Search results for " image processing."
showing 10 items of 2265 documents
Impact of textual data augmentation on linguistic pattern extraction to improve the idiomaticity of extractive summaries
2021
International audience; The present work aims to develop a text summarisation system for financial texts with a focus on the fluidity of the target language. Linguistic analysis shows that the process of writing summaries should take into account not only terminological and collocational extraction, but also a range of linguistic material referred to here as the "support lexicon", that plays an important role in the cognitive organisation of the field. On this basis, this paper highlights the relevance of pre-training the CamemBERT model on a French financial dataset to extend its domainspecific vocabulary and fine-tuning it on extractive summarisation. We then evaluate the impact of textua…
Optimal configuration for size-based burst assembly algorithms at the edge node for video traffic transmissions over OBS networks
2008
Optical burst switching (OBS) has been proposed to be a technology for implementing the next generation optical Internet. In this architecture, burst assembly algorithms have an important influence in the pattern traffic that characteristic this sort of optical networks. On the other hand, traffic coming from new applications (such as video on demand, Voice over IP, online gaming or Grid computing) that have real time and bandwidth constraints, has been experimented a rapid increment. Consequently, we consider important to evaluate the performance of traffic from real time applications over OBS networks. In this paper, we evaluate the effects of implementing a size-based burst assembly sche…
LocalRec 2018 workshop report the second ACM SIGSPATIAL workshop on recommendations for location-based services and social networks * Seattle, Washin…
2019
Driven by technological advances in hardware (positioning systems, environmental sensors), software (standards, tools, network services), and aided by various open movements (open, linked, government data) and the ever-growing mentality of sharing for the greater good (crowdsourcing, crowdfunding, collaborative and volunteered geographic information), the amount of available geo-referenced data has seen dramatic explosion over the past few years. Human activities generate data and traces that are now often transparently annotated with location and contextual information. At the same time, it has become easier than ever to collect and combine rich and diverse information about locations. Exp…
On solving single elevator-like problems using a learning automata-based paradigm
2020
This paper concentrates on a host of problems with characteristics similar to those that are related to moving elevators within a building. These are referred to as Elevator-like problems (ELPs), and their common phenomena will be expanded on in the body of the paper. We shall resolve ELPs using a subfield of AI, namely the field of learning automata (LA). Rather than working with the well-established mathematical formulations of the field, our intention is to use these tools to tackle ELPs, and in particular, those that deal with single “elevators” moving between “floors”. ELPs have not been tackled before using AI. In a simplified domain, the ELP involves the problem of optimizing the sch…
ELM Regularized Method for Classification Problems
2016
Extreme Learning Machine (ELM) is a recently proposed algorithm, efficient and fast for learning the parameters of single layer neural structures. One of the main problems of this algorithm is to choose the optimal architecture for a given problem solution. To solve this limitation several solutions have been proposed in the literature, including the regularization of the structure. However, to the best of our knowledge, there are no works where such adjustment is applied to classification problems in the presence of a non-linearity in the output; all published works tackle modelling or regression problems. Our proposal has been applied to a series of standard databases for the evaluation o…
Genetic Algorithm Modeling for Photocatalytic Elimination of Impurity in Wastewater
2019
The existence of C.I. Acid Yellow 23 (AY23) in water causes a great danger to people and society. Here, we suggest an advanced technique which predicts the photochemical deletion of AY23. The genetic algorithm (GA) technique is suggested in order to predict the photocatalytic removal of AY23 by implementing the Ag-TiO\(_{2}\) nanoparticles provided under appropriate conditions.
Phase-shifting Gabor holography.
2009
We present a modified Gabor-like setup able to recover the complex amplitude distribution of the object wavefront from a set of inline recorded holograms. The proposed configuration is characterized by the insertion of a condenser lens and a spatial light modulator (SLM) into the classical Gabor configuration. The phase shift is introduced by the SLM that modulates the central spot (dc term) in an intermediate plane, without an additional reference beam. Experimental results validate the proposed method and produce superior results to the Gabor method.
Off-axis digital holographic multiplexing for rapid wavefront acquisition and processing
2020
Off-axis holographic multiplexing involves capturing several complex wavefronts, each encoded into off-axis holograms with different interference fringe orientations, simultaneously, with a single camera acquisition. Thus, the multiplexed off-axis hologram can capture several wavefronts at once, where each one encodes different information from the sample, using the same number of pixels typically required for acquiring a single conventional off-axis hologram encoding only one sample wavefront. This gives rise to many possible applications, with focus on acquisition of dynamic samples, with hundreds of scientific papers already published in the last decade. These include field-of-view multi…
Superresolved common-path phase-shifting digital inline holographic microscopy using a spatial light modulator.
2012
Common-path phase-shifting lensless holographic microscopy has been recently proposed as a novel approach capable of high numerical aperture imaging in a lensless digital inline holographic microscopy layout [Opt. Lett.35, 3919 (2010)]. Here we present proof-of-concept validation for improving the resolution limit imposed by diffraction in such a setup. This is accomplished by shifting the phase lens displayed at the spatial light modulator, which moves the illumination point source to different off-axis positions. For each off-axis position, a set of inline phase-shifted holograms are recorded by the digital sensor and stored at the computer’s memory for later digital postprocessing. As a …
Quantitative Phase Imaging in Microscopy Using a Spatial Light Modulator
2010
In this chapter, we present a new method capable of recovery of the quantitative phase information of microscopic samples. Essentially, a spatial light modulator (SLM) and digital image processing are the basics to extract the sample’s phase distribution. The SLM produces a set of misfocused images of the input sample at the CCD plane by displaying a set of lenses with different power at the SLM device. The recorded images are then numerically processed to retrieve phase information. Computations are based on the wave propagation equation and lead to a complex amplitude image containing information of both amplitude and phase distributions of the input sample diffracted wave front. The prop…