Publications

ImageNet Large Scale Visual Recognition Challenge

An Inventory for Measuring Depression

The difficulties inherent in obtaining consistent and adequate diagnoses for the purposes of research and therapy have been pointed out by a number of authors. Pasamanick<sup>12...

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...

Absorptive Capacity: A New Perspective on Learning and Innovation

In this paper, we argue that the ability of a firm to recognize the value of new, external information, assimilate it, and apply it to commercial ends is critical to its innovat...

Glove: Global Vectors for Word Representation

Recent methods for learning vector space representations of words have succeeded in capturing fine-grained semantic and syntactic regularities using vector arithmetic, but the o...

Histograms of Oriented Gradients for Human Detection

International audience

Scoping studies: towards a methodological framework

This paper focuses on scoping studies, an approach to reviewing the literature which to date has received little attention in the research methods literature. We distinguish bet...

The SILVA ribosomal RNA gene database project: improved data processing and web-based tools

This FAIRsharing record describes: SILVA is a comprehensive, quality-controlled web resource for up-to-date aligned ribosomal RNA (rRNA) gene sequences from the Bacteria, Archae...

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...

Jacob Devlin, Ming-Wei Chang, Kenton Lee, Kristina Toutanova. Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: ...

Rethinking the Inception Architecture for Computer Vision

Convolutional networks are at the core of most state of-the-art computer vision solutions for a wide variety of tasks. Since 2014 very deep convolutional networks started to bec...

A low-cost, high-efficiency solar cell based on dye-sensitized colloidal TiO2 films

THE large-scale use of photovoltaic devices for electricity generation is prohibitively expensive at present: generation from existing commercial devices costs about ten times m...