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9 results for “cognitive automation”
BRAIN Journal-Brain-Like Artificial Intelligence for Automation-Figure 2. Two Possible Progress Scenarios for How to Reach Towards Machines and Systems with Human- Level Cognitive Skills
<p>Having identified the need for novel methods for machine recognition, situation assessment, and decision making in order to advance further in different automation domains, an important question is by what means can we reach such sophisticated mechanisms. The long-term goal in<br> mind is to construct machines and systems showing performances comparable to or even beyond human skill levels. In a guest talk at the Vienna University of Technology in 2008, Prof. Etienne Barnard, an expert in the field of Artificial Intelligence, made an interesting “conceptual suggestion” for two possible progress scenarios to reach this goal which could be summarized as depicted in Figure 2.</p>
Data from: Towards automated ethogramming: Cognitively-inspired event segmentation for streaming wildlife video monitoring
<p><span>Our dataset, Nest Monitoring of the Kagu, consists of around ten days (253 hours) of continuous monitoring sampled at 25 frames per second. Our proposed dataset aims to facilitate computer vision research that relates to event detection and localization. We fully annotated the entire dataset (23M frames) with spatial localization labels in the form of a tight bounding box. Additionally, we provide temporal event segmentation labels of five unique bird activities: Feeding, Pushing leaves, Throwing leaves, Walk-In, and Walk-Out. The feeding event represents the period of time when the birds feed the chick. The nest-building events (pushing/throwing leaves) occur when the birds work on the nest during incubation. Pushing leaves is a nest-building behavior during which the birds form a crater by pushing leaves with their legs toward the edges of the nest while sitting on the nest. Throwing leaves is another nest-building behavior during which the birds throw leaves with the bill towards the nest while being, most of the time, outside the nest. Walk-in and walkout events represent the transitioning events from an empty nest to incubation or brooding, and vice versa. We also provide five additional labels that are based on time-of-day and lighting conditions: Day, Night, Sunrise, Sunset, and Shadows. In our manuscript, we provide a baseline approach that detects events and spatially localizes the bird in each frame using an attention mechanism. Our approach does not require any labels and uses a predictive deep learning architecture that is inspired by cognitive psychology studies, specifically, Event Segmentation Theory (EST). We split the dataset such that the first two days are used for validation, and performance evaluation is done on the last eight days.</span></p>
Data from: Towards automated ethogramming: Cognitively-inspired event segmentation for streaming wildlife video monitoring
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The OpenFeeder: a flexible automated RFID feeder to measure inter and intraspecies differences in cognitive and behavioral performance in wild birds
<p>Understanding the ecology and evolution of personality and cognition requires the development of new tools to measure individual and species differences in behavioral and cognitive performances in wild populations. Furthermore, such tools should facilitate collection of large sample sizes, evaluate the repeatability of measured traits and allow direct comparison of species performances across a variety of behavioural tasks. Here we present a RFID-based feeder (OpenFeeder) designed to run visual cognitive tasks in wild animals. We illustrate the flexibility of the tool showing performances of three wild passerine species (<em>Parus major</em>, <em>Cyanistes caeruleus</em> and <em>Poecile palustris</em>) in an associative learning task. We recorded performances of a large number of individuals (>300) in the wild and showed both inter and intraspecific differences in associative learning. We also found moderate to high repeatability in individual differences in associative learning in each species. We show that the OpenFeeder is a flexible tool to record performance in multiple cognitive and behavioural tasks in free ranging animals across a variety of passerine species. The design, firmware, and software are open source to facilitate use in a wide variety of species and thus allow continuous improvement of the system and development of new behavioural and cognitive tasks. In doing so, we hope that this tool will be used by a large community of cognitive ecologists and comparative psychologists for both within and across species studies. Furthermore, our system should facilitate replication of results across populations along large-scale environmental gradients to improve our understanding of the role ecology plays in the evolution of cognitive traits.</p>
Automated and Personalized Cognitive Behavioral Therapy
ClinicalTrials.gov study NCT03445598. IPD Sharing: Not stated. Countries: 1. Publications: 3.
The OpenFeeder: a flexible automated RFID feeder to measure inter and intraspecies differences in cognitive and behavioral performance in wild birds
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An Automated, Experimenter-Free Method for the Standardised, Operant Cognitive Testing of Rats __ Data supplementing __
<p>These data supplement the article:</p> <p><strong>An Automated, Experimenter-Free Method for the Standardised, Operant Cognitive Testing of Rats</strong></p> <p><em>Marion Rivalan, Humaira Munawar, Anna Fuchs, York Winter (2017)</em></p> <ul> <li>Published: January 6, 2017</li> <li>http://dx.doi.org/10.1371/journal.pone.0169476</li> </ul> <p>Use is free for academic purposes, provided the aforementioned article is appropriately cited.</p> <p>The directory contains the following file: Pone_2016_DataSupplement-Zenodo.xlsx</p> <p>Explanations are within the document.</p>
A Study of a Self-Administered Memory Screening Test With Automated Reporting (SAMSTAR) in Participants With Mild Cognitive Impairment
ClinicalTrials.gov study NCT02419183. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Short-term Automated Longitudinal Analysis of Speech and Language in Cognitive Impairment
ClinicalTrials.gov study NCT05340218. 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.