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Dataset results
16 results for “artificial vision”
BRAIN Journal-Evolving Spiking Neural Networks for Control of Artificial Creatures-Figure 7. Effect of different type of movement on the image in the vision of artificial creature.
<p>Figure 7a, Figure 7b, Figure 7c and Figure 7d, shows effect of different type of movement on the image in the vision of artificial creature if food be on vision boundaries. As mentioned each part of the image equal 7.5 degree.<br> Therefore 15 degree left or right rotation locomotion equivalent two parts shift toward left or right.<br> For motion to forward direction, size of the image has been reduplicated so that each part has been become to the two similar parts. Then half of new image in right side and left side has been deleted in order to create new close image in vision. Accordingly, if food be on vision boundaries, the number of black parts of the image for the food object in ultimate location is 2, by one movement to forward direction the number of these parts become to 4, by one movement to forward direction the number of these parts become to 8 and so on. After four movements to forward all part of the image is black and the creature is succeed find the food object.</p>
Integrative processing in artificial and biological vision predicts the perceived beauty of natural images
<p><em>Data, code, and materials for Nara & Kaiser (2023). </em></p> <p><em>Preprint: </em><a href="https://www.biorxiv.org/content/10.1101/2023.05.05.539579v1">https://www.biorxiv.org/content/10.1101/2023.05.05.539579v1</a></p> <p>Paper: <a href="https://doi.org/10.1126/sciadv.adi9294">https://doi.org/10.1126/sciadv.adi9294</a></p> <p>In this version (v2) of the repository, we:</p> <ul> <li>fixed an error in the fMRI data, where only the data from one participant, instead of all participants was uploaded previously - now all data are available,</li> <li>added brain masks (extracted by SPM) for each participant, and</li> <li>added realignment parameter text files (created by SPM) to the functional data for each participant.</li> </ul>
Avian-eye-inspired perovskite artificial vision system for foveated and multispectral imaging
<p>Avian eyes possess a deep central fovea as a result of extensive evolution. Deep fovea efficiently refracts incident light, creating a magnified image of the target object and making it easier to track its motion. These features are essential for detecting and tracking remote objects in dynamic environments. Furthermore, avian eyes respond to a wide spectrum of light, including visible and ultraviolet light, allowing them to efficiently distinguish the target object from complex backgrounds. Despite notable advances in artificial vision systems that mimic animal vision, the exceptional object detection and targeting capabilities of avian eyes via foveated and multispectral imaging remain underexplored. Here, we present an artificial vision system that capitalizes on these aspects of avian vision. We introduce an artificial fovea and vertically-stacked perovskite photodetector arrays whose designs are optimized by theoretical simulations for the demonstration of foveated and multispectral imaging. The artificial vision system successfully identifies colored and mixed-color objects and detects remote objects through foveated imaging. The potential for use in uncrewed aerial vehicles that need to detect, track, and recognize distant targets in dynamic environments is also discussed. Our avian-eye-inspired perovskite artificial vision system marks a notable advance in bio-inspired artificial visions.</p>
Avian-eye-inspired perovskite artificial vision system for foveated and multispectral imaging
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Wide-angle simulated artificial vision enhances spatial navigation and object interaction in a naturalistic environment
<p>This folder contains the dataset and the processing code generated in the article 'Wide-angle simulated artificial vision enhances spatial navigation and object interaction in a naturalistic environment' by Hinrichs et al. </p> <p> </p>
Continued Study of Artificial Vision: Evaluation of the BrainPort® System and Investigation of Visual Ambulation
ClinicalTrials.gov study NCT02643238. IPD Sharing: NO. Countries: 1. Publications: 6.
Artificial Intelligence-assisted Colonoscopy With or Without Endocuff Vision
ClinicalTrials.gov study NCT05863208. IPD Sharing: NO. Countries: 1. Publications: 5.
Comparison of the ENDOCUFF VISION® Endoscopy Cap Coupled With GI GENIUS™ Artificial Intelligence Compared to Each Device Alone in Improving Colonic Adenoma Detection Rate During Colonoscopy
ClinicalTrials.gov study NCT05594576. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Leveraging Artificial Intelligence to Prevent Vision Loss From Diabetes Among Socioeconomically Disadvantaged Communities
ClinicalTrials.gov study NCT06763952. IPD Sharing: YES. Countries: 1. Publications: 0.
The Efficacy of an Artificial Intelligence Platform to Adapt Visual Aids for Patients With Low Vision: a Randomised Controlled Trial
ClinicalTrials.gov study NCT04919837. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Masked Comparison of a New PEG Based Artificial Tear and Optive for Comfort, Vision & Wear Time in Patients Wearing Contact Lenses
ClinicalTrials.gov study NCT00570843. IPD Sharing: Not stated. Countries: 1. Publications: 0.
AI-Powered Artificial Vision for Visual Prostheses
ClinicalTrials.gov study NCT06117332. IPD Sharing: NO. Countries: 2. Publications: 0.
Personalized Monitoring of Non-foveal, Non-vision Compromising Atrophic Age-related Macular Degeneration With Artificial Intelligence and Identification of Disease Progression
ClinicalTrials.gov study NCT06351657. IPD Sharing: Not stated. Countries: 6. Publications: 0.
BVI System: Development of an assisted vision system for blind people based on hand movement and artificial intelligence
<p><strong>BVI System</strong></p> <ul> <li><strong>Complementary repository to the article</strong>: "Development Of An Assisted Vision System For Blind People Based On Hand Movement And Artificial Intelligence"</li> <li><strong>Description</strong>: This repocitorio aims to present the files that were used for the development of the thesis "Development of a vision system for the blind based on Artificial Intelligence" of the University of Santiago, Chile (Usach).</li> <li><strong>DATASET</strong>: BVI-DATASET contains some of the most frequent signage in airports, subways and shopping malls. Available at ROBOFLOW ( <a href="https://app.roboflow.com/generic-signage/airports-ans-subways/7">here</a> ) <strong>GitHub repository</strong>: <a href="https://github.com/NicoGitSoft/BVI">https://github.com/NicoGitSoft/BVI</a></li> </ul>
Recovery of Motor Skills With the Use of Artificial Intelligence and Computer Vision
ClinicalTrials.gov study NCT06183970. IPD Sharing: Not stated. Countries: 0. Publications: 0.
Efficacy of PEG-400 and Systane Artificial Tears (Alcon) on Quality of Vision
ClinicalTrials.gov study NCT00627302. IPD Sharing: Not stated. Countries: 1. Publications: 0.
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.