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29 results for “visual estimate”
Deep Submergence Dive location dataset from Bell et al. Sci Advances: How Little We've Seen: A Visual Coverage Estimate of the Deep Seafloor
<p><span>How Little We’ve Seen: A Visual Coverage Estimate of the Deep Seafloor </span></p> <p><span>Katherine L.C. Bell,</span><sup><span>1</span></sup><em><sup><span>∗</span></sup></em><em><sup><span> </span></sup></em><span>Kristen N. Johannes,</span><sup><span>1<em>,</em>2</span></sup><span> </span></p> <p><span>Brian R.C. Kennedy,</span><sup><span>1<em>,</em>3 </span></sup><span>Susan E. Poulton</span><sup><span>1</span></sup><span> </span></p> <p><sup><span>1</span></sup><span>Ocean Discovery League, Saunderstown, RI 02874, USA, </span></p> <p><sup><span>2</span></sup><span>Integrative Oceanography Division, Scripps Institution of Oceanography, University of California San Diego, San Diego, CA 92037, USA </span></p> <p><sup><span>3</span></sup><span>Biology Department, Boston University, Boston, MA 02215 USA </span></p> <p><em><sup><span>∗</span></sup></em><span>To whom correspondence should be addressed: croff@alum.mit.edu. </span></p> <p><span><br>Despite the importance of visual observation in the ocean, we have imaged a minuscule fraction of the deep seafloor. Sixty-six percent of the entire planet is deep ocean (≥200 m), and our data show we have visually observed less than 0.001%, a total area approximately a tenth of the size of Belgium. Data gathered from over 44 thousand deep-sea dives indicate we have also seen an incredibly biased sample. Sixty-five percent of all in situ visual seafloor observations in our dataset were within 200 nm of only three countries: the United States, Japan, and New Zealand. Ninety-seven percent of all dives we compiled have been conducted by just five countries: the United States, Japan, New Zealand, France, and Germany. This small and biased sample is problematic when attempting to characterize, understand, and manage a global ocean.</span></p>
Sex differences in behavioural and anatomical estimates of visual acuity in the green swordtail Xiphophorus helleri
<p>Among fishes in the family Poeciliidae, signals such as colour patterns, ornaments, and courtship displays play important roles in mate choice and male-male competition. Despite this, visual capabilities in Poeciliids are understudied, in particular visual acuity, the ability to resolve detail. We used three methods to quantify visual acuity in male and female green swordtails (Xiphophorus helleri), a species in which body size and the length of the male's extended caudal fin ('sword') serve as assessment signals during mate choice and agonistic encounters. Topographic distribution of retinal ganglion cells (RGC) was similar in all individuals and characterized by areas of high cell densities located centro-temporally and nasally, as well as a weak horizontal streak. Based on the peak density of RGC in the centro-temporal area, anatomical acuity was estimated to be approximately 3 cycles/degree (cpd) in both sexes. However, a behavioural optomotor assay found significantly lower mean acuity in males (0.8 cpd) than females (3.0 cpd), which was not explained by differences in eye size between males and females. An additional behavioural assay, in which we trained individuals to discriminate striped gratings from grey stimuli of the same mean luminance, also showed lower acuity in males (1-2 cpd) than females (2-3 cpd). Thus, although retinal anatomy predicts identical acuity in males and females, two behavioural assays found higher acuity in females than males, a sexual dimorphism which is rare outside of invertebrates. Overall, our results have implications for understanding how Poeciliids perceive visual signals during mate choice and agonistic encounters.</p>
HoloSet - A Dataset for Visual-Inertial Pose Estimation in Extended Reality
<p>HoloSet was published at DATA'22 workshop at ACM SenSys'22. <br> <br> Overview: There is a lack of datasets for visual-inertial odometry applications in Mixed Reality (MR). To the best of our knowledge, there is no dataset available that is captured from an MR headset with a human as a carrier. To bridge this gap, we present a novel pose estimation dataset — called HoloSet — collected using Microsoft Hololens 2, which is a state-of-the-art head mounted device for XR. Potential applications for HoloSet include visual-inertial odometry, simultaneous localization and mapping (SLAM), and additional applications in XR that leverage visual-inertial data.</p> <p>HoloSet captures both macro and micro movements. For macro movements, the dataset consists of more than 66,000 samples of visual, inertial, and depth camera data in a variety of environments<br> (indoor, outdoor) and scene setups (trails, suburbs, downtown) under multiple user action scenarios (walk, jog). For micro movements, the dataset consists of more than 12,000 samples of additional articulated hand depth camera images while a user plays games that exercise fine motor skills and hand-eye coordination. We present basic visualizations and high-level statistics of the data and outline the potential research use cases for HoloSet.<br> <br> Please find the relevant publication at https://dl.acm.org/doi/abs/10.1145/3560905.3567763. </p>
Visual circuitry for distance estimation in Drosophila
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Sex differences in behavioural and anatomical estimates of visual acuity in the green swordtail Xiphophorus helleri
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Data from: On the use of double quantile regression and visual assessment to estimate performance constraints
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SGS-LTER CO2 Elevation Study: Visual estimates of plant cover on the OTC project on the Central Plains Experimental Range, Nunn, Colorado, USA 1997 - 2001
This data package was produced by researchers working on the Shortgrass Steppe Long Term Ecological Research (SGS-LTER) Project, administered at Colorado State University. Long-term datasets and background information (proposals, reports, photographs, etc.) on the SGS-LTER project are contained in a comprehensive project collection within the Digital Collections of Colorado (http://digitool.library.colostate.edu/R/?func=collections&collection_id=3429). The data table and associated metadata document, which is generated in Ecological Metadata Language, may be available through other repositories serving the ecological research community and represent components of the larger SGS-LTER project collection. Additional information and referenced materials can be found: http://hdl.handle.net/10217/82454. Every month, during the growing season, from 1997-2001, 10 small quadrats were placed in ambient and elevated CO2 open-top-chambers, and plant cover, by species, was visually estimated. In general, elevated CO2 caused an increase in one C3 grass species, Stipa comata, and a small increase in forbs.
Data files for Corron et al.'s article, "How low can we go? A skeletal maturity threshold for probabilistic visual sex estimation from immature human os coxae".
<p>Data files for Corron et al.'s article, "How low can we go? A skeletal maturity threshold for probabilistic visual sex estimation from immature human <em>os coxae</em>", published in <em>Forensic Science International</em>. doi: <a href="https://doi.org/10.1016/j.forsciint.2021.110854">10.1016/j.forsciint.2021.110854</a>.</p>
Neural mechanisms to incorporate visual counterevidence in self movement estimation
<p>In selecting appropriate behaviors, animals should weigh sensory evidence both for and against specific beliefs about the world. For instance, animals measure optic flow to estimate and control their own rotation. However, existing models of flow detection can be spuriously triggered by visual motion from external movements. Here, we show that stationary patterns on the retina, which constitute evidence against observer rotation, suppress inappropriate stabilizing rotational behavior in the fruit fly <em>Drosophila</em>. <em>In silico</em> experiments show that artificial neural networks that are optimized to distinguish observer movement from object motion similarly detect stationarity and incorporate negative evidence. Employing neural measurements and genetic manipulations, we identified components of the circuitry for stationary pattern detection, which runs parallel to the fly's local motion- and optic flow-detectors. Our results show how the fly brain incorporates negative evidence to improve heading stability, exemplifying how a compact brain exploits geometrical constraints of the visual world.</p>
Estimating density of mountain hares using distance sampling: a comparison of daylight visual surveys, night-time thermal imaging and camera traps
<p><a name="_Hlk58254629"></a></p> <p><a name="_Hlk58254629">Surveying cryptic, nocturnal animals is logistically challenging. Consequently, density estimates may be imprecise and uncertain. Survey innovations mitigate ecological and observational difficulties contributing to estimation variance. Thus, comparisons of survey techniques are critical to evaluate estimates of abundance. We simultaneously compared three methods for observing mountain hare (<i>Lepus timidus</i>) using Distance sampling to estimate abundance. Daylight visual surveys achieved 41 detections, estimating density at 14.3 hares km<sup>-2</sup> (95%CI 6.3–32.5) resulting in the lowest estimate and widest confidence interval. Night-time thermal imaging achieved 206 detections, estimating density at 12.1 hares km<sup>-2 </sup>(95%CI 7.6–19.4). Thermal imaging captured more observations at furthest distances, and detected larger group sizes. Camera traps achieved 3,705 night-time detections, estimating density at 22.6 hares km<sup>-2 </sup>(95%CI 17.1–29.9). Between the methods, detections were spatially correlated, although the estimates of density varied. Our results suggest that daylight visual surveys tended to underestimate density, failing to reflect nocturnal activity. Thermal imaging captured nocturnal activity, providing a higher detection rate, but required fine weather. Camera traps captured nocturnal activity, and operated 24/7 throughout harsh weather, but needed careful consideration of empirical assumptions. </a>We discuss the merits and limitations of each method with respect to the estimation of population density in the field.</p>
Video Data: Optic flow in the natural habitats of zebrafish supports spatial biases in visual self-motion estimation
<p>Video dataset accompanying "Spatial Biases in Optic-Flow Sampling for Self-Motion Estimation in Natural Environments." See accompanying <a href="https://github.com/eacooper/AlexanderOpticFlow">Github repository</a> for more documentation and analysis code.</p>
Deaf individuals use compensatory strategies to estimate visual time events
<p>Dataset related to the manuscript entitled Deaf individuals use compensatory strategies to estimate visual time events</p>
Preoperative Corneal Measurements Estimate the Corrected Distance Visual Acuity After Corneal Cross-linking
ClinicalTrials.gov study NCT06522789. IPD Sharing: NO. Countries: 1. Publications: 1.
Comparison of Body Weights Via Visual Estimation, Anthropometric Calculation, and Actual Measured in Critically Ill Patients
ClinicalTrials.gov study NCT06269861. IPD Sharing: NO. Countries: 1. Publications: 13.
Assement of Left Ventricular Function Before Decannulation in Cardiac Surgery :Visual Estimation vs TEE
ClinicalTrials.gov study NCT07286227. IPD Sharing: UNDECIDED. Countries: 1. Publications: 4.
Telesonography for Visually Estimating Ejection Fraction
ClinicalTrials.gov study NCT02960685. IPD Sharing: Not stated. Countries: 1. Publications: 5.
Implementation and Evaluation of a Perceptual Learning Module on Visual Estimation of LVEF
ClinicalTrials.gov study NCT03245567. IPD Sharing: NO. Countries: 1. Publications: 1.
The MAR Method Versus the Visual Estimation Method in Predicting External Blood Loss
ClinicalTrials.gov study NCT06855472. IPD Sharing: NO. Countries: 1. Publications: 6.
Estimating density of mountain hares using distance sampling: a comparison of daylight visual surveys, night-time thermal imaging and camera traps
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Neural mechanisms to incorporate visual counterevidence in self movement estimation
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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.
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.