cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.7937978
title: Pixel-wise Gaussian AD visualization (ResNet18, MVTecAD)

description: A multivariate Gaussian model is fitted with the pixel-wise feature vectors [1] (all pixel positions confounded) extracted from a pre-trained convolutional neural network using the maximum likelihood estimator (empirical mean and empirical covariance matrix). From the eigendecomposition of the empirical covariance matrix, a whitening transformation is applied to the feature vectors, which yields a new vector of the same number of "components" (cf. [2]). This dataset shows visualizations of the component maps (cf. [2]) of all the categories in the MVTec-AD dataset. All the layer blocks [3] from a ResNet18 [4] are used as feature map extractors for the model described above. Each combination of category and layer is trained separately. The visualizations are composed of heatmaps of the square of the component maps; their sum (the Mahalanobis distance of each pixel, yielding an anomaly score map), and (for images containing defects, a.k.a. "anomalies") the ground truth annotation provided in the MVTec-AD dataset. For more details, refer to our paper. --- [1] Pixel-wise feature vectors: given a stacked feature map of a 2D image (i.e. multiple 2D images, or "channels," containing information about the 2D input image), extract the values of all channels for a single pixel position. [2] The axes of the whitened [feature] vectors are referred to as "components" instead of "features" as a reminder that they come from a projection of the feature vectors along the eigenvectors, or eigen-<em>components</em>, of the covariance matrix. As the whitened vectors are in the same 2D grid structure as their original feature maps, we refer to them as "component maps." [3] "layer1", "layer2", "layer3", "layer4". [4] From torchvision version "0.15.2", model weights "ResNet18_Weights.IMAGENET1K_V1". TODO ref to paper
DOI: 10.5281/zenodo.7937977
title: Pixel-wise Gaussian AD visualization (ResNet18, MVTecAD)

description: A multivariate Gaussian model is fitted with the pixel-wise feature vectors [1] (all pixel positions confounded) extracted from a pre-trained convolutional neural network using the maximum likelihood estimator (empirical mean and empirical covariance matrix). From the eigendecomposition of the empirical covariance matrix, a whitening transformation is applied to the feature vectors, which yields a new vector of the same number of "components" (cf. [2]). This dataset shows visualizations of the component maps (cf. [2]) of all the categories in the MVTec-AD dataset. All the layer blocks [3] from a ResNet18 [4] are used as feature map extractors for the model described above. Each combination of category and layer is trained separately. The visualizations are composed of heatmaps of the square of the component maps; their sum (the Mahalanobis distance of each pixel, yielding an anomaly score map), and (for images containing defects, a.k.a. "anomalies") the ground truth annotation provided in the MVTec-AD dataset. For more details, refer to our paper. --- [1] Pixel-wise feature vectors: given a stacked feature map of a 2D image (i.e. multiple 2D images, or "channels," containing information about the 2D input image), extract the values of all channels for a single pixel position. [2] The axes of the whitened [feature] vectors are referred to as "components" instead of "features" as a reminder that they come from a projection of the feature vectors along the eigenvectors, or eigen-<em>components</em>, of the covariance matrix. As the whitened vectors are in the same 2D grid structure as their original feature maps, we refer to them as "component maps." [3] "layer1", "layer2", "layer3", "layer4". [4] From torchvision version "0.15.2", model weights "ResNet18_Weights.IMAGENET1K_V1". TODO ref to paper
DOI: 10.5281/zenodo.7270734
title: BIO4AFRICA_Survey Data Uganda - Analysis of the needs and contexts of target farmers and rural communities with a gender lens_D1.1_311022_1

description: The results of this survey support the identification of the needs, challenges, and context of target farmers and rural communities and how, why and under which circumstances the social, economic, regulatory, institutional, market and political circumstances could act as a barrier or an enabler for the uptake of bio-based solutions.
DOI: 10.5281/zenodo.7270733
title: BIO4AFRICA_Survey Data Uganda - Analysis of the needs and contexts of target farmers and rural communities with a gender lens_D1.1_311022_1

description: The results of this survey support the identification of the needs, challenges, and context of target farmers and rural communities and how, why and under which circumstances the social, economic, regulatory, institutional, market and political circumstances could act as a barrier or an enabler for the uptake of bio-based solutions.
DOI: 10.5281/zenodo.7270626
title: BIO4AFRICA_Survey Data Ivory Coast - Analysis of the needs and contexts of target farmers and rural communities with a gender lens_D1.1_311022_1

description: The results of this survey support the identification of the needs, challenges, and context of target farmers and rural communities and how, why and under which circumstances the social, economic, regulatory, institutional, market and political circumstances could act as a barrier or an enabler for the uptake of bio-based solutions.
DOI: 10.5281/zenodo.7270625
title: BIO4AFRICA_Survey Data Ivory Coast - Analysis of the needs and contexts of target farmers and rural communities with a gender lens_D1.1_311022_1

description: The results of this survey support the identification of the needs, challenges, and context of target farmers and rural communities and how, why and under which circumstances the social, economic, regulatory, institutional, market and political circumstances could act as a barrier or an enabler for the uptake of bio-based solutions.
DOI: 10.48567/xzy6-vs23
title: Marble Point Automatic Weather Station, 1994 quality-controlled observational data.
DOI: 10.48567/dgft-vv21
title: Marble Point Automatic Weather Station, 1995 quality-controlled observational data.
DOI: 10.48567/4bfp-3j29
title: Racer Rock Automatic Weather Station, 2004 quality-controlled observational data.
DOI: 10.5281/zenodo.7274016
title: BIO4AFRICA_Co-definition of technologies to be transferred with local farmers and communities - Technology Validation Data (Findings)_D1.4_021122_1

description: Validation Data (Findings) for Task 1.4: Co-definition of technologies to be transferred with local farmers and communities.
DOI: 10.5281/zenodo.7274015
title: BIO4AFRICA_Co-definition of technologies to be transferred with local farmers and communities - Technology Validation Data (Findings)_D1.4_021122_1

description: Validation Data (Findings) for Task 1.4: Co-definition of technologies to be transferred with local farmers and communities.
DOI: 10.5517/ccdc.csd.cc29gd5c
title: CCDC 2128992: Experimental Crystal Structure Determination

description: Related Article: Aneta Baj, Nirawit Kaewnok, Juan A. Rivas-Loaiza, Magdalena Szymańska, Stanisław Witkowski, Agnieszka Wojtkielewicz, Jacek W. Morzycki|2023|Chem.-Eur.J.|29|e202203314|doi:10.1002/chem.202203314
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc29gd6d
title: CCDC 2128993: Experimental Crystal Structure Determination

description: Related Article: Aneta Baj, Nirawit Kaewnok, Juan A. Rivas-Loaiza, Magdalena Szymańska, Stanisław Witkowski, Agnieszka Wojtkielewicz, Jacek W. Morzycki|2023|Chem.-Eur.J.|29|e202203314|doi:10.1002/chem.202203314
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2b0sw1
title: CCDC 2145723: Experimental Crystal Structure Determination

description: Related Article: Ina Michalsky, Viktoria Gensch, Christian Walla, Marvin Hoffmann, Frank Rominger, Thomas Oeser, Petra Tegeder, Andreas Dreuw, Milan Kivala|2022|Chem.-Eur.J.|28|e202200326|doi:10.1002/chem.202200326
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2b0sx2
title: CCDC 2145724: Experimental Crystal Structure Determination

description: Related Article: Ina Michalsky, Viktoria Gensch, Christian Walla, Marvin Hoffmann, Frank Rominger, Thomas Oeser, Petra Tegeder, Andreas Dreuw, Milan Kivala|2022|Chem.-Eur.J.|28|e202200326|doi:10.1002/chem.202200326
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2b0sy3
title: CCDC 2145725: Experimental Crystal Structure Determination

description: Related Article: Ina Michalsky, Viktoria Gensch, Christian Walla, Marvin Hoffmann, Frank Rominger, Thomas Oeser, Petra Tegeder, Andreas Dreuw, Milan Kivala|2022|Chem.-Eur.J.|28|e202200326|doi:10.1002/chem.202200326
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2b0sz4
title: CCDC 2145726: Experimental Crystal Structure Determination

description: Related Article: Ina Michalsky, Viktoria Gensch, Christian Walla, Marvin Hoffmann, Frank Rominger, Thomas Oeser, Petra Tegeder, Andreas Dreuw, Milan Kivala|2022|Chem.-Eur.J.|28|e202200326|doi:10.1002/chem.202200326
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2b0t06
title: CCDC 2145727: Experimental Crystal Structure Determination

description: Related Article: Ina Michalsky, Viktoria Gensch, Christian Walla, Marvin Hoffmann, Frank Rominger, Thomas Oeser, Petra Tegeder, Andreas Dreuw, Milan Kivala|2022|Chem.-Eur.J.|28|e202200326|doi:10.1002/chem.202200326
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2b0t17
title: CCDC 2145728: Experimental Crystal Structure Determination

description: Related Article: Ina Michalsky, Viktoria Gensch, Christian Walla, Marvin Hoffmann, Frank Rominger, Thomas Oeser, Petra Tegeder, Andreas Dreuw, Milan Kivala|2022|Chem.-Eur.J.|28|e202200326|doi:10.1002/chem.202200326
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2b0t28
title: CCDC 2145729: Experimental Crystal Structure Determination

description: Related Article: Ina Michalsky, Viktoria Gensch, Christian Walla, Marvin Hoffmann, Frank Rominger, Thomas Oeser, Petra Tegeder, Andreas Dreuw, Milan Kivala|2022|Chem.-Eur.J.|28|e202200326|doi:10.1002/chem.202200326
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2b0t39
title: CCDC 2145730: Experimental Crystal Structure Determination

description: Related Article: Ina Michalsky, Viktoria Gensch, Christian Walla, Marvin Hoffmann, Frank Rominger, Thomas Oeser, Petra Tegeder, Andreas Dreuw, Milan Kivala|2022|Chem.-Eur.J.|28|e202200326|doi:10.1002/chem.202200326
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2b0t4b
title: CCDC 2145731: Experimental Crystal Structure Determination

description: Related Article: Ina Michalsky, Viktoria Gensch, Christian Walla, Marvin Hoffmann, Frank Rominger, Thomas Oeser, Petra Tegeder, Andreas Dreuw, Milan Kivala|2022|Chem.-Eur.J.|28|e202200326|doi:10.1002/chem.202200326
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc28zh3w
title: CCDC 2114668: Experimental Crystal Structure Determination

description: Related Article: Jan Schulz, Menyhárt B. Sárosi, Evamarie Hey-Hawkins|2022|Chem.-Eur.J.|28|e202200531|doi:10.1002/chem.202200531
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc28zhsk
title: CCDC 2114689: Experimental Crystal Structure Determination

description: Related Article: Jan Schulz, Menyhárt B. Sárosi, Evamarie Hey-Hawkins|2022|Chem.-Eur.J.|28|e202200531|doi:10.1002/chem.202200531
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc28zvty
title: CCDC 2115031: Experimental Crystal Structure Determination

description: Related Article: Jan Schulz, Menyhárt B. Sárosi, Evamarie Hey-Hawkins|2022|Chem.-Eur.J.|28|e202200531|doi:10.1002/chem.202200531
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.25824/redu/7djsio
title: FORMULÁRIO TCC (respostas).xlsx
DOI: 10.25824/redu/kniryu
title: Provision of contraceptives by brazilian general gynaecologists: a nationwide online survey

description: Banco de dados referente ao artigo Provision of contraceptives by Brazilian general gynaecologists: a nationwide online survey
DOI: 10.25824/redu/9l0zus
title: ParesIdade19 (2) com motivo corrigido codigos novos.xlsx
DOI: 10.25824/redu/bpggn7
title: Expulsion and continuation rates of the 52 mg levonorgestrel intrauterine system in adolescents and adult women

description: Dados referentes ao artigo Expulsion and continuation rates of the 52 mg levonorgestrel intrauterine system in adolescents and adult women enviado ao jornal.
DOI: 10.6084/m9.figshare.22822433
title: Just Dance shorthen properties

description: <em>Dataset containing comments and metadata information for multilabel predictions for different properties of comments.</em><br> <br> <em>The data has 216193 comments make on the just dance YouTube videos. It has metadata information about the date the</em><br> <em>comment was written and the number of "likes" it got. It also has</em><br> <em>42 multilabel binary target label columns,</em><br> <em>referring to the category classification of the comment.</em><br> <br> <em>This dataset is a modification of Just Dance @ YouTube dataset curated by the COIMBRA university,</em><br> <em>For additional details about the dataset, please refer to the original source:</em><br> <em>https://www.kaggle.com/datasets/renatojmsantos/just-dance-on-youtube.</em><br> <em>Dataset used under the following license: https://creativecommons.org/licenses/by/4.0/</em><br> <br> <em>Original publication:</em><br> <em>R. Santos, J. P. Arrais and P. A. Silva, "Analysing Games for Health through Users' Opinion Mining,"</em><br> <em>2021 IEEE 34th International Symposium on Computer-Based Medical Systems (CBMS), Aveiro, Portugal, 2021, pp. 319-323,</em><br> <em>doi: 10.1109/CBMS52027.2021.00035.</em>
DOI: 10.6084/m9.figshare.22822433.v3
title: Just Dance shorthen properties

description: <em>Dataset containing comments and metadata information for multilabel predictions for different properties of comments.</em><br> <br> <em>The data has 216193 comments make on the just dance YouTube videos. It has metadata information about the date the</em><br> <em>comment was written and the number of "likes" it got. It also has</em><br> <em>42 multilabel binary target label columns,</em><br> <em>referring to the category classification of the comment.</em><br> <br> <em>This dataset is a modification of Just Dance @ YouTube dataset curated by the COIMBRA university,</em><br> <em>For additional details about the dataset, please refer to the original source:</em><br> <em>https://www.kaggle.com/datasets/renatojmsantos/just-dance-on-youtube.</em><br> <em>Dataset used under the following license: https://creativecommons.org/licenses/by/4.0/</em><br> <br> <em>Original publication:</em><br> <em>R. Santos, J. P. Arrais and P. A. Silva, "Analysing Games for Health through Users' Opinion Mining,"</em><br> <em>2021 IEEE 34th International Symposium on Computer-Based Medical Systems (CBMS), Aveiro, Portugal, 2021, pp. 319-323,</em><br> <em>doi: 10.1109/CBMS52027.2021.00035.</em>
DOI: 10.6084/m9.figshare.22822433.v2
title: Just Dance shorthen properties

description: <em>Dataset containing comments and metadata information for multilabel predictions for different properties of comments.</em><br> <br> <em>The data has 216193 comments make on the just dance YouTube videos. It has metadata information about the date the</em><br> <em>comment was written and the number of "likes" it got. It also has</em><br> <em>42 multilabel binary target label columns,</em><br> <em>referring to the category classification of the comment.</em><br> <br> <em>This dataset is a modification of Just Dance @ YouTube dataset curated by the COIMBRA university,</em><br> <em>For additional details about the dataset, please refer to the original source:</em><br> <em>https://www.kaggle.com/datasets/renatojmsantos/just-dance-on-youtube.</em><br> <em>Dataset used under the following license: https://creativecommons.org/licenses/by/4.0/</em><br> <br> <em>Original publication:</em><br> <em>R. Santos, J. P. Arrais and P. A. Silva, "Analysing Games for Health through Users' Opinion Mining,"</em><br> <em>2021 IEEE 34th International Symposium on Computer-Based Medical Systems (CBMS), Aveiro, Portugal, 2021, pp. 319-323,</em><br> <em>doi: 10.1109/CBMS52027.2021.00035.</em>
DOI: 10.5281/zenodo.7270574
title: BIO4AFRICA_Survey Data Ghana - Analysis of the needs and contexts of target farmers and rural communities with a gender lens_D1.1_101022_1

description: The results of this survey support the identification of the needs, challenges, and context of target farmers and rural communities and how, why and under which circumstances the social, economic, regulatory, institutional, market and political circumstances could act as a barrier or an enabler for the uptake of bio-based solutions.
DOI: 10.5281/zenodo.7270573
title: BIO4AFRICA_Survey Data Ghana - Analysis of the needs and contexts of target farmers and rural communities with a gender lens_D1.1_101022_1

description: The results of this survey support the identification of the needs, challenges, and context of target farmers and rural communities and how, why and under which circumstances the social, economic, regulatory, institutional, market and political circumstances could act as a barrier or an enabler for the uptake of bio-based solutions.
DOI: 10.5281/zenodo.7270707
title: BIO4AFRICA_Survey Data Senegal - Analysis of the needs and contexts of target farmers and rural communities with a gender lens_D1.1_101022_1

description: The results of this survey support the identification of the needs, challenges, and context of target farmers and rural communities and how, why and under which circumstances the social, economic, regulatory, institutional, market and political circumstances could act as a barrier or an enabler for the uptake of bio-based solutions.
DOI: 10.5281/zenodo.7270708
title: BIO4AFRICA_Survey Data Senegal - Analysis of the needs and contexts of target farmers and rural communities with a gender lens_D1.1_101022_1

description: The results of this survey support the identification of the needs, challenges, and context of target farmers and rural communities and how, why and under which circumstances the social, economic, regulatory, institutional, market and political circumstances could act as a barrier or an enabler for the uptake of bio-based solutions.
DOI: 10.34740/kaggle/dsv/5692588
title: Surface Roughness Classification
DOI: 10.5281/zenodo.7273999
title: BIO4AFRICA_Co-definition of technologies to be transferred with local farmers and communities - Technology Validation Data (Demographics)_D1.4_311022_1

description: Validation Data (Demographics) for Task 1.4: Co-definition of technologies to be transferred with local farmers and communities.
DOI: 10.5281/zenodo.7274000
title: BIO4AFRICA_Co-definition of technologies to be transferred with local farmers and communities - Technology Validation Data (Demographics)_D1.4_311022_1

description: Validation Data (Demographics) for Task 1.4: Co-definition of technologies to be transferred with local farmers and communities.