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46 results for “network visualization”
Temporal overlays of the co-word analysis network on Ecotourism, Sustainable Tourism and Nature Based Tourism (1986-2022): Map and network for VOSViewer visualization
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Geographical overlays of the co-word analysis network on Ecotourism, Sustainable Tourism and Nature Based Tourism (1986-2022): Map and network for VOSViewer visualization
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Base outline of the co-word analysis network on Ecotourism, Sustainable Tourism and Nature Based Tourism (1986-2022): Map and Network for VOSViewer visualization
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Discovering and explaining the learning process of neural networks: A study on EEG data. The animated visualizations.
<p>In the paper 'Discovering and explaining the learning process of neural networks: A study on EEG data' frames of animated visualizations are presented. Here, the full animations are made available so they can be used for interpretation.</p>
One-Way Wave Propagator driven by pure visual neural network
<p>this repository is used to reproduce the key Figures of our manuscript titled "One-Way Wave Propagator driven by pure visual neural network". </p> <p>The code is running using MATLAB, Recommend using a GPU device.</p>
Improving Visual Perception and Visuo-motor Learning With Neurofeedback of Brain Network Interaction.
ClinicalTrials.gov study NCT05732649. IPD Sharing: NO. Countries: 1. Publications: 9.
Data from: NetView P: a network visualization tool to unravel complex population structure using genome-wide SNPs
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Data from: Cross-frequency synchronization connects networks of fast and slow oscillations during visual working memory maintenance
Neuronal activity in sensory and fronto-parietal (FP) areas underlies the representation and attentional control, respectively, of sensory information maintained in visual working memory (VWM). Within these regions, beta/gamma phase-synchronization supports the integration of sensory functions, while synchronization in theta/alpha bands supports the regulation of attentional functions. A key challenge is to understand which mechanisms integrate neuronal processing across these distinct frequencies and thereby the sensory and attentional functions. We investigated whether such integration could be achieved by cross-frequency phase synchrony (CFS). Using concurrent magneto- and electroencephalography, we found that CFS was load-dependently enhanced between theta and alpha–gamma and between alpha and beta-gamma oscillations during VWM maintenance among visual, FP, and dorsal attention (DA) systems. CFS also connected the hubs of within-frequency-synchronized networks and its strength predicted individual VWM capacity. We propose that CFS integrates processing among synchronized neuronal networks from theta to gamma frequencies to link sensory and attentional functions.
Data from: FlatNJ: a novel network-based approach to visualize evolutionary and biogeographical relationships
Split networks are a type of phylogenetic network that allow visualization of conflict in evolutionary data. We present a new method for constructing such networks called FlatNetJoining (FlatNJ). A key feature of FlatNJ is that it produces networks that can be drawn in the plane in which labels may appear inside of the network. For complex data sets that involve, for example, non-neutral molecular markers, this can allow additional detail to be visualized as compared to previous methods such as split decomposition and NeighborNet. We illustrate the application of FlatNJ by applying it to whole HIV genome sequences, where recombination has taken place, fluorescent proteins in corals, where ancestral sequences are present, and mitochondrial DNA sequences from gall wasps, where biogeographical relationships are of interest. We find that the networks generated by FlatNJ can facilitate the study of genetic variation in the underlying molecular sequence data and, in particular, may help to investigate processes such as intra-locus recombination. FlatNJ has been implemented in Java and is freely available at www.uea.ac.uk/computing/software/flatnj.
Figure 4 in Visual census, photographic records and the trial of a video network provide first evidence of the elusive Sicyopterus cynocephalus in Australia
Figure 4. – Cumulative number of Sicyopterus spp. in view at any one time during the recording period across the ten cameras (i.e. NetworkN) deployed on 18 September, 2014.
Figure 2 in Visual census, photographic records and the trial of a video network provide first evidence of the elusive Sicyopterus cynocephalus in Australia
Figure 2. – Benthic habitat use and appearance of select species. A: Brown morph of male Sicyopterus cynocephalus as seen in the plunge pool initially on the first visit (however, this image was obtained in the Solomon Islands), with all other images captured from the study site; B: White morph of a large (~180 mm TL) male S. cynocephalus grazing; C: Another large male (~200 mm TL) at the front of the crevice that it consistently occupied during active searches by researchers; D: A female S. cynocephalus in a crevice; E: S. lagocephalus in a small cave/crevice; F: A freshwater crab occupying a crevice. All images photographed with a Canon G10 still camera. Date of photographs. A: September 2015; B-E: 30 June, 2014; F: 18 September, 2014.
Figure 3 in Visual census, photographic records and the trial of a video network provide first evidence of the elusive Sicyopterus cynocephalus in Australia
Figure 3. – Number of Sicyopterus spp. observed at a second-by-second reso- lution on each of ten video cameras (a-j) based on a one-hour deployment in the field on 18 September, 2014.
Figure 1. – Study site. A in Visual census, photographic records and the trial of a video network provide first evidence of the elusive Sicyopterus cynocephalus in Australia
Figure 1. – Study site. A: Waterfall and bedrock section of stream immediately upstream of the plunge pool; B: Upper section of the plunge pool; C: Lower section of the plunge pool. All photographs taken from the right stream bank, and note that there is an underwater cave underneath the slab of rock upon which the photographer was standing.
Data from: Cross-frequency synchronization connects networks of fast and slow oscillations during visual working memory maintenance
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Data from: FlatNJ: a novel network-based approach to visualize evolutionary and biogeographical relationships
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Visual perception of liquids: insights from deep neural networks
<p>Datasets and analysis code of the following publication:</p> <p>Van Assen, J.J.R., Nishida, S. & Fleming, R. W. (2020). Visual perception of liquids: insights from deep neural networks. <em>PLOS Computational Biology. </em>DOI: 10.1371/journal.pcbi.1008018</p> <p>For any questions please contact the first author at mail [at] janjaap [dot] info</p> <p><strong>Contents:</strong></p> <p>1. DataAnalysis<br> - Jupyter Notebook to run the full analysis in R<br> - For installation details see: https://irkernel.github.io/requirements/</p> <p>2. FullStimulusSet<br> - 2 million liquid images with 16 viscosities, 10 scenes, 625 variations, and 20 frames<br> - Matlab script that merges the images horizontally for network input</p> <p>3. NeuralActivations<br> - Matlab files containing the neural activations if you cannot read out the networks</p> <p>4. TrainedNetworks<br> - 100 Trained networks referred to in the paper using Matlab and the Deep Learning Toolbox<br> - One custom layer file “switchLayerAdvanced.m”</p> <p>5. ValidationSet<br> - 800 experimental stimuli that were used for validation 16 viscosities, 10 scenes, 5 variations (1,6,11,16,21)<br> - Matlab script that merges the images horizontally for network input</p>
OpenAg Forum/Github network visualizations (gephi)
<p>It includes the gephi files used to the network visualization of the OpenAg community.</p> <p>Article published: Argenton Freire, R., & Ziggiatti Monteiro, E. (2020). Measuring the development and communication of open design communities: The case of the OpenAg Initiative. <em>First Monday</em>, <em>25</em>(9). https://doi.org/10.5210/fm.v25i9.10527</p>
Visualization Engineering Platform for Pulse Diagnosis of Traditional Chinese Medicine-The Research of Similar Moiré Feature Analyzing Approach Based on Recurrent Neural Network to Process the Measure
ClinicalTrials.gov study NCT04661605. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Evaluation of the Visual Motor Task's Impact on the Behavior of a Neuronal and Spinal Network in Hemiplegic Patients
ClinicalTrials.gov study NCT03094572. IPD Sharing: NO. Countries: 1. Publications: 0.
Data from: Three-dimensional visualization of the internal plastid membrane network during runner bean chloroplast biogenesis: dynamic model of the tubular-lamellar transformation
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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.