Conditional Transfer with Dense Residual Attention: Synthesizing traffic signs from street-view imagery

Object detection and classification of traffic signs in street-view imagery is an essential element for asset management, map making and autonomous driving. However, some traffic signs occur rarely and consequently, they are difficult to recognize automatically. To improve the detection and classification rates, we propose to generate images of traffic signs, which are then used to train a detector/classifier. In this research, we present an end-to-end framework that generates a realistic image of a traffic sign from a given image of a traffic sign and a pictogram of the target class. We propose a residual attention mechanism with dense concatenation called Dense Residual Attention, that preserves the background information while transferring the object information. We also propose to utilize multi-scale discriminators, so that the smaller scales of the output guide the higher resolution output. We have performed detection and classification tests across a large number of traffic sign classes, by training the detector using the combination of real and generated data. The newly trained model reduces the number of false positives by 1.2 - 1.5% at 99% recall in the detection tests and an absolute improvement of 4.65% (top-1 accuracy) in the classification tests.Comment: The first two authors have equal contribution. Accepted at International Conference on Pattern Recognition 2018 (ICPR

Demodulation Performance Assessment of New GNSS Signals in Urban Environments

International audienceSatellite navigation signals demodulation performance ishistorically tested and compared in the Additive WhiteGaussian Noise propagation channel model which wellsimulates the signal reception in open areas. Nowadays,the majority of new applications targets dynamic users inurban environments; therefore the GNSS signalsdemodulation performance has become mandatory to beprovided in urban environments. The GPS L1C signaldemodulation performance in urban environments is thusprovided in this paper. To do that, a new methodologyadapted to provide and assess GNSS signalsdemodulation performance in urban channels has beendeveloped. It counteracts the classic method limitationswhich are the fluctuating received C/N0 in urbanenvironments and the fact that each received message istaken into account in the error rate computation whereasin GNSS it is not necessary. The new methodology thusproposes to provide the demodulation performance for‘favorable’ reception conditions together with statisticalinformation about the occurrence of these favorablereception conditions. To be able to apply this newmethodology and to provide the GPS L1C signaldemodulation performance in urban environments, asimulator SiGMeP (Simulator for GNSS MessagePerformance) has been developed. Two urbanpropagation channel models can be tested: thenarrowband Perez-Fontan/Prieto model and the widebandDLR model. Moreover, the impact of the received signalphase estimation residual errors has been taken intoaccount (ideal estimation is compared with PLL tracking)

GNSS Signal Demodulation Performance in Urban Environments

International audienceSatellite navigation signals demodulation performance is historically tested and compared in the Additive White Gaussian Noise propagation channel model which well simulates open areas. Nowadays, the majority of new applications targets dynamic users in urban environments; therefore the implementation of a simulation tool able to provide realistically GNSS signal demodulation performance in obstructed propagation channels has become mandatory . This paper presents the simulator SiGMeP (Simulator for GNSS Message Performance) which is wanted to provide demodulation performance of any GNSS signals in urban environment , as faithfully of reality as possible . The demodulation performance of GPS L1C/A, GPS L2C, GPS L1C and Galileo E1 OS signals simulated with SiGMeP in the AWGN channel model configuration is firstly showed . Then, the demodulation performance of GPS L1C simulated with SiGMeP in urban environments is presented using the Prieto channel model with two signal carrier phase estimation configurations: perfect signal carrier phase estimation and PLL trackin

A tessellation-based colocalization analysis approach for single-molecule localization microscopy

International audienceMulticolor single-molecule localization microscopy (λSMLM) is a powerful technique to reveal the relative nanoscale organization and potential colocalization between different molecular species. While several standard analysis methods exist for pixel-based images, λSMLM still lacks such a standard. Moreover, existing methods only work on 2D data and are usually sensitive to the relative molecular organization, a very important parameter to consider in quantitative SMLM. Here, we present an efficient, parameter-free colocalization analysis method for 2D and 3D λSMLM using tessellation analysis. We demonstrate that our method allows for the efficient computation of several popular colocalization estimators directly from molecular coordinates and illustrate its capability to analyze multicolor SMLM data in a robust and efficient manner

Optimizing GNSS Navigation Data Message Decoding in Urban Environment

Nowadays, the majority of new GNSS applications targets dynamic users in urban environments; therefore the decoder input in GNSS receivers needs to be adapted to the urban propagation channel to avoid mismatched decoding when using soft input channel decoding. The aim of this paper consists thus in showing that the GNSS signals demodulation performance is significantly improved integrating an advanced soft detection function as decoder input in urban areas. This advanced detection function takes into account some a priori information on the available Channel State Information (CSI). If no CSI is available, one has to blindly adapt the detection function in order to operate close to the perfect CSI case. This will lead to avoid mismatched decoding due to, for example, the consideration by default of the Additive White Gaussian Noise (AWGN) channel for the derivation of soft inputs to be fed to soft input decoders. As a consequence the decoding performance will be improved in urban areas. The expressions of the soft decoder input function adapted for an urban environment is highly dependent on the available CSI at the receiver end. Based on different model of urban propagation channels, several CSI contexts will be considered namely perfect CSI, partial statistical CSI and no CSI. Simulation results will be given related to the GPS L1C demodulation performance with these different advanced detection function expressions in an urban environment. The results presented in this paper are valid for any kind of soft input decoders, such as Viterbi decoding for trellis based codes, the MAP/BCJR decoding for turbo-codes and the Belief Propagation decoding for LDPC codes

New GNSS Signals Demodulation Performance in Urban Environments

Satellite navigation signals demodulation performance is historically tested and compared in the Additive White Gaussian Noise propagation channel model which well simulates the signal reception in open areas. Nowadays, the majority of new applications targets dynamic users in urban environments; therefore the implementation of a simulation tool able to provide realistic GNSS signal demodulation performance in obstructed propagation channels has become mandatory. This paper presents the simulator SiGMeP (Simulator for GNSS Message Performance), which is wanted to provide demodulation performance of any GNSS signals in urban environment, as faithfully of reality as possible. The demodulation performance of GPS L1C simulated with SiGMeP in the AWGN propagation channel model, in the Prieto propagation channel model (narrowband Land Mobile Satellite model in urban configuration) and in the DLR channel model (wideband Land Mobile Satellite model in urban configuration) are computed and compared one to the other. The demodulation performance for both LMS channel models is calculated using a new methodology better adapted to urban environments, and the impact of the received signal phase estimation residual errors has been taken into account (ideal estimation is compared with PLL tracking). Finally, a refined figure of merit used to represent GNSS signals demodulation performance in urban environment is proposed

Suicidal Behavior and Alcohol Abuse

Suicide is an escalating public health problem, and alcohol use has consistently been implicated in the precipitation of suicidal behavior. Alcohol abuse may lead to suicidality through disinhibition, impulsiveness and impaired judgment, but it may also be used as a means to ease the distress associated with committing an act of suicide. We reviewed evidence of the relationship between alcohol use and suicide through a search of MedLine and PsychInfo electronic databases. Multiple genetically-related intermediate phenotypes might influence the relationship between alcohol and suicide. Psychiatric disorders, including psychosis, mood disorders and anxiety disorders, as well as susceptibility to stress, might increase the risk of suicidal behavior, but may also have reciprocal influences with alcohol drinking patterns. Increased suicide risk may be heralded by social withdrawal, breakdown of social bonds, and social marginalization, which are common outcomes of untreated alcohol abuse and dependence. People with alcohol dependence or depression should be screened for other psychiatric symptoms and for suicidality. Programs for suicide prevention must take into account drinking habits and should reinforce healthy behavioral patterns

A new era for understanding amyloid structures and disease

The aggregation of proteins into amyloid fibrils and their deposition into plaques and intracellular inclusions is the hallmark of amyloid disease. The accumulation and deposition of amyloid fibrils, collectively known as amyloidosis, is associated with many pathological conditions that can be associated with ageing, such as Alzheimer disease, Parkinson disease, type II diabetes and dialysis-related amyloidosis. However, elucidation of the atomic structure of amyloid fibrils formed from their intact protein precursors and how fibril formation relates to disease has remained elusive. Recent advances in structural biology techniques, including cryo-electron microscopy and solid-state NMR spectroscopy, have finally broken this impasse. The first near-atomic-resolution structures of amyloid fibrils formed in vitro, seeded from plaque material and analysed directly ex vivo are now available. The results reveal cross-β structures that are far more intricate than anticipated. Here, we describe these structures, highlighting their similarities and differences, and the basis for their toxicity. We discuss how amyloid structure may affect the ability of fibrils to spread to different sites in the cell and between organisms in a prion-like manner, along with their roles in disease. These molecular insights will aid in understanding the development and spread of amyloid diseases and are inspiring new strategies for therapeutic intervention

R. C. Zaehner, L'Hindouisme. Traduit de l'anglais par Eva de Vitray-Meyerovitch. 1974

Ries Julien. R. C. Zaehner, L'Hindouisme. Traduit de l'anglais par Eva de Vitray-Meyerovitch. 1974. In: Revue théologique de Louvain, 6ᵉ année, fasc. 4, 1975. pp. 507-508