6,122 research outputs found
Driver Distraction Identification with an Ensemble of Convolutional Neural Networks
The World Health Organization (WHO) reported 1.25 million deaths yearly due
to road traffic accidents worldwide and the number has been continuously
increasing over the last few years. Nearly fifth of these accidents are caused
by distracted drivers. Existing work of distracted driver detection is
concerned with a small set of distractions (mostly, cell phone usage).
Unreliable ad-hoc methods are often used.In this paper, we present the first
publicly available dataset for driver distraction identification with more
distraction postures than existing alternatives. In addition, we propose a
reliable deep learning-based solution that achieves a 90% accuracy. The system
consists of a genetically-weighted ensemble of convolutional neural networks,
we show that a weighted ensemble of classifiers using a genetic algorithm
yields in a better classification confidence. We also study the effect of
different visual elements in distraction detection by means of face and hand
localizations, and skin segmentation. Finally, we present a thinned version of
our ensemble that could achieve 84.64% classification accuracy and operate in a
real-time environment.Comment: arXiv admin note: substantial text overlap with arXiv:1706.0949
Multiplex Communities and the Emergence of International Conflict
Advances in community detection reveal new insights into multiplex and
multilayer networks. Less work, however, investigates the relationship between
these communities and outcomes in social systems. We leverage these advances to
shed light on the relationship between the cooperative mesostructure of the
international system and the onset of interstate conflict. We detect
communities based upon weaker signals of affinity expressed in United Nations
votes and speeches, as well as stronger signals observed across multiple layers
of bilateral cooperation. Communities of diplomatic affinity display an
expected negative relationship with conflict onset. Ties in communities based
upon observed cooperation, however, display no effect under a standard model
specification and a positive relationship with conflict under an alternative
specification. These results align with some extant hypotheses but also point
to a paucity in our understanding of the relationship between community
structure and behavioral outcomes in networks.Comment: arXiv admin note: text overlap with arXiv:1802.0039
Very High Resolution (VHR) Satellite Imagery: Processing and Applications
Recently, growing interest in the use of remote sensing imagery has appeared to provide synoptic maps of water quality parameters in coastal and inner water ecosystems;, monitoring of complex land ecosystems for biodiversity conservation; precision agriculture for the management of soils, crops, and pests; urban planning; disaster monitoring, etc. However, for these maps to achieve their full potential, it is important to engage in periodic monitoring and analysis of multi-temporal changes. In this context, very high resolution (VHR) satellite-based optical, infrared, and radar imaging instruments provide reliable information to implement spatially-based conservation actions. Moreover, they enable observations of parameters of our environment at greater broader spatial and finer temporal scales than those allowed through field observation alone. In this sense, recent very high resolution satellite technologies and image processing algorithms present the opportunity to develop quantitative techniques that have the potential to improve upon traditional techniques in terms of cost, mapping fidelity, and objectivity. Typical applications include multi-temporal classification, recognition and tracking of specific patterns, multisensor data fusion, analysis of land/marine ecosystem processes and environment monitoring, etc. This book aims to collect new developments, methodologies, and applications of very high resolution satellite data for remote sensing. The works selected provide to the research community the most recent advances on all aspects of VHR satellite remote sensing
- …