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83 results for “Pattern Recognition”

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ClinicalTrials.gov32/100

Pattern Recognition Prosthetic Control

ClinicalTrials.gov study NCT04272593. IPD Sharing: YES. Countries: 1. Publications: 4.

controlledIPD-YESFeb 2026View details →
ClinicalTrials.gov32/100

Study to Demonstrate That Muscle Pattern Recognition (MPR) is an Effective Evaluation Tool for Musculoskeletal Neck or Back Pain

ClinicalTrials.gov study NCT00134225. IPD Sharing: Not stated. Countries: 2. Publications: 1.

restrictedIPD-UNDECIDEDFeb 2026View details →
ClinicalTrials.gov32/100

Pattern Recognition Prosthetic Control

ClinicalTrials.gov study NCT04272489. IPD Sharing: YES. Countries: 1. Publications: 4.

controlledIPD-YESFeb 2026View details →
dryad32/100

Data from: Species recognition and patterns of population variation in the reproductive structures of a damselfly genus

Open the record for dataset details and reuse information.

publicSep 2010View details →
dryad32/100

Balancing selection in Pattern Recognition Receptor signalling pathways is associated with gene function and pleiotropy in a wild rodent

Open the record for dataset details and reuse information.

publicMay 2020View details →
dryad32/100

Data from: Validating the use of coloration patterns for individual recognition in the worm pipefish using a novel set of microsatellite markers

Open the record for dataset details and reuse information.

publicJul 2013View details →
dryad32/100

Genotyping-by-sequencing-based identification of Arabidopsis pattern recognition receptor RLP32 recognizing proteobacterial translation initiation factor IF1

Open the record for dataset details and reuse information.

publicSep 2022View details →
dryad32/100

Data from: Macroparasites at peripheral sites of infection are major and dynamic modifiers of systemic anti-microbial pattern recognition responses

Open the record for dataset details and reuse information.

publicDec 2012View details →
dryad32/100

Tolerant pattern recognition: Evidence from phonotactic responses in the cricket Gryllus bimaculatus (de Geer)

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publicDec 2021View details →
zenodo28/100

Figure 1 from: Stehle M, Lasseck M, Khorramshahi O, Sturm U (2020) Evaluation of acoustic pattern recognition of nightingale (Luscinia megarhynchos) recordings by citizens. Research Ideas and Outcomes 6: e50233. https://doi.org/10.3897/rio.6.e50233

Figure 1 Verified L. megarhynchos recordings in groups based on the ConfS (10-20%, N=10; 20-30%, N=10; 30-40%, N=10; 40-50%, N=10; 50-60%, N=21; 60-70%, N=11; 70-80%, N=11; 80-90%, N=3).

opencc-by-4.0Mar 2020View details →
dryad28/100

Data from: Heritable variation in colour patterns mediating individual recognition

Understanding the developmental and evolutionary processes that generate and maintain variation in natural populations remains a major challenge for modern biology. Populations of Polistes fuscatus paper wasps have highly variable colour patterns that mediate individual recognition. Previous experimental and comparative studies have provided evidence that colour pattern diversity is the result of selection for individuals to advertise their identity. Distinctive identity-signalling phenotypes facilitate recognition, which reduces aggression between familiar individuals in P. fuscatus wasps. Selection for identity signals may increase phenotypic diversity via two distinct modes of selection that have different effects on genetic diversity. Directional selection for increased plasticity would greatly increase phenotypic diversity but decrease genetic diversity at associated loci. Alternatively, heritable identity signals under balancing selection would maintain genetic diversity at associated loci. Here, we assess whether there is heritable variation underlying colour pattern diversity used for facial recognition in a wild population of P. fuscatus wasps. We find that colour patterns are heritable and not Mendelian, suggesting that multiple loci are involved. Additionally, patterns of genetic correlations among traits indicated that many of the loci underlying colour pattern variation are unlinked and independently segregating. Our results support a model where the benefits of being recognizable maintain genetic variation at multiple unlinked loci that code for phenotypic diversity used for recognition.

opencc-zeroDec 2016View details →
dryad28/100

Data from: Color pattern facilitates species recognition but not signal detection: a field test using robots

There are many factors that affect signal design, including the need for rapid signal detection and the ability to identify the signal as conspecific. Understanding these different sources of selection on signal design is essential to explain the evolution of both signal complexity and signal diversity. We assessed the relative importance of detection and recognition for signal design in the black-bearded gliding lizard, Draco melanopogon, which uses the extension and retraction of a large, black-and-white dewlap (or throat fan) in territorial communication. We presented free-living lizards with robots displaying dewlaps of different designs that varied in the proportion of the black and white components. We found no effect of dewlap brightness or design on the time it took for a lizard to detect the robot, consistent with the view that initial detection is likely to be primarily elicited by movement rather than specific color or pattern. However, males (but not females) responded with a greater intensity to the dewlap treatment that most resembled the natural dewlap color and design of the species. Furthermore, males were more likely to display to any dewlap color in the presence of a neighbor. These results suggest that dewlap pattern may play an important role in species recognition but has minimal influence on the initial detection of the signal. Importantly, our results also highlight that factors unrelated to discrimination, such as social cues and individual motivational state, may affect responses to species identity cues.

opencc-zeroDec 2015View details →
zenodo28/100

Protein NMR assignment by isotope pattern recognition

<p>Dataset to accompany a paper titled "Protein NMR assignment by isotope pattern recognition".</p>

opencc-by-4.0Jun 2024View details →
zenodo28/100

OMuSense-23: A Multimodal dataset for contactless breathing pattern recognition and biometric analysis

<p>OMuSense-23 is a multimodal dataset for non-contact biometric and breathing analysis. &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; <br>This database comprises RGBD and mmWave radar data collected from 50 participants. &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; <br>The data capture process involves participants engaging in four breathing pattern activities &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; <br>(normal breathing, reading, guided breathing, and breath holding to simulate apnea) &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;&nbsp;&nbsp; &nbsp; &nbsp; &nbsp; &nbsp;&nbsp; <br>each one performed in three distinct static poses: standing (A), sitting (B), and lying down (C). &nbsp; &nbsp; &nbsp;&nbsp; <br>&nbsp;&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; <br>&nbsp;For citations please refer to the paper:<br>&nbsp;Manuel Lage Ca&ntilde;ellas, Le Nguyen, Anirban Mukherjee, Constantino &Aacute;lvarez Casado,<br>&nbsp;Xiaoting Wu, Nhi Nguyen, Praneeth Susarla, Sasan Sharifipour, Dinesh B. Jayagopi, Miguel Bordallo L&oacute;pez,<br>&nbsp;"OmuSense-23: A Multimodal Dataset For Contactless Breathing Pattern Recognition And Biometric Analysis",<br>&nbsp; arXiv:2407.06137, 2024 &nbsp;&nbsp;</p>

opencc-by-4.0May 2024View details →
zenodo28/100

Figures 56-65 from: Shevtsova E, Hansson C (2011) Species recognition through wing interference patterns (WIPs) in Achrysocharoides Girault (Hymenoptera, Eulophidae) including two new species. ZooKeys 154: 9-30. https://doi.org/10.3897/zookeys.154.2158

Figures 56-65 - Achrysocharoides maieri sp. nov.: 56 Head frontal, female 57 Ditto, male 58 Antenna lateral, female 59 Ditto, male 60 Mesosoma dorsal, female 61 Ditto, male 62 Mesosoma lateral, female 63 Ditto, male 64 Wing interference pattern (WIP), female 65 Ditto, male.

opencc-by-4.0Dec 2011View details →
zenodo28/100

Figures 38-45 from: Shevtsova E, Hansson C (2011) Species recognition through wing interference patterns (WIPs) in Achrysocharoides Girault (Hymenoptera, Eulophidae) including two new species. ZooKeys 154: 9-30. https://doi.org/10.3897/zookeys.154.2158

Figures 38-45 - Achrysocharoides butus (Walker), wing interference patterns (WIPs): 38–43 Males 44–45 Females. Wings on Figs 38, 40–45 from Wales, 1976 39 from Sweden, Skåne, 2010.

opencc-by-4.0Dec 2011View details →
zenodo28/100

Figures 28-37 from: Shevtsova E, Hansson C (2011) Species recognition through wing interference patterns (WIPs) in Achrysocharoides Girault (Hymenoptera, Eulophidae) including two new species. ZooKeys 154: 9-30. https://doi.org/10.3897/zookeys.154.2158

Figures 28-37 - Achrysocharoides spp., wing interference patterns (WIPs): 28–35 Achrysocharoides robiniae Hansson &amp; Shevtsova 28–33 Males 34–35 Females 36–37 Achrysocharoides robinicolus Hansson &amp; Shevtsova 36 Male 37 Female. Wings on Figs 28–31, 34–37 from USA, Connecticut, 2002 32, 33, from Hungary, Vas Co., 2002.

opencc-by-4.0Dec 2011View details →
zenodo28/100

Figures 18-27 from: Shevtsova E, Hansson C (2011) Species recognition through wing interference patterns (WIPs) in Achrysocharoides Girault (Hymenoptera, Eulophidae) including two new species. ZooKeys 154: 9-30. https://doi.org/10.3897/zookeys.154.2158

Figures 18-27 - Achrysocharoides spp., wing interference patterns (WIPs): 18–23 Achrysocharoides platanoidae Hansson &amp; Shevtsova 18–21 Males 22–23 Females 24–27 Achrysocharoides acerianus (Askew) 24–25 Males 26–27 Females. All wings from specimens from Sweden, Skåne, 2010.

opencc-by-4.0Dec 2011View details →
zenodo28/100

Figures 66-71 from: Shevtsova E, Hansson C (2011) Species recognition through wing interference patterns (WIPs) in Achrysocharoides Girault (Hymenoptera, Eulophidae) including two new species. ZooKeys 154: 9-30. https://doi.org/10.3897/zookeys.154.2158

Figures 66-71 - Achrysocharoides maieri sp. n.: 66 Head frontal, female 67 Ditto, male 68 Vertex, female 69 Ditto, male 70 Mesosoma dorsal, female. 71 Ditto, male.

opencc-by-4.0Dec 2011View details →
zenodo28/100

Figures 46-55 from: Shevtsova E, Hansson C (2011) Species recognition through wing interference patterns (WIPs) in Achrysocharoides Girault (Hymenoptera, Eulophidae) including two new species. ZooKeys 154: 9-30. https://doi.org/10.3897/zookeys.154.2158

Figures 46-55 - Achrysocharoides spp., wing interference patterns (WIPs): 46–51 Achrysocharoides latreilleii (Curtis) 46–49 Males 50–51 Females 52–55 Achrysocharoides albiscapus (Delucchi), males. Wings on Figs 46, 47, 49–51 from England, Surrey 1986–2004 48 from Sweden, Skåne, 2010; 52, 53, 55 from Greece, Crete, 1997 54 from France, 1984.

opencc-by-4.0Dec 2011View details →

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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.

allen-brain-atlas
neuroscienceopenDocumentation, web resources, and API references are available online.
Last verified 2026-04-30Open record

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.

abode-home-cage
behavioral-neuroscienceopenThe DataShare record exposes download links for annotations, documentation, license text, and the zipped per-snippet data directory.
Last verified 2026-04-30Open record

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.

dandi-nwb
electrophysiologyopenPublished Dandiset metadata and archive endpoints are available through the production DANDI API.
Last verified 2026-04-30Open record

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.

ibl
behavioral-neuroscienceopenPublic sessions can be searched and loaded from the IBL public data server through ONE.
Last verified 2026-04-29Open record

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.

openneuro
neuroscienceopenPublished datasets are available on demand over the internet.
Last verified 2026-04-29Open record