Comparison of convolutional neural networks for cloudy optical images reconstruction from single or multitemporal joint SAR and optical images

With the increasing availability of optical and synthetic aperture radar (SAR) images thanks to the Sentinel constellation, and the explosion of deep learning, new methods have emerged in recent years to tackle the reconstruction of optical images that are impacted by clouds. In this paper, we focus on the evaluation of convolutional neural networks that use jointly SAR and optical images to retrieve the missing contents in one single polluted optical image. We propose a simple framework that ease the creation of datasets for the training of deep nets targeting optical image reconstruction, and for the validation of machine learning based or deterministic approaches. These methods are quite different in terms of input images constraints, and comparing them is a problematic task not addressed in the literature. We show how space partitioning data structures help to query samples in terms of cloud coverage, relative acquisition date, pixel validity and relative proximity between SAR and optical images. We generate several datasets to compare the reconstructed images from networks that use a single pair of SAR and optical image, versus networks that use multiple pairs, and a traditional deterministic approach performing interpolation in temporal domain.Comment: 17 page

Classification de Signaux Multidimensionnels Irrégulièrement Echantillonnés

National audienc

Classification de Signaux Multidimensionnels Irrégulièrement Echantillonnés

National audienc

Near-Fatal Multiple Organ Dysfunction Syndrome Induced by Plasmodium malariae

International audienc

Empiric antimicrobial therapy for ventilator-associated pneumonia after brain injury

International audienceIssues regarding recommendations on empiric antimicrobial therapy for ventilator-associated pneumonia (VAP) have emerged in specific populations.To develop and validate a score to guide empiric therapy in brain-injured patients with VAP, we prospectively followed a cohort of 379 brain-injured patients in five intensive care units. The score was externally validated in an independent cohort of 252 brain-injured patients and its extrapolation was tested in 221 burn patients.The multivariate analysis for predicting resistance (incidence 16.4%) showed two independent factors: preceding antimicrobial therapy ≥48 h (p\textless0.001) and VAP onset ≥10 days (p\textless0.001); the area under the receiver operating characteristic curve (AUC) was 0.822 (95% CI 0.770-0.883) in the learning cohort and 0.805 (95% CI 0.732-0.877) in the validation cohort. The score built from the factors selected in multivariate analysis predicted resistance with a sensitivity of 83%, a specificity of 71%, a positive predictive value of 37% and a negative predictive value of 96% in the validation cohort. The AUC of the multivariate analysis was poor in burn patients (0.671, 95% CI 0.596-0.751).Limited-spectrum empirical antimicrobial therapy has low risk of failure in brain-injured patients presenting with VAP before day 10 and when prior antimicrobial therapy lasts \textless48 

Generation and analysis of a 29,745 unique Expressed Sequence Tags from the Pacific oyster (Crassostrea gigas) assembled into a publicly accessible database: the GigasDatabase

Background: Although bivalves are among the most-studied marine organisms because of their ecological role and economic importance, very little information is available on the genome sequences of oyster species. This report documents three large-scale cDNA sequencing projects for the Pacific oyster Crassostrea gigas initiated to provide a large number of expressed sequence tags that were subsequently compiled in a publicly accessible database. This resource allowed for the identification of a large number of transcripts and provides valuable information for ongoing investigations of tissue-specific and stimulus-dependant gene expression patterns. These data are crucial for constructing comprehensive DNA microarrays, identifying single nucleotide polymorphisms and microsatellites in coding regions, and for identifying genes when the entire genome sequence of C. gigas becomes available. Description: In the present paper, we report the production of 40,845 high-quality ESTs that identify 29,745 unique transcribed sequences consisting of 7,940 contigs and 21,805 singletons. All of these new sequences, together with existing public sequence data, have been compiled into a publicly-available Website http://public-contigbrowser.sigenae.org:9090/Crassostrea_gigas/index.htm l. Approximately 43% of the unique ESTs had significant matches against the SwissProt database and 27% were annotated using Gene Ontology terms. In addition, we identified a total of 208 in silico microsatellites from the ESTs, with 173 having sufficient flanking sequence for primer design. We also identified a total of 7,530 putative in silico, single-nucleotide polymorphisms using existing and newly-generated EST resources for the Pacific oyster. Conclusion: A publicly-available database has been populated with 29,745 unique sequences for the Pacific oyster Crassostrea gigas. The database provides many tools to search cleaned and assembled ESTs. The user may input and submit several filters, such as protein or nucleotide hits, to select and download relevant elements. This database constitutes one of the most developed genomic resources accessible among Lophotrochozoans, an orphan clade of bilateral animals. These data will accelerate the development of both genomics and genetics in a commercially-important species with the highest annual, commercial production of any aquatic organism

Origin : a 60 GHz radio-over-fiber home area network project

International audience

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.Peer reviewe

High level synthesis of a co-processor for Gröbner basis computations

Gröbner basis are a powerful tool with many applications in symbolic computation. In this article, we propose a linear systolic array which can be used as co-processor for efficient computation of Gröbner basis, especially dedicated for the domain of error-correcting codes. The design was made from a high level specification in the Alpha language, which provides many static analysis checks. A case study show how much time can be gain with such a co-processor