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19 results for “Feature representation”

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OpenNeuro52/100

Sharpening of Hierarchical Visual Feature Representations of Blurred Images

Open the record for dataset details and reuse information.

openCC0Jan 2021View details →
OpenNeuro44/100

Adaptive memory distortions are predicted by feature representations in parietal cortex

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openCC0Jan 2021View details →
zenodo40/100

Discrete Feature Representations of CHO Reaction Mechanisms as Quasireaction Subgraphs

<p>This data set contains 194778 quasireaction subgraphs extracted from CHO transition networks with 2-6 non-hydrogen atoms (CxHyOz, 2 &lt;= x + z &lt;= 6).</p> <p>The complete table of subgraphs (including file locations) is in CHO-6-atoms-subgraphs.csv file. The subgraphs are in GraphML format (http://graphml.graphdrawing.org) and are compressed using bzip2. All subgraphs are undirected and unweighted. The reactant and product nodes (initial and final) are labeled in the &quot;type&quot; node attribute. The nodes are represented as multi-molecule SMILES strings. The edges are labeled by the reaction rules in SMARTS representation. The forward and backward reading of the SMARTS string should be considered equivalent.</p> <p>The generation and analysis of this data set is described in<br> D. Rappoport, Statistics and Bias-Free Sampling of Reaction Mechanisms from Reaction Network Models, 2023, submitted. Preprint at ChemrXiv, DOI: 10.26434/chemrxiv-2023-wltcr</p> <p>Simulation parameters<br> - CHO networks constructed using polar bond break/bond formation rule set for CHO.<br> - High-energy nodes were excluded using the following rules:<br> &nbsp; (i) more than 3 rings, (ii) triple and allene bonds in rings, (iii) double bonds at<br> &nbsp; bridge atoms,(iv) double bonds in fused 3-membered rings.<br> - Neutral nodes were defined as containing only neutral molecules.<br> - Shortest path lengths were determined for all pairs of neutral nodes.<br> - Pairs of neutral nodes with shortest-path length &gt; 8 were excluded.<br> - Additionally, pairs of neutral nodes connected only by shortest paths passing through<br> &nbsp; additional neutral nodes (reducible paths) were excluded.</p> <p>For background and additional details, see paper above.</p>

opencc-by-4.0May 2023View details →
zenodo36/100

Adaptations of Scrum roles in software projects: Survey and Representation Tentative with Feature Models

<p>V&iacute;deo short paper sobre adapata&ccedil;&otilde;es dos pap&eacute;is do Scrum</p>

opencc-by-4.0Oct 2020View details →
zenodo36/100

DSM: Deep Sequential Model for Complete Neuronal Morphology Representation and Feature Extraction

<p>This is an open-source repository for hosting codes and&nbsp;data files from research, "DSM: Deep Sequential Model for Complete Neuronal Morphology Representation and Feature Extraction". We also provided a web service based on our methods, please go to http://114.117.165.134:8501/.</p><p>(1)raw_dataset.zip:&nbsp;</p><ol><li>1,282 neuron reconstructions from SEU-Allen dataset;</li><li>1,002 neuron reconstructions from Janelia dataset;</li><li>1,100 neuron reconstructions from ION dataset.</li></ol><p>(2)Supplementary.zip:&nbsp;Supplementary information, including tables and figures;</p><p>(3)DSM-tools.zip:&nbsp;A python package for converting neuron morphology into sequences and implementing DSM models.</p><ol><li>NeuronSequenceDataset class: to transform SWC files to sequence dataframes by binary tree traversals, and prepare for the input of DSM networks.</li><li>DSMDataConverter class: a helper to convert the sequence dataframes for classification and clustering.</li><li>DSMHierarchicalAttentionNetwork class: classification model, giving a pre-trained DSM-HAN model by default.</li><li>DSMAutoencoder class: clustering model, giving a pre-trained DSM-AE model by default.</li></ol><p>(4)neuron2seq_for_developer.zip:&nbsp;A repository for further development of the models, including source codes and all data files.</p>

opencc-by-4.0Jul 2023View details →
zenodo36/100

Psycholinguistic features of verbal representation of the concept of "gender inequality" by student youth

<p><strong><em>Goal. </em></strong><em>To present the results of a psycholinguistic experiment devoted to the study of verbal representations of the concept of &quot;gender inequality&quot; in the linguistic consciousness of young people.</em></p> <p><strong><em>Methods: </em></strong><em>a</em><strong><em>&nbsp;</em></strong><em>systematic analysis and generalization of literature on gender aspects of psycholinguistic research. Directed associative experiment (DAE) with the word-stimulus &quot;gender inequality&quot;; method of cognitive interpretation; questionnaire: to clarify the characteristics of the sample, comparative-descriptive and mathematical-statistical methods.</em></p> <p><strong><em>Results. </em></strong><em>The concept of &quot;gender inequality&quot; in the linguistic consciousness of student youth is represented by such frequent associations as: humiliate (6.8%), fight (4.5%), suppress (3.7%), insult (2.6%) and limit (2.3%). Differences in the most frequent reactions of women and men were revealed: women - to humiliate 42 (7.9%), to fight 32 (6%), to suppress 19 (3.6%), to limit 16 (3%), to insult 15 (2.8%) ), respect 11 (2.1%), solve 11 (2.1%); men: humiliate 11 (4.5%), oppress 10 (4.1%), insult 5 (2%), defend 5 (2%). </em></p>

opencc-by-4.0Aug 2021View details →
zenodo32/100

SAMPLER representations of FFPE TCGA-lung WSIs using tile-level features of the MMIL-Transformer model

<p>Here we provide single-scale SAMPLER representations of the FFPE TCGA-lung (LUAD and LUSC) WSIs using tile-level features provided in https://github.com/hustvl/MMIL-Transformer. To learn more about SAMPLER please visit https://github.com/TheJacksonLaboratory/SAMPLER.</p><p>The SAMPLER representations are provided as a single python pickle file. This pickle file contains a dictionary where each key is a WSI ID and each entry is the SAMPLER representation of the WSI.</p>

opencc-by-4.0Dec 2023View details →
dryad32/100

Data from: Inhibition decorrelates visual feature representations in the inner retina

The retina extracts visual features for transmission to the brain. Different types of bipolar cell split the photoreceptor input into parallel channels and provide the excitatory drive for downstream visual circuits. Mouse bipolar cell types have been described at great anatomical and genetic detail, but a similarly deep understanding of their functional diversity is lacking. Here, by imaging light-driven glutamate release from more than 13,000 bipolar cell axon terminals in the intact retina, we show that bipolar cell functional diversity is generated by the interplay of dendritic excitatory inputs and axonal inhibitory inputs. The resulting centre and surround components of bipolar cell receptive fields interact to decorrelate bipolar cell output in the spatial and temporal domains. Our findings highlight the importance of inhibitory circuits in generating functionally diverse excitatory pathways and suggest that decorrelation of parallel visual pathways begins as early as the second synapse of the mouse visual system.

opencc-zeroDec 2016View details →
dryad32/100

Data from: Inhibition decorrelates visual feature representations in the inner retina

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publicJun 2018View details →
zenodo28/100

Hippocampal Representation of Threat Features and Behavior in a Human Approach-Avoidance Conflict Anxiety Task: Unthresholded SPM Activation Maps

<p>This dataset includes group-level results from multifold parametric analyses of a high-resolution fMRI approach-avoidance conflict anxiety task (n = 19). SPM Results are divided in primary analyses using a 8 mm FWHM smoothing kernel, and secondary (localization) anaylses using a 4 mm FWHM kernel.</p> <p>Parametric modulators of BOLD activation were set up with serial orthogonalization in the following order: P1: TP, TM, TP x TM P2: A, TP, TM, A x TP, A x TM, TP x TM, A x TP x TM P3: Two separate analyses for approach and avoidance trials. Order of modulators as in P1.</p> <p>Abbreviations: TP = threat probability TM = threat magnitude A = action (approach / avoidance)</p> <p>The study is reported in the following reference: Abivardi A.*<em>, </em>Khemka S.*, Bach D.R. (2020) Hippocampal Representation of Threat Features and Behavior in a Human Approach-Avoidance Conflict Anxiety Task (accepted for publication in Journal of Neuroscience)</p> <p>Citation for this dataset: <a href="https://doi.org/10.5281/zenodo.3893443">https://doi.org/10.5281/zenodo.3893443</a>.</p>

openother-openJul 2020View details →
zenodo28/100

Adaptations of Scrum roles in software projects: Survey and Representation Tentative with Feature Models

<p>V&iacute;deo sobre adapta&ccedil;&otilde;es dos pap&eacute;is do Scrum</p>

opencc-by-4.0Oct 2020View details →
zenodo28/100

Adaptations of Scrum roles in software projects: Survey and representation tentative with feature models

<p>V&iacute;deo em portugu&ecirc;s</p> <p>&nbsp;</p> <p>This work is supported by CAPES/Brazil (Coordena&ccedil;&atilde;o de Aperfei&ccedil;oamento de Pessoal de N&iacute;vel Superior) code 001.</p>

opencc-by-4.0Oct 2020View details →
zenodo28/100

FEATURES OF UKRAINIAN STUDENTS` VERBAL REPRESENTATION OF THE GENDER INEQUALITY`S CONCEPT

<p>The study aimed to determine Ukrainian students&#39; verbal representation of the gender inequality&#39;s concept. Verbal representations were obtained based on the use of a directed associative experiment. The study involved 309 students (199 females and 110 males) from 17 to 25 years. Gender analysis showed: women provided 539 reactions, including 530 verbal (176 originals) reactions and nine rejections; men provided 319 reactions: 310 verbal reactions (103 original) and nine rejections. The most frequent reactions to the stimulus &ldquo;gender inequality&quot; were revealed: жінка / woman (10,6%), чоловік / man (9,4%), фемінізм / feminism (4,3%), несправедливість / injustice (3,7%), права / rights (2,9%), нерівність / inequality (2,8%), стать / gender (2,7%), сексизм / sexism (2,4%), дискримінація / discrimination (2,3%), насильство / violence (2%). It was determined that the concept of &quot;gender inequality&quot; has a negative connotation among Ukrainian students. Cognitive interpretation of the data showed that the concept has a more negative emotional connotation for women than for men. For a significant number of women, gender inequality includes experiences associated with sexism, discrimination, and violence. Analysis of male associations has shown that men&#39;s concept has a less emotional response and is presented at a more abstract (theoretical) level.</p>

opencc-by-4.0Sep 2021View details →
zenodo24/100

Adaptations of Scrum roles in software projects: Survey and Representation Tentative with Feature Models

<p>V&iacute;deo do short paper sobre pap&eacute;is do Scrum</p>

opencc-by-4.0Oct 2020View details →
zenodo24/100

Database For Finite Volume Features, Global Geometry Representations, and Residual Training for Deep Learning-based CFD Simulation

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restrictedcc-by-4.0May 2024View details →
zenodo24/100

Anonymized data for paper "Cross-Project Defect Identification via Path-Based Semantic Feature Representation" submitted to ICSE 2022

<p>The project includes the dataset and code used in the submitted ICSE 2022 paper titled &quot;# 971&nbsp;Cross-Project Defect Identification via Path-Based Semantic Feature Representation&quot;</p>

opencc-by-4.0Aug 2021View details →
geo16/100

Single-cell RNA sequencing clarifies dermal fibroblast subset representation in vitro and reveals variable persistence of keloid disease-associated features [scRNAseq]

GEO Series GSE293834. Homo sapiens. 4 samples. Type: Expression profiling by high throughput sequencing.

openGEO-OpenAug 2025View details →
geo16/100

Single-cell RNA sequencing clarifies dermal fibroblast subset representation in vitro and reveals variable persistence of keloid disease-associated features

GEO Series GSE303592. Homo sapiens. 20 samples. Type: Expression profiling by high throughput sequencing.

openGEO-OpenAug 2025View details →
geo12/100

Single-cell RNA sequencing clarifies dermal fibroblast subset representation in vitro and reveals variable persistence of keloid disease-associated features [bulk-RNAseq]

GEO Series GSE303591. Homo sapiens. 16 samples. Type: Expression profiling by high throughput sequencing.

openGEO-OpenAug 2025View details →

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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.

allen-brain-atlas
neuroscienceopenDocumentation, web resources, and API references are available online.
Last verified 2026-04-30Open record

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.

abode-home-cage
behavioral-neuroscienceopenThe DataShare record exposes download links for annotations, documentation, license text, and the zipped per-snippet data directory.
Last verified 2026-04-30Open record

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.

dandi-nwb
electrophysiologyopenPublished Dandiset metadata and archive endpoints are available through the production DANDI API.
Last verified 2026-04-30Open record

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.

ibl
behavioral-neuroscienceopenPublic sessions can be searched and loaded from the IBL public data server through ONE.
Last verified 2026-04-29Open record

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.

openneuro
neuroscienceopenPublished datasets are available on demand over the internet.
Last verified 2026-04-29Open record