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644 results for “genre”
FIG. 5 in Deux nouvelles espèces du genre Cynorkis Thouars (Orchidaceae, Orchidioideae) à Madagascar, et une nouvelle combinaison pour Cynorkis tryphioides var. leandriana (H.Perrier) Bosser
FIG. 5. —Cynorkis windsorensis Hervouet,sp. nov., dessins d'Alain Jouy: A, habitus;B, fleur vue de face; C, fleur vue de profil. Échelles: A, 20 mm; B, 2 mm; C, 3 mm.
FIG. 2 in Deux nouvelles espèces du genre Cynorkis Thouars (Orchidaceae, Orchidioideae) à Madagascar, et une nouvelle combinaison pour Cynorkis tryphioides var. leandriana (H.Perrier) Bosser
FIG. 2. — Cynorkis leandriana (H.Perrier) Hervouet, comb. nov., stat. nov.: holotype conservé au MNHN (P00102088).
FIG. 1 in Deux nouvelles espèces du genre Cynorkis Thouars (Orchidaceae, Orchidioideae) à Madagascar, et une nouvelle combinaison pour Cynorkis tryphioides var. leandriana (H.Perrier) Bosser
FIG. 1. — Cynorkis tryphioides Schltr.: A, holotype conservé au MNHN (P00102074); B, habitus, région d'Antsohihy, 10.II.2020; C, fleur, région d'Antsohihy, 13.I.2017, taille de l'image: 9 × 6 mm.
FIG. 4 in Deux nouvelles espèces du genre Cynorkis Thouars (Orchidaceae, Orchidioideae) à Madagascar, et une nouvelle combinaison pour Cynorkis tryphioides var. leandriana (H.Perrier) Bosser
FIG. 4. — Cynorkis windsorensis Hervouet, sp. nov. à Windsor Castle: A, habitus, 20.II.2001; B, fleurs, 20.II.2001; C, fleur de profil, 25.II.2020, taille de l'image 12 × 8 mm.
FIG. 9 in Deux nouvelles espèces du genre Cynorkis Thouars (Orchidaceae, Orchidioideae) à Madagascar, et une nouvelle combinaison pour Cynorkis tryphioides var. leandriana (H.Perrier) Bosser
FIG. 9. — Répartition de Cynorkis windsorensis Hervouet, sp. nov. et de Cynorkis ankaranensis Hervouet, sp. nov. dans le nord de Madagascar.
Fig. 2 in Le genre Ilex (Aquifoliaceae) en Nouvelle-Calédonie
Fig. 2. – Répartition de Ilex sebertii Pancher en Nouvelle-Calédonie. Les zones grisées représentent les substrats ultramafiques.
Fig. 1. – Ilex sebertii Pancher. A. Vue d in Le genre Ilex (Aquifoliaceae) en Nouvelle-Calédonie
Fig. 1. – Ilex sebertii Pancher. A. Vue d'ensemble d'un petit arbre de 6–7 m de hauteur, Haut-Coulna (NUM), Hienghène, 16.VI.2021; B. Rameau feuillé et infrutescences, plateau de Bogota (UM), Canala, 6.V.2016; C. Fleur femelle (hexamère) montrant les staminodes et un ovaire bien développé, Forêt Plate (NUM), limite Pouembout-Ponérihouen, 3.XII. 2015; D. Fleur mâle (pentamère) montrant des étamines fertiles et
Fig. 4 in Révision du genre Ammodaucus (Apiaceae) en Afrique du Nord
Fig. 4. – Méricarpes. A. Ammodaucus maroccanus (P.H. Davis & Hedge) C. Chatel. & Chamboul.; B. Ammodaucus leucotrichus Coss. & Durieu. [Photo: M. Charrier]
Fig. 1 in Révision du genre Ammodaucus (Apiaceae) en Afrique du Nord
Fig. 1. – Relations phylogénétiques du genre Ammodaucus Coss. & Durieu au sein de la sous-tribu des Daucinae (Apiaceae), résultat inféré
Fig. 5 in Révision du genre Ammodaucus (Apiaceae) en Afrique du Nord
Fig. 5. – Distribution de Ammodaucus maroccanus (P.H. Davis & Hedge) C. Chatel. & Chamboul. (ronds noirs), de A. leucotrichus Coss. & Durieu (ronds rouges) et de A. leucotrichus var.brevipilus L. Chevall. (ronds bleus).
Fig. 2. – A–B in Révision du genre Ammodaucus (Apiaceae) en Afrique du Nord
Fig. 2. – A–B. Ammodaucus maroccanus (P.H. Davis & Hedge) C. Chatel. & Chamboul.; C. Ammodaucus leucotrichus Coss. & Durieu. [A–B: Akka, Maroc, 2019; C: Es Smara, Maroc, 2015]
Fig. 3 in Novitates neocaledonicae. VIII. Taxonomie et nomenclature du genre Phelline (Phellinaceae) avec la description de la nouvelle espèce Phelline barrierei
Fig. 3. – Distribution de Phelline barrierei Barriera & Schlüssel sur la Grande Terre, en gris les zones à roches ultramafiques.
Fig. 2 in Novitates neocaledonicae. VIII. Taxonomie et nomenclature du genre Phelline (Phellinaceae) avec la description de la nouvelle espèce Phelline barrierei
Fig. 2. – Phelline barrierei Barriera & Schlüssel. A. Habitus; B. Inflorescence femelle; C. Jeune infrutescence.
Fig. 1 in Novitates neocaledonicae. VIII. Taxonomie et nomenclature du genre Phelline (Phellinaceae) avec la description de la nouvelle espèce Phelline barrierei
Fig. 1 – Phelline barrierei Barriera & Schlüssel. A. Rameau femelle; B. Fleurs femelles; C. Fleurs mâles; D. Fruit immature; E. Inflorescence mâle; F. Jeune infrutescence.
Fig. 1 in Descriptions de deux Cigales nouvelles du genre Musoda [Hom. Tibicinidae]
Fig. 1 à 3, Musoda flavida Karsch 1 et 2 segments génitaux mâles et partie distale de Pédéage vus de profil gauche (1), puis droit (2) 3 ovivalvula dela femelle.
Fig. 4 in Descriptions de deux Cigales nouvelles du genre Musoda [Hom. Tibicinidae]
Fig. 4 à 8. Musoda orienlalis n. sp.; 4 à 6 segments génitaux mâles et èdéage (Pun parutype mâle vus de profil gauche (4) puis droit (5) et de dessus (6) 7 aspect (le la limite postérieure (le Povivzilvula chez la femelle; 8 patte fouisseuse droite de la larve. Fig. 9 à 12, Musoda occidentalis n. sp. 9à11 segments génitaux et édéage (Yun mâle paratype vus de profil gauche (9) puis droit (10) et de dessus (11) 12 aspect de la limite postérieure de Povivalvula chez la femelle.
MSD-I: Million Song Dataset with Images for Multimodal Genre Classification
<p>The Million Song Dataset (https://labrosa.ee.columbia.edu/millionsong/) is a collection of metadata and precomputed audio features for 1 million songs. Along with this dataset, a dataset with annotations of 15 top-level genres with a single label per song was released. In our work, we combine the CD2c version of this genre datase (http://www.tagtraum.com/msd_genre_datasets.html) with a collection of album cover images. </p> <p><br> The final dataset contains 30,713 tracks from the MSD and their related album cover images, each annotated with a unique genre label among 15 classes. Based on an initial analysis on the images, we identified that this set of tracks is associated to 16,753 albums, yielding an average of 1.8 songs per album.</p> <p>We randomly divide the dataset into three parts: 70% for training, 15% for validation, and 15% for test, with no artist and album overlap across these sets. This is crucial to avoid possible overfitting, as the classifier may learn to predict the artist instead of the genre. </p> <p> </p> <p>Content:</p> <p>MSD-I dataset (mapping, metadata, annotations and links to images)<br> Data splits and feature vectors for TISMIR single-label classification experiments </p> <p>These data can be used together with the Tartarus deep learning python module https://github.com/sergiooramas/tartarus.</p> <p> </p> <p>Scientific References:</p> <p>Please cite the following paper if using MSD-I dataset or Tartarus software.</p> <p>Oramas, S., Barbieri, F., Nieto, O., and Serra, X (2018). Multimodal Deep Learning for Music Genre Classification, Transactions of the International Society for Music Information Retrieval, V(1).</p>
F I G. 1. — Ohbayashinema ochotoni n. gen., n in Ohbayashinema ochotoni n. gen., n. sp. (Nematoda, Trichostrongyloidea), parasite d'un Lagomorphe du Népal; intérêt phylétique de ce genre
F I G. 1. — Ohbayashinema ochotoni n. gen., n. sp., mâle. A, extrémité antérieure, vue latérale droite; 13, coupe transversale au milieu du corps; C, bourse caudale, vue ventrale; D, détail du pore excréteur et des deirides, vue ventrale; E, pointe d'un spicule. A, C, éch. = 150 fj.; B, éch. = 50 y.; D, E, éch. = 100 ¡A.
MediaEval AcousticBrainz Genre
<p>The <a href="https://mtg.github.io/acousticbrainz-genre-dataset/">AcousticBrainz Genre Dataset</a> consists of four datasets of genre annotations and music features extracted from audio suited for evaluation of hierarchical multi-label genre classification systems.</p> <p>The datasets are used within the <a href="https://multimediaeval.github.io/2018-AcousticBrainz-Genre-Task/">MediaEval AcousticBrainz Genre Task</a>. The task is focused on content-based music<br> genre recognition using genre annotations from multiple sources and large-scale music features data available in the <a href="https://acousticbrainz.org/">AcousticBrainz</a> database. The goal of our task is to explore how the same music pieces can be annotated differently by different communities following different genre taxonomies, and how this should be addressed by content-based genre recognition systems.</p> <p>We provide four datasets containing genre and subgenre annotations extracted from four different online metadata sources:</p> <ul> <li> <p><strong>AllMusic</strong> and <strong>Discogs</strong> are based on editorial metadata databases maintained by music experts and enthusiasts. These sources contain explicit genre/subgenre annotations of music releases (albums) following a predefined genre namespace and taxonomy. We propagated release-level annotations to recordings (tracks) in AcousticBrainz to build the datasets.</p> </li> <li> <p><strong>Lastfm</strong> and <strong>Tagtraum</strong> are based on collaborative music tagging platforms with large amounts of genre labels provided by their users for music recordings (tracks). We have automatically inferred a genre/subgenre taxonomy and annotations from these labels.</p> </li> </ul> <p>For details on format and contents, please refer to the <a href="https://mtg.github.io/acousticbrainz-genre-dataset/data/">data webpage</a>.</p> <p>Note, that the AllMusic ground-truth annotations are distributed separately at <a href="https://zenodo.org/record/2554044">https://zenodo.org/record/2554044</a>.</p> <p> </p> <p><strong>Citation</strong></p> <p>If you use the MediaEval AcousticBrainz Genre dataset or part of it, please cite our <a href="http://mtg.upf.edu/node/3960">ISMIR 2019 overview paper</a>:</p> <pre><code>Bogdanov, D., Porter A., Schreiber H., Urbano J., & Oramas S. (2019). The AcousticBrainz Genre Dataset: Multi-Source, Multi-Level, Multi-Label, and Large-Scale. 20th International Society for Music Information Retrieval Conference (ISMIR 2019).</code></pre> <p> </p> <p><strong>Acknowledgements</strong></p> <p>This work is partially supported by the European Union’s Horizon 2020 research and innovation programme under grant agreement No 688382 <a href="https://www.audiocommons.org/">AudioCommons</a>.</p> <p> </p>
Linked collectors and determiners for: Une espèce nouvelle du genre Dendrobium Sw. (Orchidaceae) de Nouvelle-Calédonie et une clé pour la section Kinetochilus Schltr..
Natural history specimen data linked to collectors and determiners held within, "Une espèce nouvelle du genre Dendrobium Sw. (Orchidaceae) de Nouvelle-Calédonie et une clé pour la section Kinetochilus Schltr.". Claims or attributions were made on Bionomia by volunteer Scribes, <a href="https://bionomia.net/dataset/26464cf9-5139-4f0c-90ea-39e1aeb0ff36">https://bionomia.net/dataset/26464cf9-5139-4f0c-90ea-39e1aeb0ff36</a> using specimen data from the dataset aggregated by the Global Biodiversity Information Facility, <a href="https://gbif.org/dataset/26464cf9-5139-4f0c-90ea-39e1aeb0ff36">https://gbif.org/dataset/26464cf9-5139-4f0c-90ea-39e1aeb0ff36</a>. Formatted as a Frictionless Data package.
ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.