12 research outputs found
Deep learning for detection and segmentation of artefact and disease instances in gastrointestinal endoscopy
The Endoscopy Computer Vision Challenge (EndoCV) is a crowd-sourcing initiative to address eminent problems in developing
reliable computer aided detection and diagnosis endoscopy systems and suggest a pathway for clinical translation
of technologies. Whilst endoscopy is a widely used diagnostic and treatment tool for hollow-organs, there are several core
challenges often faced by endoscopists, mainly: 1) presence of multi-class artefacts that hinder their visual interpretation, and
2) difficulty in identifying subtle precancerous precursors and cancer abnormalities. Artefacts often affect the robustness of
deep learning methods applied to the gastrointestinal tract organs as they can be confused with tissue of interest. EndoCV2020
challenges are designed to address research questions in these remits. In this paper, we present a summary of methods
developed by the top 17 teams and provide an objective comparison of state-of-the-art methods and methods designed by
the participants for two sub-challenges: i) artefact detection and segmentation (EAD2020), and ii) disease detection and
segmentation (EDD2020). Multi-center, multi-organ, multi-class, and multi-modal clinical endoscopy datasets were compiled
for both EAD2020 and EDD2020 sub-challenges. The out-of-sample generalization ability of detection algorithms was also
evaluated. Whilst most teams focused on accuracy improvements, only a few methods hold credibility for clinical usability. The
best performing teams provided solutions to tackle class imbalance, and variabilities in size, origin, modality and occurrences
by exploring data augmentation, data fusion, and optimal class thresholding techniques
Measurement of the Nucleus Charged-Current Double-Differential Cross Section at 2.4 GeV using NOvA
The inclusive electron neutrino charged-current cross section is measured in
the NOvA near detector using protons-on-target (POT) in the
NuMI beam. The sample of GeV electron neutrino interactions is the largest
analyzed to date and is limited by 17\% systematic rather than the
7.4\% statistical uncertainties. The double-differential cross section
in final-state electron energy and angle is presented for the first time,
together with the single-differential dependence on (squared
four-momentum transfer) and energy, in the range 1 GeV 6 GeV.
Detailed comparisons are made to the predictions of the GENIE, GiBUU, NEUT, and
NuWro neutrino event generators. The data do not strongly favor a model over
the others consistently across all three cross sections measured, though some
models have especially good or poor agreement in the single differential cross
section vs.
SHREC'16 track: Shape retrieval of low-cost RGB-D captures
RGB-D cameras allow to capture digital representations of objects in an easy and inexpensive way. Such technology enables ordinary users to capture everyday object into digital 3D representations. In this context, we present a track for the Shape Retrieval Contest, which focus on objects digitized using the latest version of Microsoft Kinect, namely, Kinect One. The proposed, track encompasses a dataset of two hundred objects and respective classification.info:eu-repo/semantics/publishedVersio
Video resolution enhancement by using discrete and stationary wavelet transforms with illumination compensation
Modelling and optimisation of effective hybridisation model for time‐series data forecasting
Intravenous Administration of Butaphosphan and Cyanocobalamin Combination to Late-Pregnant Dairy Cows Reduces Their Insulin Resistance After Calving
Measurement of the νe -Nucleus Charged-Current Double-Differential Cross Section at «eν »=2.4 GeV Using NOvA
© 2023 authors. Published by the American Physical Society.The inclusive electron neutrino charged-current cross section is measured in the NOvA near detector using 8.02×1020 protons-on-target in the NuMI beam. The sample of GeV electron neutrino interactions is the largest analyzed to date and is limited by ≃17% systematic rather than the ≃7.4% statistical uncertainties. The double-differential cross section in final-state electron energy and angle is presented for the first time, together with the single-differential dependence on Q2 (squared four-momentum transfer) and energy, in the range 1 GeV≤Eν<6 GeV. Detailed comparisons are made to the predictions of the GENIE, GiBUU, NEUT, and NuWro neutrino event generators. The data do not strongly favor a model over the others consistently across all three cross sections measured, though some models have especially good or poor agreement in the single differential cross section vs Q2