École normale supérieure de Cachan

About: École normale supérieure de Cachan is a education organization based out in Cachan, Île-de-France, France. It is known for research contribution in the topics: Decidability & Nonlinear system. The organization has 2717 authors who have published 5585 publications receiving 175925 citations.

Comprehensive genomic access to vector integration in clinical gene therapy

Abstract: Retroviral vectors have induced subtle clonal skewing in many gene therapy patients and severe clonal proliferation and leukemia in some of them, emphasizing the need for comprehensive integration site analyses to assess the biosafety and genomic pharmacokinetics of vectors and clonal fate of gene-modified cells in vivo. Integration site analyses such as linear amplification-mediated PCR (LAM-PCR) require a restriction digest generating unevenly small fragments of the genome. Here we show that each restriction motif allows for identification of only a fraction of all genomic integrants, hampering the understanding and prediction of biological consequences after vector insertion. We developed a model to define genomic access to the viral integration site that provides optimal restriction motif combinations and minimizes the percentage of nonaccessible insertion loci. We introduce a new nonrestrictive LAM-PCR approach that has superior capabilities for comprehensive unbiased integration site retrieval in preclinical and clinical samples independent of restriction motifs and amplification inefficiency.

Wavelets, Generalized White Noise and Fractional Integration: The Synthesis of Fractional Brownian Motion.

Abstract: We provide an almost sure convergent expansion of fractional Brownian motion in wavelets which decorrelates the high frequencies. Our approach generalizes Levy's midpoint displacement technique which is used to generate Brownian motion. The low-frequency terms in the expansion involve an independent fractional Brownian motion evaluated at discrete times or, alternatively, partial sums of a stationary fractional ARIMA time series. The wavelets fill in the gaps and provide the necessary high frequency corrections. We also obtain a way of constructing an arbitrary number of non-Gaussian continuous time processes whose second order properties are the same as those of fractional Brownian motion.

Reconstructing an image from its local descriptors

Abstract: This paper shows that an image can be approximately reconstructed based on the output of a blackbox local description software such as those classically used for image indexing. Our approach consists first in using an off-the-shelf image database to find patches that are visually similar to each region of interest of the unknown input image, according to associated local descriptors. These patches are then warped into input image domain according to interest region geometry and seamlessly stitched together. Final completion of still missing texture-free regions is obtained by smooth interpolation. As demonstrated in our experiments, visually meaningful reconstructions are obtained just based on image local descriptors like SIFT, provided the geometry of regions of interest is known. The reconstruction most often allows the clear interpretation of the semantic image content. As a result, this work raises critical issues of privacy and rights when local descriptors of photos or videos are given away for indexing and search purpose.

Vanishing point detection without any a priori information

Abstract: Even though vanishing points in digital images result from parallel lines in the 3D scene, most of the proposed detection algorithms are forced to rely heavily either on additional properties (like orthogonality or coplanarity and equal distance) of the underlying 3D lines, or on knowledge of the camera calibration parameters, in order to avoid spurious responses. In this work, we develop a new detection algorithm that relies on the Helmoltz principle recently proposed for computer vision by Desolneux et al (2001; 2003), both at the line detection and line grouping stages. This leads to a vanishing point detector with a low false alarms rate and a high precision level, which does not rely on any a priori information on the image or calibration parameters, and does not require any parameter tuning.