videos.

C - Cloud background: 19 videos.

CF - Cloud (Fewer UAVs): 9 videos.

T - Tree background: 34 videos.

TF - Tree (Fewer UAVs): 7 videos.

B - Scene with buildings: 5 videos.

BB1 - Building Background 1: 2 videos.

BB2 - Building Background 2: 8 videos.

BB2P - Building Background 2 (UAV partially out of view): 4 videos.

Landing - UAV landing phase: 2 videos.



Ensured that both the training and test sets are balanced across all scenario types to support robust evaluation.

The total number of frames across test sequences, whether from images or videos, is 74,538.


⚠️ Important Guidelines: Participants must train their models using only training data. Using external data may lead to overfitting or unreliable evaluation results.

📁 Folder Structure: The dataset is organized into three folders as below.



.├── TestImages│       └── B_00│                 ├── 00000.jpg│                 ├── 00001.jpg│                 ├── 00002.jpg│                 └── ...├── TestLabels_FirstFrameOnly│       ├── B_00.txt│       └── ...└── TestVideos          ├── B_00.mp4          └── ...




📂 Data Format: The data contains:







.mp4: Raw videos for each sequence.


.jpg: Extracted frames from each video.



.txt: Frame-by-frame object annotations in MOT format.



Each .txt file contains annotations in the following format:







frame_id, object_id, x1, y1, w, h, confidence, class, visibility








frame_id: Index of the frame in the video (starting from 1).




object_id: Unique ID assigned to each object across frames.


x1, y1: Top-left coordinates of the bounding box.

w, h: Width and height of the bounding box.

confidence: Confidence score.

class: Integer label for the object class.

visibility: Visibility ratio.



Example:







1,1,191.8,340.0,5.299999999999983,5.300000000000011,1,1,1.0

1,2,202.9,338.0,4.099999999999994,4.300000000000011,1,1,1.0





🙌 Feel free to reach out in the GitHub Issues section if you have any questions. Let us improve the tracking performance together. Have fun!
DOI: 10.3535/g9j-vgt-exn
title: Thymus L.

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/pa7-6q4-4cm
title: Tanacetum aureum (Lam.) Greuter, M. V. Agab. & Wagenitz

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/p4r-66k-1xx
title: Barbarea plantaginea DC.

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/avg-xfd-gln
title: Helianthemum sinuspersicum Gholamian & F. Ghahrem.

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/tmr-kp5-m61
title: Juncus compressus Jacq.

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/tv6-zes-kn0
title: Prunus cerasifera Ehrh.

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.5281/zenodo.16458804
title: 【Vision in Action】Beyond Strong Baseline - Sample Submission

description: 🏁 Beyond Strong Baseline: Multi-UAV Tracking Competition ₊˚⊹

🎯 COMPETITION LINK: Codabench

⬇️ DOWNLOAD: Training Data | Test Data (BB2P_02_corrected) | Sample Submission

📹 VIDEOS: Overview | Training Videos | Test Videos

A sample submission file (submission.zip) is provided to demonstrate the expected folder structure for your submission.





submission.zip

├── B_00.txt

├── B_01.txt

├── ...

├── TF_05.txt

└── TF_06.txt





✅ Submission Checklist









ZIP file is named submission.zip



Exactly 98 .txt files are included (no missing or extra files)

All .txt files follow the correct formatting and field order





No folder structure inside the ZIP (flat layout)





 






Each .txt file must contains annotations in the following format:







frame_id, object_id, x1, y1, w, h, confidence, class, visibility








frame_id: Index of the frame in the video (starting from 1).




object_id: Unique ID assigned to each object across frames.


x1, y1: Top-left coordinates of the bounding box.

w, h: Width and height of the bounding box.

confidence: Confidence score.

class: Integer label for the object class.

visibility: Visibility ratio.



Example:







1,1,191.8,340.0,5.299999999999983,5.300000000000011,1,1,1.0

1,2,202.9,338.0,4.099999999999994,4.300000000000011,1,1,1.0





🙌 Feel free to reach out in the GitHub Issues section if you have any questions. Let us improve the tracking performance together. Have fun!
DOI: 10.5281/zenodo.16458805
title: 【Vision in Action】Beyond Strong Baseline - Sample Submission

description: 🏁 Beyond Strong Baseline: Multi-UAV Tracking Competition ₊˚⊹

🎯 COMPETITION LINK: Codabench

⬇️ DOWNLOAD: Training Data | Test Data (BB2P_02_corrected) | Sample Submission

📹 VIDEOS: Overview | Training Videos | Test Videos

A sample submission file (submission.zip) is provided to demonstrate the expected folder structure for your submission.





submission.zip

├── B_00.txt

├── B_01.txt

├── ...

├── TF_05.txt

└── TF_06.txt





✅ Submission Checklist









ZIP file is named submission.zip



Exactly 98 .txt files are included (no missing or extra files)

All .txt files follow the correct formatting and field order





No folder structure inside the ZIP (flat layout)





 






Each .txt file must contains annotations in the following format:







frame_id, object_id, x1, y1, w, h, confidence, class, visibility








frame_id: Index of the frame in the video (starting from 1).




object_id: Unique ID assigned to each object across frames.


x1, y1: Top-left coordinates of the bounding box.

w, h: Width and height of the bounding box.

confidence: Confidence score.

class: Integer label for the object class.

visibility: Visibility ratio.



Example:







1,1,191.8,340.0,5.299999999999983,5.300000000000011,1,1,1.0

1,2,202.9,338.0,4.099999999999994,4.300000000000011,1,1,1.0





🙌 Feel free to reach out in the GitHub Issues section if you have any questions. Let us improve the tracking performance together. Have fun!
DOI: 10.15468/dl.ddby2m
title: Occurrence Download

description: A dataset containing 1 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Hedychium flavescens",
 "Country is Zambia",
 "HasCoordinate is true"
 ]
}

 The dataset includes 1 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0072785-250717081556266/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.3535/r3x-thq-w61
title: Saxifraga sibirica L.

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.15468/dl.wcy4z3
title: Occurrence Download

description: A dataset listing the 120 species recorded in GBIF matching the query:
{
 "DatasetKey" : [
 "is UK Biodiversity Action Plan Invertebrate Data for Wales"
 ]
}

 The dataset's 120 records were derived from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0072771-250717081556266/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.3535/4g3-80z-rb6
title: Poa L.

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/h1e-909-93q
title: Malanea glabra A.Rich.

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/exb-s9p-09m
title: Ajuga genevensis L.

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/l9b-vst-1rg
title: Forsteronia pubescens A. DC.

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.15468/dl.pvaxzz
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "BasisOfRecord is one of (Human Observation, Machine Observation, Occurrence evidence, Observation)",
 "TaxonKey is one of (Eurycea wilderae)",
 "Country is one of (Åland Islands, Albania, Andorra, Austria, Belarus, Belgium, Bosnia and Herzegovina, Bulgaria, Croatia, Czechia, Denmark, Estonia, Faroe Islands, Finland, France, Germany, Gibraltar, Greece, Guernsey, Holy See, Hungary, Iceland, Ireland, Isle of Man, Italy, Jersey, Latvia, Liechtenstein, Lithuania, Luxembourg, Malta, Moldova, Republic of, Monaco, Montenegro, Netherlands, North Macedonia, Norway, Poland, Portugal, Romania, Russian Federation, San Marino, Serbia, Slovakia, Slovenia, Spain, Svalbard and Jan Mayen, Sweden, Switzerland, Ukraine, United Kingdom of Great Britain and Northern Ireland)"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0072783-250717081556266/datasets/export for details.
DOI: 10.3535/f1n-nqd-2zg
title: Juncus atratus Krock.

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/p4n-ssc-tgq
title: Swartzia linharensis Mansano

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/m04-5x6-1j2
title: Scirpus sylvaticus L.

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/td8-5bx-wrb
title: Polygonum cognatum Meisn.

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/1g7-7t2-qd6
title: Medicago lupulina L.

description: Digital Specimen for the physical specimen hosted at University of Graz.