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921
datasets available to search
ShareScore release 0.7.1
Dataset results
921 results for “neural networks”
Data set used in "FACIAL WRINKLE CATEGORIZATION USING CONVOLUTIONAL NEURAL NETWORK"
<p><span>For the purpose of training the neural network, a total of 5,098 images were provided, collected over a period of 3 years. These images were categorized into 4 classes, with the number of images in each category as evenly balanced as possible, with minimal deviation from the ideal distribution</span>. <span>A tool for the detection and classification of wrinkles is provided in this way.</span></p>
NPClassifier: A Deep Neural Network-Based Structural Classification Tool for Natural Products
<p>Dataset for NPClassifier project</p>
Predicting code comprehension: a novel approach to align human gaze with code using deep neural networks
<p>Supplementary data and scripts intended for submission review only. </p>
A Convolutional Neural Network for Difficult Biliary Cannulation
ClinicalTrials.gov study NCT07389915. IPD Sharing: NO. Countries: 0. Publications: 0.
Osteoporotic Precisely Screening Using Chest Radiograph and Artificial Neural Network (OPSCAN)
ClinicalTrials.gov study NCT05721157. IPD Sharing: NO. Countries: 1. Publications: 0.
Accurate Diagnosis of the Invasion Depth in ESCC by a Deep Neural Network Analysis of NBI Endoscopy Data
ClinicalTrials.gov study NCT06252974. IPD Sharing: Not stated. Countries: 0. Publications: 0.
Effect of Donepezil on the Reorganization of Cognitive Neural Network in Patients With Post-Stroke Cognitive Impairment
ClinicalTrials.gov study NCT00530478. IPD Sharing: Not stated. Countries: 1. Publications: 0.
fMRI Study of Brain Neural Network and Plasticity After Stroke
ClinicalTrials.gov study NCT00530647. IPD Sharing: Not stated. Countries: 1. Publications: 0.
LSTM neural network for textual ngrams
Open the record for dataset details and reuse information.
Convolutional neural network modelling: advancing identification of true mRNA cleavage sites
GEO Series GSE163382. Solanum tuberosum; Phytophthora infestans. 35 samples. Type: Expression profiling by high throughput sequencing; Non-coding RNA profiling by high throughput sequencing.
GPM Ground Validation Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks Cloud Classification System (PERSIANN-CCS) IFloodS V1
The GPM Ground Validation Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks Cloud Classification System (PERSIANN-CCS) IFloodS dataset is a subset from the global 30-minute PERSIANN-CCS files generated in near-real time selected for the time period of the GPM Ground Validation Iowa Flood Studies (IFloodS) field campaign. The main goal of IFloodS were to collect detailed measurements of precipitation at the Earth’s surface using ground instruments and advanced weather radars and to simultaneously collect data from satellites passing overhead. This PERSIANN-CCS data product is available in ASCII and netCDF-4 formats from April 1, 2013 thru July 1, 2013.
GMDH polynomial neural network
Learning and building GMDH polynomial neural networks and printing them as 3rd degree polynomial equation.
An Adaptive Recurrent Neural Network for Remaining Useful Life Prediction of Lithium-ion Batteries
Prognostics is an emerging science of predicting the health condition of a system (or its components) based upon current and previous system states. A reliable predictor is very useful to a wide array of industries to predict the future states of the system such that the maintenance service could be scheduled in advance when needed. In this paper, an adaptive recurrent neural network (ARNN) is proposed for system dynamic state forecasting. The developed ARNN is constructed based on the adaptive/recurrent neural network architecture and the network weights are adaptively optimized using the recursive Levenberg-Marquardt (RLM) method. The effectiveness of the proposed ARNN is demonstrated via an application in remaining useful life prediction of lithium-ion batteries.*
CHD7 regulates gene networks involved in neural crest cell migration and axon guidance
GEO Series GSE46591. Mus musculus. 12 samples. Type: Expression profiling by array.
Joint sequence and chromatin neural networks characterize the differential abilities of Forkhead transcription factors to engage inaccessible chromatin
GEO Series GSE244411. Mus musculus. 57 samples. Type: Expression profiling by high throughput sequencing; Genome binding/occupancy profiling by high throughput sequencing; Other.
The Transcriptomic Consequences of Zika Virus Infection on Porcine Induced Neural Stem Cells and Associated Gene Regulatory Networks
GEO Series GSE225413. Sus scrofa. 9 samples. Type: Expression profiling by high throughput sequencing.
A transcriptome-based deep neural network classifier for identifying the site of origin in mucinous cancer
GEO Series GSE163126. Homo sapiens. 14 samples. Type: Expression profiling by high throughput sequencing.
Joint sequence and chromatin neural networks characterize the differential abilities of Forkhead transcription factors to engage inaccessible chromatin (ChIP-exo)
GEO Series GSE244410. Mus musculus. 28 samples. Type: Other.
Structure classification of glass-forming liquids by graph neural networks: Explaining predictions with the Self-Attention mechanism
<p>This repository includes the dataset and Python scripts used in the article, "Structure classification of glass-forming liquids by graph neural networks: Explaining predictions with the Self-Attention mechanism". The repository also includes source data of figures in the article.</p>
Dataset related to the article "UPVnet: A Neural Network for Accurate First-Arrival Picking in Ultrasonic Pulse Velocity Testing of Rock Samples"
<p>The compressed folder contains ultrasonic pulse velocity testing data for 172 P- and S-waves of 7 types of rocks mentioned in the article, as well as demonstration code for UPVnet.</p> <h2>Note:</h2> <ol> <li>Data augmentation generated 4500 training and 500 validation waveform datasets, stored in the .npz files in the "data" folder. In "UPVnet.ipynb", if "data_augmentation=True", data augmentation is reapplied; otherwise, the ".npz" files in the data folder are directly accessed.</li> <li>In UPVnet.ipynb, when "train_mode=True", the model is retrained. Otherwise, the model parameters are directly loaded from the ".pt" file in the "data" folder.</li> <li>All ultrasonic waveform data are saved in the "datasets" folder, named according to the format "(sample number)_(transducer type)_(measurement distance)_(experiment number)". "Calibration" indicates the calibration of the transducers.</li> </ol>
ScienceDex guides
Understand access before you commit
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.