Publications

Fully convolutional networks for semantic segmentation

Convolutional networks are powerful visual models that yield hierarchies of features. We show that convolutional networks by themselves, trained end-to-end, pixels-to-pixels, ex...

PLINK: A Tool Set for Whole-Genome Association and Population-Based Linkage Analyses

SciPy 1.0: fundamental algorithms for scientific computing in Python

Histograms of Oriented Gradients for Human Detection

International audience

Rich Feature Hierarchies for Accurate Object Detection and Semantic Segmentation

Object detection performance, as measured on the canonical PASCAL VOC dataset, has plateaued in the last few years. The best-performing methods are complex ensemble systems that...

An Algorithm for Least-Squares Estimation of Nonlinear Parameters

Previous article Next article An Algorithm for Least-Squares Estimation of Nonlinear ParametersDonald W. MarquardtDonald W. Marquardthttps://doi.org/10.1137/0111030PDFPDF PLUSBi...

An introduction to probability theory and its applications

Standards and guidelines for the interpretation of sequence variants: a joint consensus recommendation of the American College of Medical Genetics and Genomics and the Association for Molecular Pathology

Semiempirical GGA‐type density functional constructed with a long‐range dispersion correction

Abstract A new density functional (DF) of the generalized gradient approximation (GGA) type for general chemistry applications termed B97‐D is proposed. It is based on Becke's p...

Society and the Adolescent Self-Image

Over 5,000 high-school students of different social, religious, and national backgrounds were studied to show the effects of family experience, neighborhoods, minority groups, e...

Econometric Analysis of Cross Section and Panel Data

The second edition of this acclaimed graduate text provides a unified treatment of two methods used in contemporary econometric research, cross section and data panel methods. B...

A Computational Approach to Edge Detection

This paper describes a computational approach to edge detection. The success of the approach depends on the definition of a comprehensive set of goals for the computation of edg...