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1,049
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ShareScore release 0.9.0
Dataset results
1,049 results for “robustness”
FIG. 2 in A medium-sized robust-necked azhdarchid pterosaur (Pterodactyloidea: Azhdarchidae) from the Maastrichtian of Pui (Haţeg Basin, Transylvania, Romania)
FIG. 2. Photographs of LPV (FGGUB) R.2395, almost complete cervical four from Pui, Haţeg basin, in anterior (A), dorsal (B), posterior (C), lateral (D), left lateral, inverted, (E) and right lateral (F) views.
robustness
<p>robustness</p>
In vivo tracking of functionally tagged Rad51 unveils a robust strategy of homology search.
<p>This deposit contains all the raw data presented in the Figures of this manuscript<br> </p>
Datasets for "Generic and Robust Localization of Multi-Dimensional Root Causes"
<p>Datasets <code>A, B0, B1, B2, B3, B4, D</code> in Table VII. The ground truth root cause sets are in <code>injection_info.csv</code> in each subfolder.</p> <p>The official GitHub repo is <a href="https://github.com/NetManAIOps/Squeeze">NetManAIOps/Squeeze: ISSRE 2019: Generic and Robust Localization of Multi-Dimensional Root Cause (github.com)</a></p>
Fig. 4 in Structure and activity of a novel robust peroxidase from Alkanna frigida cell culture
Fig. 4. General chemical structure of the examined diazo compounds in reactions with POXalf.
Robust Table Integration in Data Lakes
<p>Benmarks</p>
Dataset for CDFI: Cross Domain Feature Interaction for Robust Bronchi Lumen Detection [ICRA2023]
<p>Data of lumen detection, including artifacts and clean images.</p>
Robust model training strategy via hard negative mining in the weakly labeled dataset for lymphatic invasion in gastric cancer
<p>Gastric cancer poses a significant public health concern, emphasizing the need for accurate evaluation of lymphatic invasion (LI) for determining prognosis and treatment options. However, this task is time-consuming, labor-intensive, and prone to intra- and inter-observer variability. Furthermore, the scarcity of annotated data presents a challenge, particularly in the field of digital pathology. Therefore, there is a demand for an accurate and objective method to detect LI using a small dataset, benefiting pathologists. In this study, we trained convolutional neural networks (CNNs) to classify LI using a four-step training process: (1) weak model training; (2) identification of false positives; (3) hard negative mining in a weakly labeled dataset; and (4) strong model training. To overcome the lack of annotated datasets, we applied a hard negative mining approach in a weakly labeled dataset, which contained only final diagnostic information, resembling the typical data found in hospital databases, and improved classification performance. Ablation studies were performed to simulate the lack of datasets and severely unbalanced datasets, further confirming the effectiveness of our proposed approach. Notably, our results demonstrated that despite the small number of annotated datasets, efficient training was achievable, with the potential to extend to other image classification approaches used in the field of medicine.</p><p> </p><p><strong>Key words: Artificial intelligence, Computational pathology, Gastric cancer, Lymphatic invasion, Hard negative mining</strong></p>
RESCU System for Robust Upper Limb Prosthesis Control
ClinicalTrials.gov study NCT04043234. IPD Sharing: NO. Countries: 1. Publications: 0.
Multicenter Prospective Trial of Office-based Carpal Tunnel Release With Ultrasound Guidance (ROBUST)
ClinicalTrials.gov study NCT05675046. IPD Sharing: NO. Countries: 1. Publications: 0.
Margin-Based Vs. Robust Photon Radiotherapy Planning in IMRT of HN-SQCC
ClinicalTrials.gov study NCT03552965. IPD Sharing: Not stated. Countries: 1. Publications: 0.
An Open Study to Assess the Robustness of the CRC749 Inhaler
ClinicalTrials.gov study NCT02474017. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Clinical Endpoint Bioequivalence Study of Test and Reference Inhalation Products in Patients With COPD With Device Robustness
ClinicalTrials.gov study NCT03137992. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Data from: Robustness of the outcome of adult bumblebee infection with a trypanosome parasite after varied parasite exposures during larval development
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Data from: Robustness of the approximate likelihood of the protracted speciation model
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Data from: Termite mounds can increase the robustness of dryland ecosystems to climatic change
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Data from: A robust and tunable mitotic oscillator in artificial cells
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Data from: The peripheral olfactory code in Drosophila larvae contains temporal information and is robust over multiple timescales
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Data from: Insulin signaling’s role in mediating tissue-specific nutritional plasticity and robustness in the horn-polyphenic beetle Onthophagus taurus
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Data from: Cold adaptation shapes the robustness of metabolic networks in Drosophila melanogaster.
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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.