Search results for "GEP"

showing 10 items of 1017 documents

Iris : a solution for executing handwritten code

2012

Masteroppgave i informasjons- og kommunikasjonsteknologi IKT590 2012 – Universitetet i Agder, Grimstad This paper presents a novel approach to executing handwritten code, the solution coined Iris. My research falls within the field of mobile app development, handwriting recognition, optical and intelligent character recognition (OCR & ICR), machine learning, as well as various Computer Science-related fields such as domain specific languages, or DSLs. The solution outlined in this paper details a system where one can author code using only a writing utensil (such as a pen), scratch paper (such as a napkin), and a smart phone. Iris leverages the power of the cloud to process an image of hand…

ComputingMethodologies_PATTERNRECOGNITIONComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION
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Table S1 from Open data and digital morphology

2017

Summary of main online repositories for 3D digital morphological data.

ComputingMethodologies_PATTERNRECOGNITIONComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONComputingMethodologies_COMPUTERGRAPHICS
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Interactive Pansharpening and Active Classification in Remote Sensing

2013

This chapter presents two multimodal prototypes for remote sensing image classification where user interaction is an important part of the system. The first one applies pansharpening techniques to fuse a panchromatic image and a multispectral image of the same scene to obtain a high resolution (HR) multispectral image. Once the HR image has been classified the user can interact with the system to select a class of interest. The pansharpening parameters are then modified to increase the system accuracy for the selected class without deteriorating the performance of the classifier on the other classes. The second prototype utilizes Bayesian modeling and inference to implement active learning …

ComputingMethodologies_PATTERNRECOGNITIONContextual image classificationKernel (image processing)PixelComputer scienceMultispectral imageComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONDecision boundaryLinear discriminant analysisClassifier (UML)Panchromatic filmRemote sensing
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Additional file 1 of Case report: Trans-papillary free stenting of the cystic duct and of the common bile duct in a double biliary ducts anastomoses …

2021

Additional file 1: Video. Imaging evaluation and surgical maneuvers.

ComputingMethodologies_SIMULATIONANDMODELINGData_FILESComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONComputerApplications_COMPUTERSINOTHERSYSTEMSComputingMethodologies_COMPUTERGRAPHICS
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"Table 1" of "Lowest Q**2 measurement of the gamma* p --> delta reaction: Probing the pionic contribution."

2006

Measured value of SIG(C=T) + EPS*SIG(C=L) as a function of the pion angle relative to the virtual photon direction.

ComputingMilieux_THECOMPUTINGPROFESSIONElectron productionNuclear TheoryIntegrated Cross SectionComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONCross SectionSIGInformationSystems_MODELSANDPRINCIPLES7.950E-017.950E-01E- P --> E- PI0 PExclusiveInformationSystems_MISCELLANEOUS1.221ComputingMethodologies_COMPUTERGRAPHICSComputer Science::Cryptography and Security
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The SISCone jet algorithm optimised for low particle multiplicities

2011

The SISCone jet algorithm is a seedless infrared-safe cone jet algorithm. There exists an implementation which is highly optimised for a large number of final state particles. However, in fixed-order perturbative calculations with a small number of final state particles, it turns out that the computer time needed for the jet clustering of this implementation is comparable to the computer time of the matrix elements. This article reports on an implementation of the SISCone algorithm optimised for low particle multiplicities.

Cone algorithmPhysicsComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONGeneral Physics and AstronomyFOS: Physical sciencesPartonJet (particle physics)Matrix (mathematics)High Energy Physics - PhenomenologyHigh Energy Physics - Phenomenology (hep-ph)Hardware and ArchitectureParticleState (computer science)Cluster analysisAlgorithmTest data
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Metal artifact reduction in x-ray computed tomography: Inpainting versus missing value

2011

A comparison of algorithms for reduction of metal artifacts in x-ray cone beam computed tomography (CBCT) is presented. In the context of algebraic reconstruction techniques (ART) several inpainting algorithms in the image domain are evaluated against missing data strategies. A GPU-based iterative framework is employed for a meaningful comparison of both. Simulation results from an extended Shepp-Logan phantom and real world dental data are given.

Cone beam computed tomographyComputer sciencebusiness.industryComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONInpaintingContext (language use)Iterative reconstructionMissing dataMetal ArtifactComputer visionTomographyArtificial intelligencebusinessImage restorationComputingMethodologies_COMPUTERGRAPHICS2011 IEEE Nuclear Science Symposium Conference Record
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A system based on neural architectures for the reconstruction of 3-D shapes from images

1991

The connectionist approach to the recovery of 3-D shape information from 2-D images developed by the authors, is based on a system made up by two cascaded neural networks. The first network is an implementation of the BCS, an architecture which derives from a biological model of the low level visual processes developed by Grossberg and Mingolla: this architecture extracts a sort of brightness gradient map from the image. The second network is a backpropagation architecture that supplies an estimate of the geometric parameters of the objects in the scene under consideration, starting from the outputs of the BCS. A detailed description of the system and the experimental results obtained by si…

ConnectionismArtificial neural networkbusiness.industryComputer scienceTime delay neural networkDeep learningComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONsortArtificial intelligenceArchitecturebusinessBackpropagationImage (mathematics)
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Metabolic disorders and gastroenteropancreatic-neuroendocrine tumors (GEP-NETs): How do they influence each other? An Italian Association of Medical …

2022

Gastroenteropancreatic neuroendocrine tumors (GEP-NETs) are a heterogeneous group of malignancies derived from neuroendocrine cells that can occur anywhere along the gastrointestinal tract. GEP-NETs incidence has been steadily increasing over the past decades, in parallel with the increasing incidence of the metabolic syndrome (MetS). It is not yet fully known whether the MetS components (such as obesity, dyslipidemia and type 2 diabetes) could be involved in the etiology of GEP-NETs or could influence their outcomes. In this review, a panel of experts of the Italian Association of Medical Oncology (AIOM), Italian Association of Medical Diabetologists (AMD), Italian Society of Endocrinology…

ConsensusSettore MED/06 - Oncologia MedicaGEP-NET progressionMetabolic disordersHematologyMedical OncologyMetabolic syndromeNOGEP-NET survivalPancreatic NeoplasmsNeuroendocrine Tumorsgastroenteropancreatic neuroendocrine tumors; gep-net progression; gep-net survival; metabolic disorders; metabolic syndrome; consensus; humans; medical oncology; diabetes mellitus; type 2; intestinal neoplasms; neuroendocrine tumors; pancreatic neoplasms; stomach neoplasmsOncologyGEP-NET progression; GEP-NET survival; Gastroenteropancreatic neuroendocrine tumors; Metabolic disorders; Metabolic syndromeDiabetes Mellitus Type 2Stomach NeoplasmsIntestinal NeoplasmsDiabetes MellitusHumansLS4_3Gastroenteropancreatic neuroendocrine tumorsType 2
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The indexing of persons in news sequences using audio-visual data

2004

We describe a video indexing system that automatically searches for a specific person in a news sequence. The proposed approach combines audio and video confidence values extracted from speaker and face recognition analysis. The system also incorporates a shot selection module that seeks for anchors, where the person on the scene is likely speaking. The system has been extensively tested on several news sequences with very good recognition rates.

Contextual image classificationComputer scienceSpeech recognitionSearch engine indexingComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONSelection (linguistics)Speaker recognitionAudio signal processingcomputer.software_genrecomputerFacial recognition systemElectronic mail2003 IEEE International Conference on Acoustics, Speech, and Signal Processing, 2003. Proceedings. (ICASSP '03).
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