Un modèle probabiliste pour la reconstruction 3D

Session "Atelier V3DPAT"National audienceCet article introduit un cadre probabiliste permettant d'étudier mathématiquement et a priori des algorithmes de reconstruction 3D. Dans cet article, l'étude se concentre sur la famille des algorithmes de reconstruction 3D définit par les trois critères suivants. Premièrement, ils étudient une scène observée simultanément par deux camé- ras calibrées. Deuxièmement, ils discrétisent la scène en un ensemble de voxels pleins ou vides. Troisièmement, ces algorithmes se basent sur la donnée d'une fonction qui a chaque voxel associe une mesure de la concordance entre les zones des deux images où ce voxel se projette. L'idée-clé de ce cadre probabiliste est que, statistiquement, la concordance entre les zones des deux images où se pro- jette un voxel est : forte si ce voxel est sur la surface que l'on cherche à reconstruire, et, faible sinon. Nous montrerons d'abord que cette idée-clé, assez naturelle, est justifiée expérimentalement. Nous montrerons alors que certaines propriétés de ces algorithmes peuvent se déduire mathématiquement des deux distributions de probabilité des concordances (celle pour les voxels sur la surface et celle pour ceux en dehors de la surface). Nous montrerons pour quelques algorithmes que les propriétés établies théoriquement à l'aide de notre modélisation sont compatibles avec les propriétés expérimentales mesurées sur des jeux de données réelles. Enfin, nous étudierons théoriquement un algorithme NP-complet, que l'on ne peut pas étudier expérimentalement

Une modélisation probabiliste de la reconstruction 3D

On s'intéresse dans cet article au problème de la reconstruction 3D d'une scène à partir de 2 photographies de la scène et de la connaissance des relations géométriques entre les points (physique ou virtuelle) de l'espace 3D et les positions dans les 2 images (les calibrations des 2 photographies) d'un point de vue théorique. On introduit une modélisation probabiliste du problème de la reconstruction 3D qui assimile reconstruction 3D et inférence de paramètres inconnus d'un tirage aléatoire. L'expressivité de notre modélisation est discutée pour montrer que la plupart des méthodes classiques de la littérature peuvent se modéliser comme des cas particulier de notre formulation

Exploration du graphe des états discrétisés pour le robot à deux roues commandées en accélération

Cet article s'intéresse à l'étude du problème du guidage optimal en temps du robot à 2 roues commandées en accélération, évoluant dans un plan contenant des obstacles. On s'intéresse au cas particulier où la commande doit être choisie dans un ensemble discret et à des instants discrets régulièrement répartis. Ce problème est alors un problème discret dont on peut trouver la solution optimale par exploration de l'arbre des suites de commande. Cette exploration étant couteuse, une approche s'appuyant sur les propriétés du graphe des états discrétisés est présentée. Ce nouvel algorithme est complémentaire de l'algorithme basé sur l'exploration de l'arbre des suites de commandes

Gradient regularisation increases deep learning performance under stress on remote sensing applications.

Deep learning community currently put a very large effort on resistance to adversarial attacks, and, major improvements has been achieved to increase local smoothness. In contrast, global smoothness is intrinsically linked to Lipschitz value, but, the link between these two notions is too few explored.In this paper, experiments of object detection and image segmentation on public remote sensing datasets show that adding Lipschitz related penalty consistently increase performance under stress (including adversarial attacks)

Adversarial poisoning and inverse poisoning against deep learning

Efficient attacks for both adversarial poisoning and adversarial inverse poisoning have recently been found on frozen deep feature plus support vector machine.But, new experiments show that such attacks only works for poisoning.But, such attacks is completely inefficient for inverse poisoning when targeting deep networks as stochastic training provides a natural defense.However, new attacks are presented to overcome this defense.This way, this paper shows that adversarial poisoning and inverse poisoning are possible against straightforward deep network

Apprendre à comprendre les images d'observation de la Terre avec des annotations pauvres et non fiables

International audienceIn this paper we discuss the issues of using inexact and inaccurate ground truth in the context of supervised learning. To leverage large amounts of Earth observation data for training algorithms, one often has to use ground truth which was not been carefully assessed. We address both the problems of training and evaluation. We first propose a weakly supervised approach for training change classifiers which is able to detect pixel-level changes in aerial images. We then propose a data poisoning approach to get a reliable estimate of the accuracy that can be expected from a classifier, even when the only ground-truth available does not match the reality. Both are assessed on practical land use and land cover applications

Experimental demonstration of 111.1-Gb/s net information rate using IM/DD probabilistically shaped orthogonal chirp-division multiplexing with a 10-GHz-class modulator

We propose probabilistically shaped quadrature amplitude modulation (PS-QAM) formats to maximize the capacity in fiber transmission systems using orthogonal chirp-division multiplexing (OCDM). OCDM possesses the property of chirp spread spectrum (CSS), leading to improved resilience to system impairments. We further investigate the recently proposed robust channel estimator based on pulse compression and noise rejection and experimentally demonstrate its feasibility in an intensity-modulated/direction-detection (IM/DD) OCDM system. By applying the proposed PS-QAM based OCDM to an IM/DD optical system, a net information rate of 111.1 Gb/s has been successfully achieved using a 10-GHz class Mach–Zehnder modulator (MZM) and has also shown improved performance compared to the conventional PS-QAM based orthogonal frequency-division multiplexing (OFDM) systems. Moreover, due to the superior characteristics of OCDM, there is no need for additional feedback to obtain the prior knowledge of channel state information in the proposed system, leading to reduced complexity and cos

Immunoregulatory Protein Profiles of Necrotizing Enterocolitis versus Spontaneous Intestinal Perforation in Preterm Infants

Necrotizing enterocolitis (NEC) and spontaneous intestinal perforation (SIP) are the most common acute surgical emergencies associated with high morbidity and mortality in preterm infants. We aimed to compare the profiles of immunoregulatory proteins and identify novel mediators in plasma of NEC and SIP infants. We also investigated the expression of target genes in resected intestinal tissues and an enterocyte cell line. Using Cytokine Antibody Array assay, we reported the first comparative profiles of immunoregulatory proteins in plasma of NEC and SIP infants, and showed that dysregulated proteins belonged to functionally diversified categories, including pro- and anti-inflammation, angiogenesis, cell growth, wound healing, anti-apoptosis, cell adhesion and extracellular matrix reorganization. Validation by ELISA confirmed significantly higher concentrations of interleukin (IL)-6, angiopoietin (Ang)-2, soluble type II interleukin-1 receptor (sIL-1RII), and soluble urokinase-type plasminogen activator receptor (suPAR) in NEC infants compared with gestational age-matched control, and a lower level of an epidermal growth factor receptor, secreted form of receptor tyrosine-protein kinase ErbB3 (sErbB3), compared with SIP infants. mRNA expressions of IL1-RII and uPAR were up-regulated in resected bowel tissues from NEC infants, indicating that immunoregulation also occurred at the cellular level. In FHs-74 Int cells, Ang-2, IL1-RII and uPAR mRNA expressions were significantly induced by the combined treatment with lipopolysaccharide (LPS) and platelet activating factor (PAF). Our study provided plasmatic signatures of immunoregulatory proteins in NEC and SIP infants, and demonstrated involvement of multiple functional pathways. The magnitude of changes in these proteins was significantly more extensive in NEC infants, reflecting the different nature of injury and/or severity of inflammation. We speculate that dysregulation of IL-6, Ang-2, IL-1RII and uPAR occurred at both systemic and cellular levels, and probably mediated via LPS and endogeneous PAF signals. Such exaggerated immunologic responses may account for the high morbidity and mortality in NEC compared with SIP patients

Acute renal impairment in coronavirus-associated severe acute respiratory syndrome

Acute renal impairment in coronavirus-associated severe acute respiratory syndrome.BackgroundSevere acute respiratory syndrome (SARS) is a newly emerged infection from a novel coronavirus (SARS-CoV). Apart from fever and respiratory complications, acute renal impairment has been observed in some patients with SARS. Herein, we describe the clinical, pathologic, and laboratory features of the acute renal impairment complicating this new viral infection.MethodsWe conducted a retrospective analysis of the plasma creatinine concentration and other clinical parameters of the 536 SARS patients with normal plasma creatinine at first clinical presentation, admitted to two regional hospitals following a major outbreak in Hong Kong in March 2003. Kidney tissues from seven other patients with postmortem examinations were studied by light microscopy and electron microscopy.ResultsAmong these 536 patients with SARS, 36 (6.7%) developed acute renal impairment occurring at a median duration of 20 days (range 5–48 days) after the onset of viral infection despite a normal plasma creatinine level at first clinical presentation. The acute renal impairment reflected the different prerenal and renal factors that exerted renal insult occurring in the context of multiorgan failure. Eventually, 33 SARS patients (91.7%) with acute renal impairment died. The mortality rate was significantly higher among patients with SARS and acute renal impairment compared with those with SARS and no renal impairment (91.7% vs. 8.8%) (P < 0.0001). Renal tissues revealed predominantly acute tubular necrosis with no evidence of glomerular pathology. The adjusted relative risk of mortality associated with the development of acute renal impairment was 4.057 (P < 0.001). By multivariate analysis, acute respiratory distress syndrome and age were the most significant independent risk factors predicting the development of acute renal impairment in SARS.ConclusionAcute renal impairment is uncommon in SARS but carries a high mortality. The acute renal impairment is likely to be related to multi-organ failure rather than the kidney tropism of the virus. The development of acute renal impairment is an important negative prognostic indicator for survival with SARS