cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.3535/x7q-elr-pqq
title: Juncus filiformis L.

description: Digital Specimen for the physical specimen hosted at Natural History Museum Vienna.
DOI: 10.13140/rg.2.2.20135.57760
title: ICRA 2020 Virtual Conference Presentation Video-2740
DOI: 10.3535/7bc-80x-e96
title: Fagonia arabica var. arabica L.

description: Digital Specimen for the physical specimen hosted at Natural History Museum Vienna.
DOI: 10.3535/h7e-85w-ah5
title: Lamiastrum flavidum (F. Herm.) Ehrend.

description: Digital Specimen for the physical specimen hosted at Natural History Museum Vienna.
DOI: 10.13140/rg.2.2.16989.84966
title: Habitats in transact 20200624_036_TZ
DOI: 10.13140/rg.2.2.29782.47683
title: Centre for the Rehabilitation of the Paralysed (Banglapedia, National Encyclopedia of Bangladesh)
DOI: 10.13140/rg.2.2.33976.78085
title: Announcement of the Webinar "Landscape of Kashmir Shaivism", organised by the Ishwar Ashram Trust (Bangalore)
DOI: 10.3535/76j-ws9-dpr
title: Corydalis pumila (Host) Rchb.

description: Digital Specimen for the physical specimen hosted at Natural History Museum Vienna.
DOI: 10.3535/98y-h52-k0c
title: Gnaphalium uliginosum L.

description: Digital Specimen for the physical specimen hosted at Natural History Museum Vienna.
DOI: 10.3535/b78-74f-rww
title: Kickxia acerbiana (Boiss.) Täckh. & Boulos

description: Digital Specimen for the physical specimen hosted at Natural History Museum Vienna.
DOI: 10.3535/nmh-6f0-mdd
title: Atriplex oblongifolia Waldst. & Kit.

description: Digital Specimen for the physical specimen hosted at Natural History Museum Vienna.
DOI: 10.3535/8vg-7rh-15t
title: Chenopodium chenopodioides (L.) Aellen

description: Digital Specimen for the physical specimen hosted at Natural History Museum Vienna.
DOI: 10.3535/ejs-k6f-acp
title: Ephedra dahurica Turcz.

description: Digital Specimen for the physical specimen hosted at Natural History Museum Vienna.
DOI: 10.3535/c2r-zes-bhg
title: Amaranthus hypochondriacus L.

description: Digital Specimen for the physical specimen hosted at Natural History Museum Vienna.
DOI: 10.3535/k60-qxp-j2y
title: Arabis sagittata (Bertol.) DC.

description: Digital Specimen for the physical specimen hosted at Natural History Museum Vienna.
DOI: 10.3535/nqt-wnn-dez
title: Veronica L.

description: Digital Specimen for the physical specimen hosted at Natural History Museum Vienna.
DOI: 10.3535/avd-yp1-7a7
title: Galium pseudorivale Tzvelev

description: Digital Specimen for the physical specimen hosted at Natural History Museum Vienna.
DOI: 10.3535/nts-vtw-jwf
title: Didesmus aegyptius (L.) Desv.

description: Digital Specimen for the physical specimen hosted at Natural History Museum Vienna.
DOI: 10.3535/vam-pas-5x9
title: Amaranthus hybridus L.

description: Digital Specimen for the physical specimen hosted at Natural History Museum Vienna.
DOI: 10.13140/rg.2.2.20528.79364
title: Front End C++ code of camera PID controller
DOI: 10.3535/2vz-29m-sn1
title: Fagonia arabica var. arabica L.

description: Digital Specimen for the physical specimen hosted at Natural History Museum Vienna.
DOI: 10.3535/3xq-6d4-e6r
title: Chenopodium ficifolium Sm.

description: Digital Specimen for the physical specimen hosted at Natural History Museum Vienna.
DOI: 10.3535/fg0-7gf-ptq
title: Minuartia laricifolia (L.) Schinz & Thell.

description: Digital Specimen for the physical specimen hosted at Natural History Museum Vienna.
DOI: 10.3535/08f-ryv-rzr
title: Diphasiastrum alpinum (L.) Holub

description: Digital Specimen for the physical specimen hosted at Natural History Museum Vienna.
DOI: 10.3535/ge4-e0v-0xy
title: Salvadora persica L.

description: Digital Specimen for the physical specimen hosted at Natural History Museum Vienna.
DOI: 10.3535/x7r-3ty-5c7
title: Kohautia caespitosa subsp. caespitosa Schnizl.

description: Digital Specimen for the physical specimen hosted at Natural History Museum Vienna.
DOI: 10.3535/1xw-j5t-w9b
title: Nitraria retusa (Forssk.) Asch.

description: Digital Specimen for the physical specimen hosted at Natural History Museum Vienna.
DOI: 10.3535/95d-jha-5yz
title: Chenopodium ficifolium Sm.

description: Digital Specimen for the physical specimen hosted at Natural History Museum Vienna.
DOI: 10.3535/jyc-j2e-ax6
title: Erysimum hajastanicum Wissjul. & Bordz.

description: Digital Specimen for the physical specimen hosted at Natural History Museum Vienna.
DOI: 10.3535/fa5-0rz-qsy
title: Erysimum insubricum Peccenini & Polatschek

description: Digital Specimen for the physical specimen hosted at Natural History Museum Vienna.
DOI: 10.3535/hzv-ld6-zvt
title: Ranunculus L.

description: Digital Specimen for the physical specimen hosted at Natural History Museum Vienna.
DOI: 10.3535/mbg-9ej-74n
title: Dracocephalum peregrinum L.

description: Digital Specimen for the physical specimen hosted at Natural History Museum Vienna.
DOI: 10.3535/waz-vxt-v2x
title: Pulmonaria officinalis L.

description: Digital Specimen for the physical specimen hosted at Natural History Museum Vienna.
DOI: 10.3535/3gv-ker-se6
title: Fagonia arabica var. arabica L.

description: Digital Specimen for the physical specimen hosted at Natural History Museum Vienna.
DOI: 10.3535/zs5-lel-j6f
title: Chenopodium chenopodioides (L.) Aellen

description: Digital Specimen for the physical specimen hosted at Natural History Museum Vienna.
DOI: 10.13140/rg.2.2.13241.19041
title: Actuator Model for Spacecraft Attitude Control Simulation
DOI: 10.3535/423-6yq-0kz
title: Myricaria bracteata Royle

description: Digital Specimen for the physical specimen hosted at Natural History Museum Vienna.
DOI: 10.3535/4n5-slt-txq
title: Amethystea coerulea L.

description: Digital Specimen for the physical specimen hosted at Natural History Museum Vienna.
DOI: 10.3535/hqa-bhd-4j4
title: Adenophora liliifolia (L.) Ledeb. ex A. DC.

description: Digital Specimen for the physical specimen hosted at Natural History Museum Vienna.
DOI: 10.3535/2y3-7mz-rkf
title: Chenopodium ficifolium Sm.

description: Digital Specimen for the physical specimen hosted at Natural History Museum Vienna.
DOI: 10.3535/3gv-qzk-srn
title: Amaranthus retroflexus L.

description: Digital Specimen for the physical specimen hosted at Natural History Museum Vienna.
DOI: 10.3535/ynm-xa8-4dk
title: Cenolophium denudatum (Hornem.) Tutin

description: Digital Specimen for the physical specimen hosted at Natural History Museum Vienna.
DOI: 10.13140/rg.2.2.14414.28480
title: Reviewer STATUS GIZI BALITA (Studi Analitik pada Balita di Wilayah Kerja Puskesmas Waigete Kabupaten Sikka Provinsi Nusa Tenggara Timur)
DOI: 10.3535/5tk-qpc-nk9
title: Selaginella borealis (Kaulf.) Rupr.

description: Digital Specimen for the physical specimen hosted at Natural History Museum Vienna.
DOI: 10.3535/7nf-z2c-xyy
title: Amaranthus retroflexus L.

description: Digital Specimen for the physical specimen hosted at Natural History Museum Vienna.
DOI: 10.3535/esp-7zs-0va
title: Linaria altaica Fisch. ex Ledeb.

description: Digital Specimen for the physical specimen hosted at Natural History Museum Vienna.
DOI: 10.3535/7bh-whf-5dr
title: Euphorbia nicaeënsis All.

description: Digital Specimen for the physical specimen hosted at Natural History Museum Vienna.
DOI: 10.3535/llx-j0h-hk7
title: Amaranthus powellii S. Watson

description: Digital Specimen for the physical specimen hosted at Natural History Museum Vienna.
DOI: 10.3535/xf8-7c9-a46
title: Molinia caerulea (L.) Moench

description: Digital Specimen for the physical specimen hosted at Natural History Museum Vienna.
DOI: 10.15468/dl.694afv
title: Occurrence Download

description: A dataset containing 290 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Melaleuca cruenta Craven & R.D.Edwards)",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "HasGeospatialIssue is false",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Specimen)"
 ]
 }
 }
 ]
}

 The dataset includes 290 records from 13 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0037039-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.7q5byy
title: Occurrence Download

description: A dataset containing 4118 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Tradescantia zebrina Bosse",
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 },
 {
 "or" : [
 "CoordinateUncertaintyInMeters is less than 10000",
 "CoordinateUncertaintyInMeters is null"
 ]
 }
 ]
}

 The dataset includes 4118 records from 196 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0037040-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.wzj45r
title: Occurrence Download

description: A dataset listing the 228 species recorded in GBIF matching the query:
{
 "and" : [
 "Country is Colombia",
 "OccurrenceStatus is Present",
 "TaxonKey is Acrididae"
 ]
}

 The dataset's 228 records were derived from 73 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0037028-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.rsrveq
title: Occurrence Download

description: A dataset containing 68 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Melaleuca glauca Domin)",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "HasGeospatialIssue is false",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Specimen)"
 ]
 }
 }
 ]
}

 The dataset includes 68 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0037043-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.xvtqs2
title: Occurrence Download

description: A dataset containing 21 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Melaleuca hislopii Craven & R.D.Edwards)",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "HasGeospatialIssue is false",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Specimen)"
 ]
 }
 }
 ]
}

 The dataset includes 21 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0037045-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.8ncuqm
title: Occurrence Download

description: A dataset containing 2153 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Ecuador",
 "TaxonKey is Dasypus novemcinctus Linnaeus, 1758"
 ]
}

 The dataset includes 2153 records from 21 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0037044-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.2t2hem
title: Occurrence Download

description: A dataset containing 42 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Melaleuca huegelii subsp. huegelii)",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "HasGeospatialIssue is false",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Specimen)"
 ]
 }
 }
 ]
}

 The dataset includes 42 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0037046-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.12179883
title: ADD 2023 Challenge Track 3 Evaluation Dataset

description: Audio deepfake detection is an emerging topic in the artificial intelligence community. The second Audio Deepfake Detection Challenge (ADD 2023) aims to spur researchers around the world to build new innovative technologies that can further accelerate and foster research on detecting and analyzing deepfake speech utterances. Different from previous challenges (e.g. ADD 2022), ADD 2023 focuses on surpassing the constraints of binary real/fake classification, and actually localizing the manipulated intervals in a partially fake speech as well as pinpointing the source responsible for generating any fake audio. Furthermore, ADD 2023 includes more rounds of evaluation for the fake audio game sub-challenge. The ADD 2023 challenge (http://addchallenge.cn/add2023) includes three subchallenges: audio fake game (FG), manipulation region location (RL) and deepfake algorithm recognition (AR). This paper describes the datasets, evaluation metrics, and protocols. Some findings are also reported in audio deepfake detection tasks.


The ADD 2023 dataset is publicly available.


This data set is licensed with a CC BY-NC-ND 4.0 license.


If you use this dataset, please cite the following paper:



Jiangyan Yi, Jianhua Tao, Ruibo Fu, Xinrui Yan, Chenglong Wang, Tao Wang, Chu Yuan Zhang, Xiaohui Zhang, Yan Zhao, Yong Ren, Le Xu, Junzuo Zhou, Hao Gu, Zhengqi Wen, Shan Liang, Zheng Lian, Shuai Nie, Haizhou Li: ADD 2023: the Second Audio Deepfake Detection Challenge. DADA@IJCAI 2023: 125-130
DOI: 10.5281/zenodo.12179884
title: ADD 2023 Challenge Track 3 Evaluation Dataset

description: Audio deepfake detection is an emerging topic in the artificial intelligence community. The second Audio Deepfake Detection Challenge (ADD 2023) aims to spur researchers around the world to build new innovative technologies that can further accelerate and foster research on detecting and analyzing deepfake speech utterances. Different from previous challenges (e.g. ADD 2022), ADD 2023 focuses on surpassing the constraints of binary real/fake classification, and actually localizing the manipulated intervals in a partially fake speech as well as pinpointing the source responsible for generating any fake audio. Furthermore, ADD 2023 includes more rounds of evaluation for the fake audio game sub-challenge. The ADD 2023 challenge (http://addchallenge.cn/add2023) includes three subchallenges: audio fake game (FG), manipulation region location (RL) and deepfake algorithm recognition (AR). This paper describes the datasets, evaluation metrics, and protocols. Some findings are also reported in audio deepfake detection tasks.


The ADD 2023 dataset is publicly available.


This data set is licensed with a CC BY-NC-ND 4.0 license.


If you use this dataset, please cite the following paper:



Jiangyan Yi, Jianhua Tao, Ruibo Fu, Xinrui Yan, Chenglong Wang, Tao Wang, Chu Yuan Zhang, Xiaohui Zhang, Yan Zhao, Yong Ren, Le Xu, Junzuo Zhou, Hao Gu, Zhengqi Wen, Shan Liang, Zheng Lian, Shuai Nie, Haizhou Li: ADD 2023: the Second Audio Deepfake Detection Challenge. DADA@IJCAI 2023: 125-130
DOI: 10.5281/zenodo.12176325
title: ADD 2023 Challenge Track 1.2 Evaluation Dataset (Round 2)

description: Audio deepfake detection is an emerging topic in the artificial intelligence community. The second Audio Deepfake Detection Challenge (ADD 2023) aims to spur researchers around the world to build new innovative technologies that can further accelerate and foster research on detecting and analyzing deepfake speech utterances. Different from previous challenges (e.g. ADD 2022), ADD 2023 focuses on surpassing the constraints of binary real/fake classification, and actually localizing the manipulated intervals in a partially fake speech as well as pinpointing the source responsible for generating any fake audio. Furthermore, ADD 2023 includes more rounds of evaluation for the fake audio game sub-challenge. The ADD 2023 challenge (http://addchallenge.cn/add2023) includes three subchallenges: audio fake game (FG), manipulation region location (RL) and deepfake algorithm recognition (AR). This paper describes the datasets, evaluation metrics, and protocols. Some findings are also reported in audio deepfake detection tasks.


The ADD 2023 dataset is publicly available.


This data set is licensed with a CC BY-NC-ND 4.0 license.


If you use this dataset, please cite the following paper:



Jiangyan Yi, Jianhua Tao, Ruibo Fu, Xinrui Yan, Chenglong Wang, Tao Wang, Chu Yuan Zhang, Xiaohui Zhang, Yan Zhao, Yong Ren, Le Xu, Junzuo Zhou, Hao Gu, Zhengqi Wen, Shan Liang, Zheng Lian, Shuai Nie, Haizhou Li: ADD 2023: the Second Audio Deepfake Detection Challenge. DADA@IJCAI 2023: 125-130
DOI: 10.5281/zenodo.12176326
title: ADD 2023 Challenge Track 1.2 Evaluation Dataset (Round 2)

description: Audio deepfake detection is an emerging topic in the artificial intelligence community. The second Audio Deepfake Detection Challenge (ADD 2023) aims to spur researchers around the world to build new innovative technologies that can further accelerate and foster research on detecting and analyzing deepfake speech utterances. Different from previous challenges (e.g. ADD 2022), ADD 2023 focuses on surpassing the constraints of binary real/fake classification, and actually localizing the manipulated intervals in a partially fake speech as well as pinpointing the source responsible for generating any fake audio. Furthermore, ADD 2023 includes more rounds of evaluation for the fake audio game sub-challenge. The ADD 2023 challenge (http://addchallenge.cn/add2023) includes three subchallenges: audio fake game (FG), manipulation region location (RL) and deepfake algorithm recognition (AR). This paper describes the datasets, evaluation metrics, and protocols. Some findings are also reported in audio deepfake detection tasks.


The ADD 2023 dataset is publicly available.


This data set is licensed with a CC BY-NC-ND 4.0 license.


If you use this dataset, please cite the following paper:



Jiangyan Yi, Jianhua Tao, Ruibo Fu, Xinrui Yan, Chenglong Wang, Tao Wang, Chu Yuan Zhang, Xiaohui Zhang, Yan Zhao, Yong Ren, Le Xu, Junzuo Zhou, Hao Gu, Zhengqi Wen, Shan Liang, Zheng Lian, Shuai Nie, Haizhou Li: ADD 2023: the Second Audio Deepfake Detection Challenge. DADA@IJCAI 2023: 125-130
DOI: 10.5281/zenodo.12176529
title: ADD 2023 Challenge Track 2 Training/Development Dataset

description: Audio deepfake detection is an emerging topic in the artificial intelligence community. The second Audio Deepfake Detection Challenge (ADD 2023) aims to spur researchers around the world to build new innovative technologies that can further accelerate and foster research on detecting and analyzing deepfake speech utterances. Different from previous challenges (e.g. ADD 2022), ADD 2023 focuses on surpassing the constraints of binary real/fake classification, and actually localizing the manipulated intervals in a partially fake speech as well as pinpointing the source responsible for generating any fake audio. Furthermore, ADD 2023 includes more rounds of evaluation for the fake audio game sub-challenge. The ADD 2023 challenge (http://addchallenge.cn/add2023) includes three subchallenges: audio fake game (FG), manipulation region location (RL) and deepfake algorithm recognition (AR). This paper describes the datasets, evaluation metrics, and protocols. Some findings are also reported in audio deepfake detection tasks.


The ADD 2023 dataset is publicly available.


This data set is licensed with a CC BY-NC-ND 4.0 license.


If you use this dataset, please cite the following paper:



Jiangyan Yi, Jianhua Tao, Ruibo Fu, Xinrui Yan, Chenglong Wang, Tao Wang, Chu Yuan Zhang, Xiaohui Zhang, Yan Zhao, Yong Ren, Le Xu, Junzuo Zhou, Hao Gu, Zhengqi Wen, Shan Liang, Zheng Lian, Shuai Nie, Haizhou Li: ADD 2023: the Second Audio Deepfake Detection Challenge. DADA@IJCAI 2023: 125-130
DOI: 10.5281/zenodo.12176530
title: ADD 2023 Challenge Track 2 Training/Development Dataset

description: Audio deepfake detection is an emerging topic in the artificial intelligence community. The second Audio Deepfake Detection Challenge (ADD 2023) aims to spur researchers around the world to build new innovative technologies that can further accelerate and foster research on detecting and analyzing deepfake speech utterances. Different from previous challenges (e.g. ADD 2022), ADD 2023 focuses on surpassing the constraints of binary real/fake classification, and actually localizing the manipulated intervals in a partially fake speech as well as pinpointing the source responsible for generating any fake audio. Furthermore, ADD 2023 includes more rounds of evaluation for the fake audio game sub-challenge. The ADD 2023 challenge (http://addchallenge.cn/add2023) includes three subchallenges: audio fake game (FG), manipulation region location (RL) and deepfake algorithm recognition (AR). This paper describes the datasets, evaluation metrics, and protocols. Some findings are also reported in audio deepfake detection tasks.


The ADD 2023 dataset is publicly available.


This data set is licensed with a CC BY-NC-ND 4.0 license.


If you use this dataset, please cite the following paper:



Jiangyan Yi, Jianhua Tao, Ruibo Fu, Xinrui Yan, Chenglong Wang, Tao Wang, Chu Yuan Zhang, Xiaohui Zhang, Yan Zhao, Yong Ren, Le Xu, Junzuo Zhou, Hao Gu, Zhengqi Wen, Shan Liang, Zheng Lian, Shuai Nie, Haizhou Li: ADD 2023: the Second Audio Deepfake Detection Challenge. DADA@IJCAI 2023: 125-130
DOI: 10.5281/zenodo.12176903
title: ADD 2023 Challenge Track 2 Evaluation Dataset

description: Audio deepfake detection is an emerging topic in the artificial intelligence community. The second Audio Deepfake Detection Challenge (ADD 2023) aims to spur researchers around the world to build new innovative technologies that can further accelerate and foster research on detecting and analyzing deepfake speech utterances. Different from previous challenges (e.g. ADD 2022), ADD 2023 focuses on surpassing the constraints of binary real/fake classification, and actually localizing the manipulated intervals in a partially fake speech as well as pinpointing the source responsible for generating any fake audio. Furthermore, ADD 2023 includes more rounds of evaluation for the fake audio game sub-challenge. The ADD 2023 challenge (http://addchallenge.cn/add2023) includes three subchallenges: audio fake game (FG), manipulation region location (RL) and deepfake algorithm recognition (AR). This paper describes the datasets, evaluation metrics, and protocols. Some findings are also reported in audio deepfake detection tasks.


The ADD 2023 dataset is publicly available.


This data set is licensed with a CC BY-NC-ND 4.0 license.


If you use this dataset, please cite the following paper:



Jiangyan Yi, Jianhua Tao, Ruibo Fu, Xinrui Yan, Chenglong Wang, Tao Wang, Chu Yuan Zhang, Xiaohui Zhang, Yan Zhao, Yong Ren, Le Xu, Junzuo Zhou, Hao Gu, Zhengqi Wen, Shan Liang, Zheng Lian, Shuai Nie, Haizhou Li: ADD 2023: the Second Audio Deepfake Detection Challenge. DADA@IJCAI 2023: 125-130