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ShareScore release 0.9.0
Dataset results
101 results for “signal detection”
Data from: Detecting signals of chronic shedding to explain pathogen persistence: Leptospira interrogans in California sea lions
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Signal detection theory applied to giant pandas: Do pandas go out of their way to make sure their scent marks are found?
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Natural noise affects conspecific signal detection and territorial defense behaviors in songbirds
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Detecting phylogenetic signal and adaptation in papionin cranial shape by decomposing variation at different spatial scales
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Confirming an antiphasic bicyclic pattern of forward entrainment in signal detection: a reanalysis of Sun et al. (2021)
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CommRad RF: A dataset of communication radio signals for detection, identification and classification
<p>In this age of information, data is the most valuable commodity. In today's world it is easier to acquire millions of standard/known and even non- standard/unknown RF signals. Perhaps, having such huge amount of data can help people to develop novel deep learning techniques. This dataset focuses on communication radios baseband signals. It includes RF signals from multiple radios using different frequencies, in different environments. Over 2700 RF signals from 27 different radios are included in the dataset. An RF receiver was used to capture the dataset, which automatically detects RF signals and records them until they disappear. In order to create a signal library, the receiver is connected to a laptop that pre-processes and stores RF signatures from different emitters.</p>
CommRad RF: A dataset of communication radio signals for detection, identification and classification
<div> <div> <div> <div> <p>In today’s world, data is one of the most valuable resources. It’s now easier than ever to collect millions of radio frequency (RF) signals, both well-known and unusual. With such a large amount of data, researchers can create advanced deep learning techniques. This dataset focuses on baseband signals from communication radios. It includes RF signals captured from 27 different radios, using various frequencies and recorded in different environments. Altogether, there are over 2,700 signals in this collection. The signals were captured using an RF receiver that automatically detects and records signals until they disappear. To organize these signals into a library, the receiver was connected to a laptop, which processed and saved the unique RF fingerprints from different devices.</p> </div> </div> </div> </div> <div> <div> <div> </div> </div> </div>
Variable Message Signal annotated images for object detection
<p><strong>If you use this dataset, please cite this paper: <em>Puertas, E.; De-Las-Heras, G.; Sánchez-Soriano, J.; Fernández-Andrés, J. Dataset: Variable Message Signal Annotated Images for Object Detection. Data 2022, 7, 41. https://doi.org/10.3390/data7040041</em></strong></p> <p>This dataset consists of Spanish road images taken from inside a vehicle, as well as annotations in XML files in PASCAL VOC format that indicate the location of Variable Message Signals within them. Also, a CSV file is attached with information regarding the geographic position, the folder where the image is located, and the text in Spanish. This can be used to train supervised learning computer vision algorithms, such as convolutional neural networks. Throughout this work, the process followed to obtain the dataset, image acquisition, and labeling, and its specifications are detailed. The dataset is constituted of <strong>1216</strong> instances, <strong>888</strong> positives, and <strong>328</strong> negatives, in <strong>1152</strong> jpg images with a resolution of 1280x720 pixels. These are divided into <strong>576</strong> real images and <strong>576</strong> images created from the data-augmentation technique. The purpose of this dataset is to help in road computer vision research since there is not one specifically for VMSs.</p> <p>The folder structure of the dataset is as follows:</p> <ul> <li>vms_dataset/ <ul> <li>data.csv</li> <li>real_images/ <ul> <li>imgs/</li> <li>annotations/</li> </ul> </li> <li>data-augmentation/ <ul> <li>imgs/</li> <li>annotations/</li> </ul> </li> </ul> </li> </ul> <p>In which:</p> <ul> <li><strong>data.csv:</strong> Each row contains the following information separated by commas (,): image_name, x_min, y_min, x_max, y_max, class_name, lat, long, folder, text.</li> <li><strong>real_images:</strong> Images extracted directly from the videos.</li> <li><strong>data-augmentation:</strong> Images created using data-augmentation</li> <li><strong>imgs:</strong> Image files in .jpg format.</li> <li><strong>annotations:</strong> Annotation files in .xml format.</li> </ul>
Data from: Phylogenetic signal detection from an ancient rapid radiation: effects of noise reduction, long-branch attraction, and model selection in crown clade Apocynaceae
Crown clade Apocynaceae comprise seven primary lineages of lianas, shrubs, and herbs with a diversity of pollen aggregation morphologies including monads, tetrads, and pollinia, making them an ideal group for investigating the evolution and function of pollen packaging. Traditional molecular systematic approaches utilizing small amounts of sequence data have failed to resolve relationships along the spine of the crown clade, a likely ancient rapid radiation. The previous best estimate of the phylogeny was a five-way polytomy, leaving ambiguous the homology of aggregated pollen in two major lineages, the Periplocoideae, which possess pollen tetrads, and the milkweeds (Secamonoideae plus Asclepiadoideae), which possess pollinia. To assess whether greatly increased character sampling would resolve these relationships, a plastome sequence data matrix was assembled for 13 taxa of Apocynaceae, including nine newly generated complete plastomes, one partial new plastome, and three previously reported plastomes, collectively representing all primary crown clade lineages and outgroups. The effects of phylogenetic noise, long-branch attraction, and model selection (linked versus unlinked branch lengths among data partitions) were evaluated in a hypothesis-testing framework based on Shimodaira–Hasegawa tests. Discrimination among alternative crown clade resolutions was affected by all three factors. Exclusion of the noisiest alignment positions and topologies influenced by long-branch attraction resulted in a trichotomy along the spine of the crown clade consisting of Rhabdadenia + the Asian clade, Baisseeae + milkweeds, and Periplocoideae + the New World clade. Parsimony reconstruction on all optimal topologies after noise exclusion unambiguously supports parallel evolution of aggregated pollen in Periplocoideae (tetrads) and milkweeds (pollinia). Our phylogenomic approach has greatly advanced the resolution of one of the most perplexing radiations in Apocynaceae, providing the basis for study of convergent floral morphologies and their adaptive value.
Supplementary material 4 from: Rosenblad MA, Martín MP, Tedersoo L, Ryberg M, Larsson E, Wurzbacher C, Abarenkov K, Nilsson RH (2016) Detection of signal recognition particle (SRP) RNAs in the nuclear ribosomal internal transcribed spacer 1 (ITS1) of three lineages of ectomycorrhizal fungi (Agaricomycetes, Basidiomycota). MycoKeys 13: 21-33. https://doi.org/10.3897/mycokeys.13.8579
SRP RNA multiple sequence alignment : Explanation note: Multiple sequence alignment with the SRP RNA sequences of Dumesic et al. (2015; Stereum hirsutum, Heterobasidion irregulare, and Heterobasidion annosum) aligned to our newly generated ITS sequences of Russula and Lactarius.
Supplementary material 3 from: Rosenblad MA, Martín MP, Tedersoo L, Ryberg M, Larsson E, Wurzbacher C, Abarenkov K, Nilsson RH (2016) Detection of signal recognition particle (SRP) RNAs in the nuclear ribosomal internal transcribed spacer 1 (ITS1) of three lineages of ectomycorrhizal fungi (Agaricomycetes, Basidiomycota). MycoKeys 13: 21-33. https://doi.org/10.3897/mycokeys.13.8579
ITS/SRP RNA multiple sequence alignment : Explanation note: Multiple sequence alignment comprising the 63 public ITS1 sequences with SRP RNA found in them, the three newly generated sequences, and the SRP RNA sequences from Dumesic et al. (2015) (Stereum hirsutum, Heterobasidion irregulare, and Heterobasidion annosum).
Supplementary material 2 from: Rosenblad MA, Martín MP, Tedersoo L, Ryberg M, Larsson E, Wurzbacher C, Abarenkov K, Nilsson RH (2016) Detection of signal recognition particle (SRP) RNAs in the nuclear ribosomal internal transcribed spacer 1 (ITS1) of three lineages of ectomycorrhizal fungi (Agaricomycetes, Basidiomycota). MycoKeys 13: 21-33. https://doi.org/10.3897/mycokeys.13.8579
ITS multiple sequence alignment : Explanation note: A multiple sequence alignment in the NEXUS format (Maddison et al. 1997) comprising all 63 matching ITS sequences, plus the three newly generated ones (KU356730, KU356731, and KU356732). The alignment was produced in MAFFT without manual adjustment (Katoh and Standley 2013). The alignment is composed of partial nSSU (bases 1-34 in the alignment), the full ITS1 (bases 35-678), the full 5.8S (bases 679-838), the full ITS2 (bases 839-1395), and partial nLSU (bases 1396-end). The SRP RNA occupies position 203-474 in the alignment. The alignment is provided for overview purposes only; the two-order nature of the taxa (Boletales and Russulales) coupled with the high variability of the ITS region jointly mean that the alignment will not be suited for phylogenetic inference.
Supplementary material 1 from: Rosenblad MA, Martín MP, Tedersoo L, Ryberg M, Larsson E, Wurzbacher C, Abarenkov K, Nilsson RH (2016) Detection of signal recognition particle (SRP) RNAs in the nuclear ribosomal internal transcribed spacer 1 (ITS1) of three lineages of ectomycorrhizal fungi (Agaricomycetes, Basidiomycota). MycoKeys 13: 21-33. https://doi.org/10.3897/mycokeys.13.8579
Output from cmsearch and primers used : Explanation note: A) The output from cmsearch showing all 63 relevant matches to the three ectomycorrhizal lineages. B) Detail of the primers used to re-amplify the specimens.
Dataset and code for 'Signal to Noise Ratio and Spectral Sampling Constraints on Olivine Detection and Compositional Determination in the Intermediate Infrared Region'
<p>Feature fitting code and spectra of olivine samples used in paper "<em>Signal to Noise Ratio and Spectral Sampling Constraints on Olivine Detection and Compositional Determination in the Intermediate Infrared Region: Applications in Planetary Sciences</em>"</p>
Evaluation of Safety and Performance of Intraoperative Detection of Light Signals During Electrosurgical Breast Cancer Resection
ClinicalTrials.gov study NCT06020573. IPD Sharing: NO. Countries: 1. Publications: 1.
Embolic Signals Detection Study (Esds) in Candidates for Surgical Carotid Revascularisation
ClinicalTrials.gov study NCT05134493. IPD Sharing: NO. Countries: 1. Publications: 1.
Non-invasive Point-of-care Diagnosis Using Machine Learning and Signal Analytics to Transform Early Detection of Heart Disease
ClinicalTrials.gov study NCT03864081. IPD Sharing: NO. Countries: 1. Publications: 0.
Non-invasive Technology for Early Signal Detection of Hypoxemia With ORI During Intubation
ClinicalTrials.gov study NCT03600181. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Detecting a Reward Signal in the Motor Cortex
ClinicalTrials.gov study NCT00422071. IPD Sharing: Not stated. Countries: 1. Publications: 3.
Observational Surveillance Study to Detect Potential Safety Signals in Patients Who Have Had at Least One Dose of GARDASIL™ (V501-031)
ClinicalTrials.gov study NCT01078220. IPD Sharing: Not stated. Countries: 0. Publications: 2.
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.