Hexagonal structure for intelligent vision

Using hexagonal grids to represent digital images have been studied for more than 40 years. Increased processing capabilities of graphic devices and recent improvements in CCD technology have made hexagonal sampling attractive for practical applications and brought new interests on this topic. The hexagonal structure is considered to be preferable to the rectangular structure due to its higher sampling efficiency, consistent connectivity and higher angular resolution and is even proved to be superior to square structure in many applications. Since there is no mature hardware for hexagonal-based image capture and display, square to hexagonal image conversion has to be done before hexagonal-based image processing. Although hexagonal image representation and storage has not yet come to a standard, experiments based on existing hexagonal coordinate systems have never ceased. In this paper, we firstly introduced general reasons that hexagonally sampled images are chosen for research. Then, typical hexagonal coordinates and addressing schemes, as well as hexagonal based image processing and applications, are fully reviewed. © 2005 IEEE

Finding strong lenses in CFHTLS using convolutional neural networks

We train and apply convolutional neural networks, a machine learning technique developed to learn from and classify image data, to Canada-France-Hawaii Telescope Legacy Survey (CFHTLS) imaging for the identification of potential strong lensing systems. An ensemble of four convolutional neural networks was trained on images of simulated galaxy-galaxy lenses. The training sets consisted of a total of 62,406 simulated lenses and 64,673 non-lens negative examples generated with two different methodologies. The networks were able to learn the features of simulated lenses with accuracy of up to 99.8% and a purity and completeness of 94-100% on a test set of 2000 simulations. An ensemble of trained networks was applied to all of the 171 square degrees of the CFHTLS wide field image data, identifying 18,861 candidates including 63 known and 139 other potential lens candidates. A second search of 1.4 million early type galaxies selected from the survey catalog as potential deflectors, identified 2,465 candidates including 117 previously known lens candidates, 29 confirmed lenses/high-quality lens candidates, 266 novel probable or potential lenses and 2097 candidates we classify as false positives. For the catalog-based search we estimate a completeness of 21-28% with respect to detectable lenses and a purity of 15%, with a false-positive rate of 1 in 671 images tested. We predict a human astronomer reviewing candidates produced by the system would identify ~20 probable lenses and 100 possible lenses per hour in a sample selected by the robot. Convolutional neural networks are therefore a promising tool for use in the search for lenses in current and forthcoming surveys such as the Dark Energy Survey and the Large Synoptic Survey Telescope.Comment: 16 pages, 8 figures. Accepted by MNRA

Studying Sun-Planet Connections Using the Heliophysics Integrated Observatory (HELIO)

The Heliophysics Integrated Observatory (HELIO) is a software infrastructure involving a collection of web services, heliospheric data sources (e.g., solar, planetary, etc.), and event catalogues – all of which are accessible through a unified front end. In this paper we use the HELIO infrastructure to perform three case studies based on solar events that propagate through the heliosphere. These include a coronal mass ejection that intersects both Earth and Mars, a solar energetic particle event that crosses the orbit of Earth, and a high-speed solar wind stream, produced by a coronal hole, that is observed in situ at Earth (L1). A ballistic propagation model is run as one of the HELIO services and used to model these events, predicting if they will interact with a spacecraft or planet and determining the associated time of arrival. The HELIO infrastructure streamlines the method used to perform these kinds of case study by centralising the process of searching for and visualising data, indicating interesting features on the solar disk, and finally connecting remotely observed solar features with those detected by in situ solar wind and energetic particle instruments. HELIO represents an important leap forward in European heliophysics infrastructure by bridging the boundaries of traditional scientific domains

Edge Detection on Spiral Architecture: an Overview

Abstract Gradient-based edge detection is a straightforward method to identify the edge points in the origina

Direct generation of optical vortices

A detailed scheme is established for the direct generation of optical vortices, signifying light endowed with orbital angular momentum. In contrast to common techniques based on the tailored conversion of the wave front in a conventional beam, this method provides for the direct spontaneous emission of photons with the requisite field structure. This form of optical emission results directly from the electronic relaxation of a delocalized exciton state that is supported by a ringlike array of three or more nanoscale chromophores. An analysis of the conditions leads to a general formulation revealing a requirement for the array structure to adhere to one of a restricted set of permissible symmetry groups. It is shown that the coupling between chromophores within each array leads to an energy level splitting of the exciton structure, thus providing for a specific linking of exciton phase and emission wavelength. For emission, arrays conforming to one of the given point-group families’ doubly degenerate excitons exhibit the specific phase characteristics necessary to support vortex emission. The highest order of exciton symmetry, corresponding to the maximum magnitude of electronic orbital angular momentum supported by the ring, provides for the most favored emission. The phase properties of the emission produced by the relaxation of such excitons are exhibited on plots which reveal the azimuthal phase progression around the ring, consistent with vortex emission. It is proven that emission of this kind produces electromagnetic fields that map with complete fidelity onto the phase structure of a Laguerre-Gaussian optical mode with the corresponding topological charge. The prospect of direct generation paves the way for practicable devices that need no longer rely on the modification of a conventional laser beam by a secondary optical element. Moreover, these principles hold promise for the development of a vortex laser, also based on nanoscale exciton decay, enabling the production of coherent radiation with a tailor-made helical wave front

Increasing the Dependability of VLSI Systems Through Early Detection of Fugacious Faults

Technology advances provide a myriad of advantages for VLSI systems, but also increase the sensitivity of the combinational logic to different fault profiles. Shorter and shorter faults which up to date had been filtered, named as fugacious faults, require new attention as they are considered a feasible sign of warning prior to potential failures. Despite their increasing impact on modern VLSI systems, such faults are not largely considered today by the safety industry. Their early detection is however critical to enable an early evaluation of potential risks for the system and the subsequent deployment of suitable failure avoidance mechanisms. For instance, the early detection of fugacious faults will provide the necessary means to extend the mission time of a system thanks to the temporal avoidance of aging effects. Because classical detection mechanisms are not suited to cope with such fugacious faults, this paper proposes a method specifically designed to detect and diagnose them. Reported experiments will show the feasibility and interest of the proposal.This work has been funded by the Spanish Ministry of Economy ARENES project (TIN2012-38308-C02—01).Espinosa García, J.; Andrés Martínez, DD.; Gil, P. (2015). Increasing the Dependability of VLSI Systems Through Early Detection of Fugacious Faults. IEEE Computer Society - Conference Publishing Services (CPS). https://doi.org/10.1109/EDCC.2015.13

Deep Learning Paradigm and Its Bias for Coronary Artery Wall Segmentation in Intravascular Ultrasound Scans: A Closer Look

Background and motivation: Coronary artery disease (CAD) has the highest mortality rate; therefore, its diagnosis is vital. Intravascular ultrasound (IVUS) is a high-resolution imaging solution that can image coronary arteries, but the diagnosis software via wall segmentation and quantification has been evolving. In this study, a deep learning (DL) paradigm was explored along with its bias. Methods: Using a PRISMA model, 145 best UNet-based and non-UNet-based methods for wall segmentation were selected and analyzed for their characteristics and scientific and clinical validation. This study computed the coronary wall thickness by estimating the inner and outer borders of the coronary artery IVUS cross-sectional scans. Further, the review explored the bias in the DL system for the first time when it comes to wall segmentation in IVUS scans. Three bias methods, namely (i) ranking, (ii) radial, and (iii) regional area, were applied and compared using a Venn diagram. Finally, the study presented explainable AI (XAI) paradigms in the DL framework. Findings and conclusions: UNet provides a powerful paradigm for the segmentation of coronary walls in IVUS scans due to its ability to extract automated features at different scales in encoders, reconstruct the segmented image using decoders, and embed the variants in skip connections. Most of the research was hampered by a lack of motivation for XAI and pruned AI (PAI) models. None of the UNet models met the criteria for bias-free design. For clinical assessment and settings, it is necessary to move from a paper-to-practice approach

Team MIT Urban Challenge Technical Report

This technical report describes Team MITs approach to theDARPA Urban Challenge. We have developed a novel strategy forusing many inexpensive sensors, mounted on the vehicle periphery,and calibrated with a new cross-­modal calibrationtechnique. Lidar, camera, and radar data streams are processedusing an innovative, locally smooth state representation thatprovides robust perception for real­ time autonomous control. Aresilient planning and control architecture has been developedfor driving in traffic, comprised of an innovative combination ofwell­proven algorithms for mission planning, situationalplanning, situational interpretation, and trajectory control. These innovations are being incorporated in two new roboticvehicles equipped for autonomous driving in urban environments,with extensive testing on a DARPA site visit course. Experimentalresults demonstrate all basic navigation and some basic trafficbehaviors, including unoccupied autonomous driving, lanefollowing using pure-­pursuit control and our local frameperception strategy, obstacle avoidance using kino-­dynamic RRTpath planning, U-­turns, and precedence evaluation amongst othercars at intersections using our situational interpreter. We areworking to extend these approaches to advanced navigation andtraffic scenarios

Formation and evolution of planetary systems: the impact of high angular resolution optical techniques

The direct images of giant extrasolar planets recently obtained around several main sequence stars represent a major step in the study of planetary systems. These high-dynamic range images are among the most striking results obtained by the current generation of high angular resolution instruments, which will be superseded by a new generation of instruments in the coming years. It is therefore an appropriate time to review the contributions of high angular resolution visible/infrared techniques to the rapidly growing field of extrasolar planetary science. During the last 20 years, the advent of the Hubble Space Telescope, of adaptive optics on 4- to 10-m class ground-based telescopes, and of long-baseline infrared stellar interferometry has opened a new viewpoint on the formation and evolution of planetary systems. By spatially resolving the optically thick circumstellar discs of gas and dust where planets are forming, these instruments have considerably improved our models of early circumstellar environments and have thereby provided new constraints on planet formation theories. High angular resolution techniques are also directly tracing the mechanisms governing the early evolution of planetary embryos and the dispersal of optically thick material around young stars. Finally, mature planetary systems are being studied with an unprecedented accuracy thanks to single-pupil imaging and interferometry, precisely locating dust populations and putting into light a whole new family of long-period giant extrasolar planets.Comment: 71 pages, published in Astronomy and Astrophysics Review, online at http://www.springerlink.com/openurl.asp?genre=article&id=doi:10.1007/s00159-009-0028-