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1,506 results for “objects”
Figure 1 in Seminiferous tubule number and surface: validation of objective parameters to estimate reproduction activity of male European anchovy (Engraulis encrasicolus, L.)
Figure 1. – Photomicrograph of male anchovy testicular tissue illustrating the seminiferous tubules in stage I.
Study to Investigate the Objective Response Rate of Dabrafenib in Combination With Trametinib in Subjects With BRAF V600 Mutation-Positive Melanoma
ClinicalTrials.gov study NCT02083354. IPD Sharing: UNDECIDED. Countries: 5. Publications: 2.
The Objective of This Study is to Evaluate the Efficacy, Safety and Tolerability of Cariprazine as an Adjunctive Treatment to Antidepressant Therapy (ADT) in Patients With Major Depressive Disorder (M
ClinicalTrials.gov study NCT03739203. IPD Sharing: YES. Countries: 8. Publications: 1.
Deep learning models challenge the prevailing assumption that face-like effects for objects of expertise support domain-general mechanisms
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Annotated spiral ganglion neuron training data for object detection
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Data and original code for: A generalized approach to characterise optical properties of natural objects
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A high-resolution and whole-body dataset of hand-object contact areas based on 3D scanning method
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An intracochlear electrocochleography dataset: From raw data to objective analysis using deep learning
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Hippocampal firing fields anchored to a moving object predict homing direction during path-integration-based behavior
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Cortical topographic motifs emerge in a self-organized map of object space
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Data from: Eurasian tree sparrows are more food neophobic and habituate to novel objects more slowly than house sparrows
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Data from: Illusory speeding-up and slowing-down of objects moving at constant speed emerges from natural motion detection algorithms
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Seurat objects for the manuscript Single-cell consequences of X-linked meiotic drive in stalk-eyed flies
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Object neophilia in wild herring gulls in urban and rural locations
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An objective-based prioritization approach to support trophic complexity through ecological restoration
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Data from: Adaptive multi-objective control explains how humans make lateral maneuvers while walking
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Data from: SimPLE: A visuotactile method learned in simulation to precisely pick, localize, regrasp, and place objects
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Common guillemots in the Baltic Sea studied with video surveillance and object detection: raw data, annotations, model, and model outputs
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A dataset for evaluating one-shot categorization of novel object classes
<p>From just a single example, we can derive quite precise intuitions about what other class members look like. This stands in stark contrast to machine learning algorithms, which typically require tens or even hundreds of thousands of examples to learn a new category. One of the most important open questions in our field is: How do humans achieve this? The stimuli and data provided here (in MATLAB format) are from thousands of crowd-sourced human responses to novel objects. The data can be used to test machine learning generalization as compared to human and also can be used as a test bed for various kinds of category learning models. </p>
Ground, Object and Interpretant
<p><strong>Ground, Object and Interpretant</strong></p> <p> </p> <p>Logic, in its general sense, is, as I believe I have shown, only another name for <em><strong>semiotic</strong></em> ({sémeiötiké}), the quasi-necessary, or formal, doctrine of signs. By describing the doctrine as "quasi-necessary," or formal, I mean that we observe the characters of such signs as we know, and from such an observation, by a process which I will not object to naming Abstraction, we are led to statements, eminently fallible, and therefore in one sense by no means necessary, as to what <em><strong>must be</strong></em> the characters of all signs used by a "scientific" intelligence, that is to say, by an intelligence capable of learning by experience. As to that process of abstraction, it is itself a sort of observation. The faculty which I call abstractive observation is one which ordinary people perfectly recognize, but for which the theories of philosophers sometimes hardly leave room. It is a familiar experience to every human being to wish for something quite beyond his present means, and to follow that wish by the question, "Should I wish for that thing just the same, if I had ample means to gratify it?" To answer that question, he searches his heart, and in doing so makes what I term an abstractive observation. He makes in his imagination a sort of skeleton diagram, or outline sketch, of himself, considers what modifications the hypothetical state of things would require to be made in that picture, and then examines it, that is, <em><strong>observes</strong></em> what he has imagined, to see whether the same ardent desire is there to be discerned. By such a process, which is at bottom very much like mathematical reasoning, we can reach conclusions as to what <em><strong>would be</strong></em> true of signs in all cases, so long as the intelligence using them was scientific. The modes of thought of a God, who should possess an intuitive omniscience superseding reason, are put out of the question. Now the whole process of development among the community of students of those formulations by abstractive observation and reasoning of the truths which <em><strong>must</strong></em> hold good of all signs used by a scientific intelligence is an observational science, like any other positive science, notwithstanding its strong contrast to all the special sciences which arises from its aiming to find out what <em><strong>must be</strong></em> and not merely what <em><strong>is</strong></em> in the actual world. Charles Sanders Peirce, Collected Papers of Charles Sanders Peirce, ed. by Charles Hartshorne, Paul Weiss, and Arthur W. Burks, 8 vols. (Cambridge, MA: Harvard University Press, 1931-1958), 2.227.</p> <p> </p> <p>A sign, or <em><strong>representamen</strong></em>, is something which stands to somebody for something in some respect or capacity. It addresses somebody, that is, creates in the mind of that person an equivalent sign, or perhaps a more developed sign. That sign which it creates I call the <em><strong>interpretant</strong></em> of the first sign. The sign stands for something, its <em><strong>object</strong></em>. It stands for that object, not in all respects, but in reference to a sort of idea, which I have sometimes called the <em><strong>ground</strong></em> of the representamen. "Idea" is here to be understood in a sort of Platonic sense, very familiar in everyday talk; I mean in that sense in which we say that one man catches another man's idea, in which we say that when a man recalls what he was thinking of at some previous time, he recalls the same idea, and in which when a man continues to think anything, say for a tenth of a second, in so far as the thought continues to agree with itself during that time, that is to have a <em><strong>like</strong></em> content, it is the same idea, and is not at each instant of the interval a new idea. <em>Ibid, </em>2.228.</p> <p> </p> <p>In consequence of every representamen being thus connected with three things, the ground, the object, and the interpretant, the science of semiotic has three branches. The first is called by Duns Scotus <em><strong>grammatica speculativa</strong></em>. We may term it <em><strong>pure grammar</strong></em>. It has for its task to ascertain what must be true of the representamen used by every scientific intelligence in order that they may embody any <em><strong>meaning</strong></em>. The second is logic proper. It is the science of what is quasi-necessarily true of the representamina of any scientific intelligence in order that they may hold good of any <em><strong>object</strong></em>, that is, may be true. Or say, logic proper is the formal science of the conditions of the truth of representations. The third, in imitation of Kant's fashion of preserving old associations of words in finding nomenclature for new conceptions, I call <em><strong>pure rhetoric</strong></em>. Its task is to ascertain the laws by which in every scientific intelligence one sign gives birth to another, and especially one thought brings forth another. <em>Ibid, </em>2.229.</p> <p> </p> <p>Written c. 1897</p>
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.