338 research outputs found
Lieb-Robinson Bounds for Harmonic and Anharmonic Lattice Systems
We prove Lieb-Robinson bounds for the dynamics of systems with an infinite
dimensional Hilbert space and generated by unbounded Hamiltonians. In
particular, we consider quantum harmonic and certain anharmonic lattice
systems
EL-GAN: Embedding Loss Driven Generative Adversarial Networks for Lane Detection
Convolutional neural networks have been successfully applied to semantic
segmentation problems. However, there are many problems that are inherently not
pixel-wise classification problems but are nevertheless frequently formulated
as semantic segmentation. This ill-posed formulation consequently necessitates
hand-crafted scenario-specific and computationally expensive post-processing
methods to convert the per pixel probability maps to final desired outputs.
Generative adversarial networks (GANs) can be used to make the semantic
segmentation network output to be more realistic or better
structure-preserving, decreasing the dependency on potentially complex
post-processing. In this work, we propose EL-GAN: a GAN framework to mitigate
the discussed problem using an embedding loss. With EL-GAN, we discriminate
based on learned embeddings of both the labels and the prediction at the same
time. This results in more stable training due to having better discriminative
information, benefiting from seeing both `fake' and `real' predictions at the
same time. This substantially stabilizes the adversarial training process. We
use the TuSimple lane marking challenge to demonstrate that with our proposed
framework it is viable to overcome the inherent anomalies of posing it as a
semantic segmentation problem. Not only is the output considerably more similar
to the labels when compared to conventional methods, the subsequent
post-processing is also simpler and crosses the competitive 96% accuracy
threshold.Comment: 14 pages, 7 figure
Model Adaptation with Synthetic and Real Data for Semantic Dense Foggy Scene Understanding
This work addresses the problem of semantic scene understanding under dense
fog. Although considerable progress has been made in semantic scene
understanding, it is mainly related to clear-weather scenes. Extending
recognition methods to adverse weather conditions such as fog is crucial for
outdoor applications. In this paper, we propose a novel method, named
Curriculum Model Adaptation (CMAda), which gradually adapts a semantic
segmentation model from light synthetic fog to dense real fog in multiple
steps, using both synthetic and real foggy data. In addition, we present three
other main stand-alone contributions: 1) a novel method to add synthetic fog to
real, clear-weather scenes using semantic input; 2) a new fog density
estimator; 3) the Foggy Zurich dataset comprising real foggy images,
with pixel-level semantic annotations for images with dense fog. Our
experiments show that 1) our fog simulation slightly outperforms a
state-of-the-art competing simulation with respect to the task of semantic
foggy scene understanding (SFSU); 2) CMAda improves the performance of
state-of-the-art models for SFSU significantly by leveraging unlabeled real
foggy data. The datasets and code are publicly available.Comment: final version, ECCV 201
Three (Potential) Pillars of Transnational Economic Justice: The Bretton Woods Institutions as Guarantors of Global Equal Treatment and Market Completion
This essay aims to bring two important lines of inquiry and criticism together. It first lays out an institutionally enriched account of what a just world economic order will look like. That account prescribes, via the requisites to that mechanism which most directly instantiate the account, three realms of equal treatment and market completion - the global products, services, and labor markets; the global investment/financial markets; and the global preparticipation opportunity allocation. The essay then suggests how, with minimal if any departure from familiar canons of traditional international legal mandate interpretation, each of the Bretton Woods institutions - particularly the GATT/WTO and the IMF - can be viewed at least in part as charged with the task of fostering equal treatment and ultimate market completion within one of those three realms. The piece then argues that one of the institutions in particular - the World Bank - has, for reasons of at best negligent and at worst willful injustice on the part of influential state actors in the world community, fallen farthest short in pursuit of what should be viewed as its proper mandate. The article accordingly concludes that a fuller empowerment of the Bank to effect its ideal mission will press the Bretton Woods system more nearly into ethical balance, and with it the world into justice; and that full empowerment of the GATT/WTO and IMF should be partly conditioned upon the fuller empowerment of the Bank
Phylogenetic interrelationships of the barbets (Aves: Capitonidae) and toucans (Aves: Ramphastidae) based on morphology with comparisons to DNA-DNA hybridization
Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/73985/1/j.1096-3642.1988.tb01728.x.pd
Number preferences in lotteries
We explore people's preferences for numbers in large proprietary data sets from two different lottery games. We find that choice is far from uniform, and exhibits some familiar and some new tendencies and biases. Players favor personally meaningful and situationally available numbers, and are attracted towards numbers in the center of the choice form. Frequent players avoid winning numbers from recent draws, whereas infrequent players chase these. Combinations of numbers are formed with an eye for aesthetics, and players tend to spread their numbers relatively evenly across the possible range
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