Search results for "Images"
showing 10 items of 460 documents
Extending the Unmixing methods to Multispectral Images
2021
In the past few decades, there has been intensive research concerning the Unmixing of hyperspectral images. Some methods such as NMF, VCA, and N-FINDR have become standards since they show robustness in dealing with the unmixing of hyperspectral images. However, the research concerning the unmixing of multispectral images is relatively scarce. Thus, we extend some unmixing methods to the multispectral images. In this paper, we have created two simulated multispectral datasets from two hyperspectral datasets whose ground truths are given. Then we apply the unmixing methods (VCA, NMF, N-FINDR) to these two datasets. By comparing and analyzing the results, we have been able to demonstrate some…
multimodal and multi-criteria analysis for the expertise and locating faults in modern electrical components
2017
The purpose of this manuscript is to exhibit the research work solving the issue of data processing stem from defect localization techniques. This step being decisive in the failure analysis process, scientists have to harness data coming from light emission and laser techniques. Nevertheless, this analysis process is sequential and only depends on the expert’s decision. This factor leads to a not quantified probability of localization. Consequently to solve these issues, a multimodaland multicriteria analysis has been developped, taking advantage of the heterogeneous and complementary nature of light emission and laser probing techniques. This kind of process is based on advanced level too…
Vehicle localization based on scene perception
2021
The vision-based vehicle localization task is tackled as an image-based place recognition problem in this thesis. As image representation is an important process to place recognition, we proposed place recognition methods focusing on increasing the quality of image features. First, the dynamic object removal step is proposed to remove the dynamic objects, such as vehicles and pedestrians, of an image by semantic segmentation method and restore their background information by image inpainting method. Second, reducing instead of removing the noisy information of an image is proposed. Using the image blurring method to reduce the image noise, the performance of place recognition is improved wi…
Destructuration of typical Sicilian calcarenites
2010
The paper discusses some interesting features of Sicilian fine grain calcarenites. Uniaxial, triaxial, oedometer and isotropic compression tests were undertaken on intact specimens of two types of calcarenite in order to investigate their mechanical characteristics. It was found that the strength and deformability is significantly influenced by the structure (fabric and bonding) and by the destructuration processes. A better understanding of fracture development behavior is gained through a combination of acoustic emission and photographic monitoring on non-homogeneous samples with natural pre-existing heterogeneities due to cementation or to density. The results show that the destructurati…
Rural futures in developed economies: The case of Finland
2015
Abstract This study presents four possible images of rural futures in Finland: decentralized bio-economy, colonial countryside, museum countryside and rural business islets. They are distilled through literature reviews, futures workshops and futures tables. Alternative specifications of structures, contents and agencies result in highly divergent states of key dimensions and, consequently, divergent rural futures. This diversity challenges the conventional public wisdom or intellectual monoculture that considers decay as the only future for rural areas. Key challenges in crafting plausible but divergent futures images are finding an appropriate level of abstraction or “flight altitude”, es…
A virtual laboratory designed for teaching diffractive lenses
2010
[EN] We present a virtual laboratory generated in Matlab GuiQc (Graphical User Interface) for its use in Optics courses as an informatic tool for teaching the focusing properties of a diffractive lens. This Gui allows the students to learn easily and rapidly about the influence on the focal volume of the lens construction parameters. As an example in this work we analyze fractal diffractive lenses because we found that fractal geometry is a highly motivating topic for students since it is related to a wide range of scientific and technological phenomena.
Editing and the Shadow of the Folio: On the Textual Integrity of The Taming of a Shrew (1594)
2015
No abstract
Fusion of multimodal data by combining the uncertainty and perception models
2019
The general idea is to use together heterogeneous multiple information on the same problem tainted by imperfections and coming from several sources in order to improve the knowledge of a given situation. Appropriate visualization of the images to aid in decision making using the perceptual information carried by the salience maps.
A Combined Fuzzy and Probabilistic Data Descriptor for Distributed CBIR
2009
With the wide diffusion of digital image acquisition devices, the cost of managing hundreds of digital images is quickly increasing. Currently, the main way to search digital image libraries is by keywords given by the user. However, users usually add ambiguos keywords for large set of images. A content-based system intended to automatically find a query image, or similar images, within the whole collection is needed. In our work we address the scenario where medical image collections, which nowadays are rapidly expanding in quantity and heterogeneity, are shared in a distributed system to support diagnostic and preventive medicine. Our goal is to produce an efficient content-based descript…
Unsupervised tissue classification of brain MR images for voxel-based morphometry analysis
2016
In this article, a fully unsupervised method for brain tissue segmentation of T1-weighted MRI 3D volumes is proposed. The method uses the Fuzzy C-Means (FCM) clustering algorithm and a Fully Connected Cascade Neural Network (FCCNN) classifier. Traditional manual segmentation methods require neuro-radiological expertise and significant time while semiautomatic methods depend on parameter's setup and trial-and-error methodologies that may lead to high intraoperator/interoperator variability. The proposed method selects the most useful MRI data according to FCM fuzziness values and trains the FCCNN to learn to classify brain’ tissues into White Matter, Gray Matter, and Cerebro-Spinal Fluid in …