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9,302 results for “DETECT”
Fault detection in Robotic Swarm Aggregation using a Kalman Filter - Appendix
<p>The appendix for my bachelor thesis: Fault detection in Robotic Swarm Aggregation using a<br> Kalman Filter. In the images of the aggregation experiments the different lines refer to the number of clustering robots.</p>
MALDI-TOF mass spectrometry profiling of bovine skim milk for subclinical mastitis detection
<p>MALDI-TOF spectra acquired from bovine milk collected from dairy cows in Piedmont (Italy)</p>
Real-time detection and grading of degenerative disc disease using YO-LO-v5 model
<p>Video 1: Real-time detection and grading of degenerative disc disease using YOLO-v5 model</p>
A Dataset of Patients Reviews on Doctissimo Forum of the 2017 Levothyrox Scandal in France for the Early Detection of Safety Signals from Social Networks
<p>In France, the Levothyrox case is an extremely mediated pharmacovogilance case which received a lot of media coverage in August 2017 following the change, in March of the same year, of the pharmaceutical formulation of the specialty (modification of the type and content of excipients at the initial request of the french's national agency of drug safety - ANSM). Many patients have experienced adverse effects related to fluctuating thyroid function when they were already treated and stabilized with Levothyrox (3 million french patients with thyroid pathologies).</p> <p>This dataset presents patients posts collected from the French health forum <a href="http://forum.doctissimo.fr">Doctissimo</a>, Thyroid and Endocrine Problems sub-forum using a web scraping algorithm. The main idea is to find out whether the result of the processing of the data exchanged on the Doctissimo forum can be used in pharmacovigilance and whether it would have allowed better reactivity from the public authorities and responsible laboratories.</p> <p><br> Doctissimo was chosen since it is the most used health forum in France by drug consuming patients (ranking first with 61\% of users). Other sources of information could have been chosen such as Twitter which is the most used website in the world by drug consuming patients. Twitter brings together 52% of these patients against 27% for all discussion forums combined. However, access to Twitter data is chargeable, which is why Doctissimo has been selected.</p> <p>The extraction was performed on the ``Thyroide et Problemes Endocriniens (Thyroid and Endocrine Problems)'' sub-forum with the keyword ``levothyrox''. The choice of extracting information from this forum using the particular relevant keyword ``levothyrox'' was to limit the amount of extracted data. Indeed, during data extraction, Doctissimo blocks the scraping task when reaching a limit of 8,000 extracted discussion threads, since it detects an automatic machine activity.</p> <p>We collected the messages written between years 2000 and 2020. This resulted in a total of 110,260 comments written by a total of 7650 subjects. For each of the comments, we extract the date, pseudo of the person who wrote the comment, the comment's text, and URL link. </p> <p> </p>
A Fine-Grained Vehicle Detection (FGVD) Dataset for Unconstrained Roads
<p>The previous fine-grained datasets mainly focus on classification and are often captured in a controlled setup, with the camera focusing on the objects. We introduce the first Fine-Grained Vehicle Detection (FGVD) dataset in the wild, captured from a moving camera mounted on a car. It contains 5502 scene images with 210 unique fine-grained labels of multiple vehicle types organized in a three-level hierarchy. While previous classification datasets also include makes for different kinds of cars, the FGVD dataset introduces new class labels for categorizing two-wheelers, autorickshaws, and trucks. The FGVD dataset is challenging as it has vehicles in complex traffic scenarios with intra-class and inter-class variations in types, scale, pose, occlusion, and lighting conditions. The current object detectors like yolov5 and faster RCNN perform poorly on our dataset due to a lack of hierarchical modeling. Along with providing baseline results for existing object detectors on FGVD Dataset, we also present the results of a combination of an existing detector and the recent Hierarchical Residual Network (HRN) classifier for the FGVD task. Finally, we show that FGVD vehicle images are the most challenging to classify among the fine-grained datasets.</p>
A Fine-Grained Vehicle Detection (FGVD) Dataset for Unconstrained Roads
<p>The previous fine-grained datasets mainly focus on classification and are often captured in a controlled setup, with the camera focusing on the objects. We introduce the first Fine-Grained Vehicle Detection (FGVD) dataset in the wild, captured from a moving camera mounted on a car. It contains 5502 scene images with 210 unique fine-grained labels of multiple vehicle types organized in a three-level hierarchy. While previous classification datasets also include makes for different kinds of cars, the FGVD dataset introduces new class labels for categorizing two-wheelers, autorickshaws, and trucks. The FGVD dataset is challenging as it has vehicles in complex traffic scenarios with intra-class and inter-class variations in types, scale, pose, occlusion, and lighting conditions. The current object detectors like yolov5 and faster RCNN perform poorly on our dataset due to a lack of hierarchical modeling. Along with providing baseline results for existing object detectors on FGVD Dataset, we also present the results of a combination of an existing detector and the recent Hierarchical Residual Network (HRN) classifier for the FGVD task. Finally, we show that FGVD vehicle images are the most challenging to classify among the fine-grained datasets.</p>
Is there a non-invasive biomarker for the early-stage detection of ovarian torsion: a systematic literature review
<p>Articles for meta-analysis </p>
Wayfinding artificial intelligence to detect clinically meaningful spots of retinal diseases: Artificial intelligence to help retina specialists in real world practice
<p>Dataset related to the Ambiguity index of 300 images analyzed in the thesis.</p>
VIOLA JONES ALGORITHM WITH CAPSULE GRAPH NETWORK FOR DEEPFAKE DETECTION
<p><strong>dataset of this paper VIOLA JONES ALGORITHM WITH CAPSULE GRAPH NETWORK FOR DEEPFAKE DETECTION</strong></p>
Evaluating Deep Learning-based Vulnerability Detection Models on Realistic Datasets
<p>This package contains all the data we used for our experiments.<br> </p>
Supplementary material 2 from: Villacorta-Rath C, Lach L, Andrade-Rodriguez N, Burrows D, Gleeson D, Trujillo-González A (2023) Invasive terrestrial invertebrate detection in water and soil using a targeted eDNA approach. NeoBiota 83: 71-89. https://doi.org/10.3897/neobiota.83.98898
Additional qPCR results
Supplementary material 1 from: Villacorta-Rath C, Lach L, Andrade-Rodriguez N, Burrows D, Gleeson D, Trujillo-González A (2023) Invasive terrestrial invertebrate detection in water and soil using a targeted eDNA approach. NeoBiota 83: 71-89. https://doi.org/10.3897/neobiota.83.98898
Invasive terrestrial invertebrate detection in water and soil using a targeted eDNA approach
Blurred remote sensing image detection 1.0
<p>This is an open dataset for blurred remote sensing image detection.</p>
Singleton detection mode prevents habituation of the attentional capture by color singleton distractors
<p>Datasets analysed during the study</p>
Meta-data of published work titled 'Effect of selection bias on Automatic Colonoscopy Polyp Detection'
<p>Meta-data of published work titled 'Effect of selection bias on Automatic Colonoscopy Polyp Detection' includes:</p> <p>1. Gastrolab-Polyp test dataset </p> <p>2. App release of the developed real-time polyp detector </p> <p>3. Meta-data prepared during test set analysis of the developed app and Polyp detector app on Google Store for five existing datasets like Polypgen, Kvasir, and CVC-Clinic, etc. </p> <p>For more details : https://www.sciencedirect.com/science/article/abs/pii/S1746809423003488</p> <p> </p>
Data for paper: Assessment of ChatGPT's ability to detect variability in requirements
<p>Data for paper: Assessment of ChatGPT's ability to detect variability in requirements</p>
BiLSTM and BiGRU models layer's view, for detection attack.
SciDraw upload
A chemiresistive-potentiometric multivariate sensor for discriminative gas detection
<p>The data set contains source data for all figures in this article and supplementary materials.</p>
Data Anomaly Detection in Cyber-Physical Energy Systems
<p>The data is created in an agent-system, used for controlling distributed energy systems. The agents follow the Lightweight Power Exchange Protocol to negotiate whenever an agent detects a planning problem. The protocol is explained in "A lightweight distributed software agent for automatic demand—supply calculation in smart grids" by Veith, Steinbach and Windeln. Different kinds of anomalies were created by manipulating an agent accordingly: anomalies in the values of the exchanged messages and anomalies in the communication behavior. The implementation of the power exchange used for the data generation can be found here: https://gitlab.com/mango-agents/mango-library/-/tags/Integration_of_the_LPEP.</p> <p>Anomalies in the values are manipulated by 500 % of the original value (dataset 500_p.csv).</p> <p>Anomalies in the communication behavior are anomalously started every minute for 8996 seconds in the future (dataset 1m_8996_50p.csv) and every 15 minutes for 2012 seconds in the future (15m_2012_50p.csv).</p> <p>For anomalies in the communication topology, an agent was chosen to which selected agent does not send any messages, although the agent is part of the neighborhood (Topology anomalies/agent_removed.csv). Furthermore, an agent was manipulated to send messages to an agent which is normally not part of its neighborhood (Topologie anomalies/agent_added.csv).</p> <p>Normal data is also given.</p>
Bioinformatics workflow for the detection of eQTL in the cattle genome using Nextflow DSL2
<p>The <em>in silico</em> detection of expression quantitative trait loci (eQTL) demands high throughput processing from hundreds of samples, which is often a challenge to handle and run such large datasets. In order to focus on the core analysis, it is convenient to have simple coding and hassle-free installation of different software tools required for the bioinformatics workflow. In this context, the newly available technologies like workflow managers and software containers enabled to develop workflows with less complexity. In this study, we developed an eQTL bioinformatics pipeline with the workflow manager Nextflow and docker container software, for coding and installing the required software tools. This workflow can be portable to a different computer environment, and the results are reproducible. We tested the functionality of our workflow with a sample dataset and the runtime estimates from this demo run will provide important information in planning future analyses with much larger datasets.</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.