Search results for " Computer vision"
showing 10 items of 352 documents
Chemical Bath Deposition as a Simple Way to Grow Isolated and Coalesced ZnO Nanorods for Light-Emitting Diodes Fabrication
2018
A way to grow and characterize isolated and coalesced ZnO nanorods on $p$ -GaN/sapphire structure is presented. Chemical bath deposition can be used to grow ZnO nanorods of device-quality, simply controlling the duration time of the growth process and the concentration of the nutrient solution in the bath. Increasing the duration of the process, as well as the concentration of the solution, leads to compact and sound layers instead of separated nanorods. However, too high concentrations stop the growth process. Light-emitting diodes fabricated on these ZnO-p-GaN heterostructure have a peak of electroluminescence at 400 nm and exhibit interesting electrical and optical properties. Optical po…
hidden markov random fields and cuckoo search method for medical image segmentation
2020
Segmentation of medical images is an essential part in the process of diagnostics. Physicians require an automatic, robust and valid results. Hidden Markov Random Fields (HMRF) provide powerful model. This latter models the segmentation problem as the minimization of an energy function. Cuckoo search (CS) algorithm is one of the recent nature-inspired meta-heuristic algorithms. It has shown its efficiency in many engineering optimization problems. In this paper, we use three cuckoo search algorithm to achieve medical image segmentation.
Unsupervised learning of category-specific symmetric 3D keypoints from point sets
2020
Lecture Notes in Computer Science, 12370
3D landmark detection for augmented reality based otologic procedures
2019
International audience; Ear consists of the smallest bones in the human body and does not contain significant amount of distinct landmark points that may be used to register a preoperative CT-scan with the surgical video in an augmented reality framework. Learning based algorithms may be used to help the surgeons to identify landmark points. This paper presents a convolutional neural network approach to landmark detection in preoperative ear CT images and then discusses an augmented reality system that can be used to visualize the cochlear axis on an otologic surgical video.
The Large Area Detector of LOFT: the Large Observatory for X-ray Timing
2014
LOFT (Large Observatory for X-ray Timing) is one of the five candidates that were considered by ESA as an M3 mission (with launch in 2022-2024) and has been studied during an extensive assessment phase. It is specifically designed to perform fast X-ray timing and probe the status of the matter near black holes and neutron stars. Its pointed instrument is the Large Area Detector (LAD), a 10 m 2 -class instrument operating in the 2-30keV range, which holds the capability to revolutionise studies of variability from X-ray sources on the millisecond time scales. The LAD instrument has now completed the assessment phase but was not down-selected for launch. However, during the assessment, most o…
LOFT: the Large Observatory For X-ray Timing
2012
The LOFT mission concept is one of four candidates selected by ESA for the M3 launch opportunity as Medium Size missions of the Cosmic Vision programme. The launch window is currently planned for between 2022 and 2024. LOFT is designed to exploit the diagnostics of rapid X-ray flux and spectral variability that directly probe the motion of matter down to distances very close to black holes and neutron stars, as well as the physical state of ultra-dense matter. These primary science goals will be addressed by a payload composed of a Large Area Detector (LAD) and a Wide Field Monitor (WFM). The LAD is a collimated (<1 degree field of view) experiment operating in the energy range 2-50 keV,…
Convergence Analysis of Distributed Set-Valued Information Systems
2016
This paper focuses on the convergence of information in distributed systems of agents communicating over a network. The information on which the convergence is sought is not rep- resented by real numbers, as often in the literature, rather by sets. The dynamics of the evolution of information across the net- work is accordingly described by set-valued iterative maps. While the study of convergence of set-valued iterative maps is highly complex in general, this paper focuses on Boolean maps, which are comprised of arbitrary combinations of unions, intersections, and complements of sets. For these important class of systems, we provide tools to study both global and local convergence. A distr…
123D Catch: efficiency, accuracy, constraints and limitations in architectural heritage field
2013
Today, the accurate and detailed reconstruction of geometric models of real objects has become a common process. The diffusion of Image-based 3D modeling techniques, through image-based free, low cost and open source software, have increased drastically in the past few years, especially in the sector of Cultural Heritage (Architecture, Archeology, Urban planning). Nevertheless, web based software (ARC3D, 123D Catch, Hyp3D, my3Dscanner) offer another opportunity respect the desktop systems: they use the power of cloud computing to carry out a semi-automatic data processing. In this way is overcome the considerably slowing-down of the computer of hardware-heavy approaches. Our research inves…
A Non-Local Mode-I Cohesive Model for Ascending Thoracic Aorta Dissections (ATAD)
2018
This paper presents a non-local interface mechanical model to describe aortic dissection. In this regard, the mode-I debonding problem based on a cohesive zone modeling is endowed with non-local terms to include long-range interactions that are present in multi-layered biological tissue. Such non-local effects are related to the collagen fibers that transmit forces between non-adjacent elements. Numerical simulations are provided with different values of the non-local parameters in order to show the effect of the non-locality during the debonding processes.
Predicting the availability of users' devices in Decentralized Online Social Networks
2018
The understanding of the user temporal behavior is a crucial aspect for all those systems that rely on user resources for daily operations, such as decentralized online social networks (DOSNs). Indeed, DOSNs exploit the devices of their users to take on and share the tasks needed to provide services such as storing the published data. In the last years, the increasing popularity of DOSN services has changed the way of how people interact with each other by enabling users to connect to these services at any time by using their personal devices (such as notebooks or smartphones). As a result, the availability of data in these systems is strongly affected (or reflected) by the temporal behavio…