6,690 research outputs found
Multi-layer Architecture For Storing Visual Data Based on WCF and Microsoft SQL Server Database
In this paper we present a novel architecture for storing visual data.
Effective storing, browsing and searching collections of images is one of the
most important challenges of computer science. The design of architecture for
storing such data requires a set of tools and frameworks such as SQL database
management systems and service-oriented frameworks. The proposed solution is
based on a multi-layer architecture, which allows to replace any component
without recompilation of other components. The approach contains five
components, i.e. Model, Base Engine, Concrete Engine, CBIR service and
Presentation. They were based on two well-known design patterns: Dependency
Injection and Inverse of Control. For experimental purposes we implemented the
SURF local interest point detector as a feature extractor and -means
clustering as indexer. The presented architecture is intended for content-based
retrieval systems simulation purposes as well as for real-world CBIR tasks.Comment: Accepted for the 14th International Conference on Artificial
Intelligence and Soft Computing, ICAISC, June 14-18, 2015, Zakopane, Polan
Ellipsometric measurements of the refractive indices of linear alkylbenzene and EJ-301 scintillators from 210 to 1000 nm
We report on ellipsometric measurements of the refractive indices of LAB-PPO,
Nd-doped LAB-PPO and EJ-301 scintillators to the nearest +/-0.005, in the
wavelength range 210-1000 nm.Comment: 7 pages, 4 figure
A Review of Rare Pion and Muon Decays
After a decade of no measurements of pion and muon rare decays, PIBETA, a new
experimental program is producing its first results. We report on a new
experimental study of the pion beta decay, Pi(+) -> Pi(0) e(+) Nu, the Pi(e2
gamma) radiative decay, Pi(+) -> e(+) Nu Gamma, and muon radiative decay, Mu ->
e Nu Gamma. The new results represent four- to six-fold improvements in
precision over the previous measurements. Excellent agreement with Standard
Model predictions is observed in all channels except for one kinematic region
of the Pi(e2 gamma) radiative decay involving energetic photons and
lower-energy positrons.Comment: 10 pages, 6 figures, 2 tables, invited talk presented at MESON 2004,
8th Int'l. Workshop on Meson Production, Properties and Interaction, Krakow,
Poland 4-8 June 200
Target Mass Monitoring and Instrumentation in the Daya Bay Antineutrino Detectors
The Daya Bay experiment measures sin^2 2{\theta}_13 using functionally
identical antineutrino detectors located at distances of 300 to 2000 meters
from the Daya Bay nuclear power complex. Each detector consists of three nested
fluid volumes surrounded by photomultiplier tubes. These volumes are coupled to
overflow tanks on top of the detector to allow for thermal expansion of the
liquid. Antineutrinos are detected through the inverse beta decay reaction on
the proton-rich scintillator target. A precise and continuous measurement of
the detector's central target mass is achieved by monitoring the the fluid
level in the overflow tanks with cameras and ultrasonic and capacitive sensors.
In addition, the monitoring system records detector temperature and levelness
at multiple positions. This monitoring information allows the precise
determination of the detectors' effective number of target protons during data
taking. We present the design, calibration, installation and in-situ tests of
the Daya Bay real-time antineutrino detector monitoring sensors and readout
electronics.Comment: 22 pages, 20 figures; accepted by JINST. Changes in v2: minor
revisions to incorporate editorial feedback from JINS
Scene Coordinate Regression with Angle-Based Reprojection Loss for Camera Relocalization
Image-based camera relocalization is an important problem in computer vision
and robotics. Recent works utilize convolutional neural networks (CNNs) to
regress for pixels in a query image their corresponding 3D world coordinates in
the scene. The final pose is then solved via a RANSAC-based optimization scheme
using the predicted coordinates. Usually, the CNN is trained with ground truth
scene coordinates, but it has also been shown that the network can discover 3D
scene geometry automatically by minimizing single-view reprojection loss.
However, due to the deficiencies of the reprojection loss, the network needs to
be carefully initialized. In this paper, we present a new angle-based
reprojection loss, which resolves the issues of the original reprojection loss.
With this new loss function, the network can be trained without careful
initialization, and the system achieves more accurate results. The new loss
also enables us to utilize available multi-view constraints, which further
improve performance.Comment: ECCV 2018 Workshop (Geometry Meets Deep Learning
Determination of Lubricant Bulk Modulus in Metal Forming by Means of a Simple Laboratory Test and Inverse FEM Analysis
Effect of Achromycin Ointment on Healing Following Periodontal Surgery
Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/141040/1/jper0368.pd
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