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1,782 results for “Algorithm”
Between the Frames - Evaluation of Various Motion Interpolation Algorithms to Improve 360° Video Quality
<p>With the increasing availability of 360° video content, it becomes important to provide smoothly playing videos of<br> high quality for end users. For this reason, we compare the influence of different Motion Interpolation (MI) algorithms on 360°<br> video quality. After conducting a pre-test with 12 video experts in [3], we found that MI is a useful tool to increase the QoE (Quality<br> of Experience) of omnidirectional videos. As a result of the pretest, we selected three suitable MI algorithms, namely ffmpeg<br> Motion Compensated Interpolation (MCI), Butterflow and Super- SloMo. Subsequently, we interpolated 15 entertaining and realworld<br> omnidirectional videos with a duration of 20 seconds from 30 fps (original framerate) to 90 fps, which is the native refresh<br> rate of the HMD used, the HTC Vive Pro. To assess QoE, we conducted two subjective tests with 24 and 27 participants. In<br> the first test we used a Modified Paired Comparison (M-PC) method, and in the second test the Absolute Category Rating<br> (ACR) approach. In the M-PC test, 45 stimuli were used and in the ACR test 60. Results show that for most of the 360° videos, the<br> interpolated versions obtained significantly higher quality scores than the lower-framerate source videos, validating our hypothesis<br> that motion interpolation can improve the overall video quality for 360° video. As expected, it was observed that the relative<br> comparisons in the M-PC test result in larger differences in terms of quality. Generally, the ACR method lead to similar results,<br> while reflecting a more realistic viewing situation. In addition, we compared the different MI algorithms and can conclude that<br> with sufficient available computing power Super-SloMo should be preferred for interpolation of omnidirectional videos, while<br> MCI also shows a good performance.</p>
Recognition of Cutaneous Melanoma on Digitized Histopathological Slides via Artificial Intelligence Algorithm - deep net Matlab
<p>The file is the trained convolutional neural network (CNN) developed in "De Logu, Francesco, et al. "Recognition of Cutaneous Melanoma on Digitized Histopathological Slides via Artificial Intelligence Algorithm." <em>Frontiers in Oncology</em> 10 (2020)". The CNN is based on a pretrained Inception-ResNet-v2 to automatically recognizes cutaneous melanoma from histopathological digitalized slides. The file is in a Matlab format (.mat).</p>
Fast Deterministic Algorithms for Highly-Dynamic Networks (video)
Full video presentation of the paper: Fast Deterministic Algorithms for Highly-Dynamic Networks.<br><br>Appears in Session 4 of the 24th International Conference on Principles of Distributed Systems OPODIS 2020<br><a href="https://opodis2020.unistra.fr">https://opodis2020.unistra.fr</a>
Fast Hybrid Network Algorithms for Shortest Paths in Sparse Graphs (video)
Full video presentation of the paper: Fast Hybrid Network Algorithms for Shortest Paths in Sparse Graphs.<br><br>Appears in Session 4 of the 24th International Conference on Principles of Distributed Systems OPODIS 2020<br><a href="https://opodis2020.unistra.fr">https://opodis2020.unistra.fr</a>
DM-PhyClus: A Bayesian phylogenetic algorithm for infectious disease transmission cluster inference
<p>The files include the simulated datasets and the chain results for the simulation study described in, </p> <p>DM-PhyClus: A Bayesian phylogenetic algorithm for infectious disease transmission cluster inference</p> <p>Those are all compressed R data files (gzip format).</p>
Finite element data collected and Machine learning algorithms to predict the mechanical properties of innovative CLT
<p>This folder includes the data collected from the finite element simulations of the innovative CLT to compute its mechanical properties, the error of the closed-form solutions predicting the bending stiffness in the minor direction D22, the variation of the distance between the Reissner Mindlin and Bending Gradient theory in terms of spacing between lateral lamellas, the hyperparameters tuning of several ML algorithms (Regression Tree, Random Forest, Gradient Boosting and Artificial Neural Network), the ML evaluations, the saved artificial neural network algorithms to predict each mechanical property of innovative CLT, and the ML application to use it.</p>
Identification of Potential Functional Modules and Diagnostic Genes for Crohn's Disease Based on Weighted Gene Co-expression Network Analysis and LASSO Algorithm
<p>Table S1 651 DEGs between CD and control samples</p> <p>Table S2 381 ME turquoise module genes</p> <p>Table S3 Coefficients of the eight module genes analyzed by LASSO regression</p>
Parallel, Portable Algorithms for Distance-2 Maximal Independent Set and Graph Coarsening: Rebuttal Material
<p>Additional material with rebuttal of IPDPS22 submission, "Parallel, Portable Algorithms for Distance-2 Maximal Independent Set and Graph Coarsening".</p>
Large-scale comparison of machine learning algorithms for target prediction of natural products
<p>Supplement Materials of the article named "Large-scale comparison of machine learning algorithms for target prediction of natural products".</p>
Figure 2 from: Lahti L, da Silva F, Laine M, Lähteenoja V, Tolonen M (2017) Alchemy & algorithms: perspectives on the philosophy and history of open science. Research Ideas and Outcomes 3: e13593. https://doi.org/10.3897/rio.3.e13593
Figure 2 PHOS16 Conference Programme.
Dataset for a Novel Hybrid Cryptography Algorithm for RDP Security
<p>The dataset consists of 95 rows and 8 columns. Each row contains information about an alphanumeric character (e.g. (A-Z), (a-z), (0-9), punctuation, and all special characters). The columns were created based on the steps of the proposed hybrid cryptography algorithm. The features include ASCII_Equivalent, Hex_Values, S_box_Conversion, Decimal_Values_of_S_box, RSA_Encrypted_Values, Replaced_Values, Group, and Class, with Class being the dependent variable. The characters in the Replaced_Values column are assigned a class of 0 or 1 depending on the presence of uppercase or lowercase letters. The dataset was generated using small RSA keys for convenience.</p>
[5G-IANA] UC1 - Data processed by the AI object detection algorithm
<p>Bounding boxes of objects detected by the artificial intelligence algorithm for each video frame received.</p>
Design of NFF antenna by multi-objective algorithm
<p><span>提出了一种多目标方法来优化反射超表面阵列的相位分布</span></p>
Smart hydroponic agriculture using genetic algorithm based k-nearest neighbors
Open the record for dataset details and reuse information.
Data repository of the paper "Expectation Values from the Single-Layer Quantum Approximate Optimization Algorithm on Ising Problems"
<p>This data repository contains the I-set instances of the paper "Expectation Values from the Single-Layer Quantum Approximate Optimization Algorithm on Ising Problems". </p>
Solving the multi-commodity flow problem using an evolutionary routing algorithm in a computer network environment
<p>The continued increase in Internet traffic requires that routing algorithms make the best use of all available network resources. Most of the current deployed networks are not doing so due to their use of single path routing algorithms. In this work we propose the use of a multipath capable routing algorithm using Evolutionary Algorithms (EAs) that takes into account all the traffic going over the network and the link capacities by leveraging the information available at the Software Defined Networks (SDN) controller. The use of such information ensures that no link is used beyond its capacity, eliminating network congestion. We use EAs as true multi-objective solvers to provide a set of valid routing solutions from a single run of the algorithm. Modifications to the Multipath TCP (MPTCP) protocol are proposed to overcome the multipath problems associated with TCP.</p>
single-cell RNAseq data (data set 13) in the publication scFASTCORMICS: A contextualization algorithm to reconstruct metabolic multi-cell population models from single-cell RNAseq data
<p>The present dataset (dataset13) was used as input to build scFASTCORMICS models. The files correspond to the clusters identified by Seurat in the single-cell data from pancreas donor11 downloaded from the GEO website (<strong>GSE114297). </strong></p> <p>see the protocol: scFASTCORMICS: A contextualization algorithm to reconstruct metabolic multi-cell population models from single-cell RNAseq data</p> <p>and github: <a href="https://github.com/sysbiolux/scFASTCORMICS">https://github.com/sysbiolux/scFASTCORMICS</a></p> <p>For more information, version updates of the scFASTCORMICS. </p>
single-cell RNAseq data (data set 10) in the publication scFASTCORMICS: A contextualization algorithm to reconstruct metabolic multi-cell population models from single-cell RNAseq data
<p>The present dataset (dataset10) was used as input to build scFASTCORMICS models. The files correspond to the clusters identified by Seurat in the single-cell data from pancreas donor8 downloaded from the GEO website (<strong>GSE114297). </strong></p> <p>see the protocol: scFASTCORMICS: A contextualization algorithm to reconstruct metabolic multi-cell population models from single-cell RNAseq data</p> <p>and github: https://github.com/sysbiolux/scFASTCORMICS</p> <p>For more information, version updates of the scFASTCORMICS. </p>
single-cell RNAseq data (data set 6) in the publication scFASTCORMICS: A contextualization algorithm to reconstruct metabolic multi-cell population models from single-cell RNAseq data
<p>The present dataset (dataset6) was used as input to build scFASTCORMICS models. The files correspond to the clusters identified by Seurat in the single-cell data from pancreas donor4 downloaded from the GEO website (<strong>GSE114297). </strong></p> <p>see the protocol: scFASTCORMICS: A contextualization algorithm to reconstruct metabolic multi-cell population models from single-cell RNAseq data</p> <p>and github: <a href="https://github.com/sysbiolux/scFASTCORMICS">https://github.com/sysbiolux/scFASTCORMICS</a></p> <p>For more information, version updates of the scFASTCORMICS. </p>
single-cell RNAseq data (data set 2) in the publication scFASTCORMICS: A contextualization algorithm to reconstruct metabolic multi-cell population models from single-cell RNAseq data
<p>The present dataset (dataset2) was used as input to build scFASTCORMICS models. The files correspond to the clusters identified by Seurat in the single-cell data from normal mucosa samples downloaded from the GEO website (<strong>GSE81861). </strong></p> <p>see the protocol: scFASTCORMICS: A contextualization algorithm to reconstruct metabolic multi-cell population models from single-cell RNAseq data</p> <p>and github: https://github.com/sysbiolux/scFASTCORMICS</p> <p>For more information, version updates of the scFASTCORMICS. </p>
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.