24,841 research outputs found
Graph-Based Classification of Omnidirectional Images
Omnidirectional cameras are widely used in such areas as robotics and virtual
reality as they provide a wide field of view. Their images are often processed
with classical methods, which might unfortunately lead to non-optimal solutions
as these methods are designed for planar images that have different geometrical
properties than omnidirectional ones. In this paper we study image
classification task by taking into account the specific geometry of
omnidirectional cameras with graph-based representations. In particular, we
extend deep learning architectures to data on graphs; we propose a principled
way of graph construction such that convolutional filters respond similarly for
the same pattern on different positions of the image regardless of lens
distortions. Our experiments show that the proposed method outperforms current
techniques for the omnidirectional image classification problem
Historical Evolution of theWave Resource and Energy Production off the Chilean Coast over the 20th Century
The wave energy resource in the Chilean coast shows particularly profitable characteristics for wave energy production, with relatively high mean wave power and low inter-annual resource variability. This combination is as interesting as unusual, since high energetic locations are usually also highly variable, such as the west coast of Ireland. Long-term wave resource variations are also an important aspect when designing wave energy converters (WECs), which are often neglected in resource assessment. The present paper studies the long-term resource variability of the Chilean coast, dividing the 20th century into five do-decades and analysing the variations between the different do-decades. To that end, the ERA20C reanalysis of the European Centre for Medium-Range Weather Forecasts is calibrated versus the ERA-Interim reanalysis and validated against buoy measurements collected in different points of the Chilean coast. Historical resource variations off the Chilean coast are compared to resource variations off the west coast in Ireland, showing a significantly more consistent wave resource. In addition, the impact of historical wave resource variations on a realistic WEC, similar to the Corpower device, is studied, comparing the results to those obtained off the west coast of Ireland. The annual power production off the Chilean coast is demonstrated to be remarkably more regular over the 20th century, with variations of just 1% between the different do-decades.The authors with the Centre for Ocean Energy Research in Maynooth University are supported by Science Foundation Ireland under Grant No. 13/IA/1886. It is also supported by grant CGL2016-76561-R, MINECO/ERDF, UE. Additional funding was received from the University of Basque Country (UPV/EHU, GIU17/002)
Interferometric Optical Tomography
Embodiments of the present disclosure provide systems and methods for constructing a profile of sample object. Briefly described, in architecture, one embodiment of the system, among others, can be implemented as follows. An interferometer device is used to collect interference images of a sample object at a sequence of angles around the sample object. Accordingly, a controller device rotates the sample object to enable acquisition of the interference images; and a projection generator produces projections of the sample object from the interference images at the sequence of angles. Further, a tomographic device constructs the profile of the optical device from the projections of the interference images. The profile is capable of characterizing small index variations of less than 1x10?4. Other systems and methods are also included.Georgia Tech Research Corporatio
Topographically specific effects of ELF-1 on retinal axon guidance in vitro and retinal axon mapping in vivo
Peer reviewedPublisher PD
Sparse-to-Continuous: Enhancing Monocular Depth Estimation using Occupancy Maps
This paper addresses the problem of single image depth estimation (SIDE),
focusing on improving the quality of deep neural network predictions. In a
supervised learning scenario, the quality of predictions is intrinsically
related to the training labels, which guide the optimization process. For
indoor scenes, structured-light-based depth sensors (e.g. Kinect) are able to
provide dense, albeit short-range, depth maps. On the other hand, for outdoor
scenes, LiDARs are considered the standard sensor, which comparatively provides
much sparser measurements, especially in areas further away. Rather than
modifying the neural network architecture to deal with sparse depth maps, this
article introduces a novel densification method for depth maps, using the
Hilbert Maps framework. A continuous occupancy map is produced based on 3D
points from LiDAR scans, and the resulting reconstructed surface is projected
into a 2D depth map with arbitrary resolution. Experiments conducted with
various subsets of the KITTI dataset show a significant improvement produced by
the proposed Sparse-to-Continuous technique, without the introduction of extra
information into the training stage.Comment: Accepted. (c) 2019 IEEE. Personal use of this material is permitted.
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this work in other work
Labour Migration From EaP Countries to the EU - Assessment of Costs and Benefits and Proposals for Better Labour Market Matching
It is reasonable to expect steady migratory flows from Eastern Parntership nations in the future, and that migration would be a desirable phenomenon (based on the so-far advantageous migratory flows from EaP nations). They cause no negative wage effects on native workers
Overcoming the Challenges Associated with Image-based Mapping of Small Bodies in Preparation for the OSIRIS-REx Mission to (101955) Bennu
The OSIRIS-REx Asteroid Sample Return Mission is the third mission in NASA's
New Frontiers Program and is the first U.S. mission to return samples from an
asteroid to Earth. The most important decision ahead of the OSIRIS-REx team is
the selection of a prime sample-site on the surface of asteroid (101955) Bennu.
Mission success hinges on identifying a site that is safe and has regolith that
can readily be ingested by the spacecraft's sampling mechanism. To inform this
mission-critical decision, the surface of Bennu is mapped using the OSIRIS-REx
Camera Suite and the images are used to develop several foundational data
products. Acquiring the necessary inputs to these data products requires
observational strategies that are defined specifically to overcome the
challenges associated with mapping a small irregular body. We present these
strategies in the context of assessing candidate sample-sites at Bennu
according to a framework of decisions regarding the relative safety,
sampleability, and scientific value across the asteroid's surface. To create
data products that aid these assessments, we describe the best practices
developed by the OSIRIS-REx team for image-based mapping of irregular small
bodies. We emphasize the importance of using 3D shape models and the ability to
work in body-fixed rectangular coordinates when dealing with planetary surfaces
that cannot be uniquely addressed by body-fixed latitude and longitude.Comment: 31 pages, 10 figures, 2 table
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