846 research outputs found
INTERNET CONTENT PROVIDER LICENCES IN THE PEOPLE’S REPUBLIC OF CHINA’S INTERNET INDUSTRY: A PRACTICAL PERSPECTIVE
The provision of internet services in China is governed by a detailed regulatory regime. This chapter will outline the basic legal framework for such regulation and highlight current issues created by the existing model
Latent Space Energy-based Model for Fine-grained Open Set Recognition
Fine-grained open-set recognition (FineOSR) aims to recognize images
belonging to classes with subtle appearance differences while rejecting images
of unknown classes. A recent trend in OSR shows the benefit of generative
models to discriminative unknown detection. As a type of generative model,
energy-based models (EBM) are the potential for hybrid modeling of generative
and discriminative tasks. However, most existing EBMs suffer from density
estimation in high-dimensional space, which is critical to recognizing images
from fine-grained classes. In this paper, we explore the low-dimensional latent
space with energy-based prior distribution for OSR in a fine-grained visual
world. Specifically, based on the latent space EBM, we propose an
attribute-aware information bottleneck (AIB), a residual attribute feature
aggregation (RAFA) module, and an uncertainty-based virtual outlier synthesis
(UVOS) module to improve the expressivity, granularity, and density of the
samples in fine-grained classes, respectively. Our method is flexible to take
advantage of recent vision transformers for powerful visual classification and
generation. The method is validated on both fine-grained and general visual
classification datasets while preserving the capability of generating
photo-realistic fake images with high resolution
3D tracking of particles in a dusty plasma by laser sheet tomography
The collective behavior of levitated particles in a weakly-ionized plasma
(dusty plasma) has raised significant scientific interest. This is due to the
complex array of forces acting on the particles, and their potential to act as
in-situ diagnostics of the plasma environment. Ideally, the three-dimensional
(3D) motion of many particles should be tracked for long periods of time.
Typically, stereoscopic imaging using multiple cameras combined with particle
image velocimetry (PIV) is used to obtain a velocity field of many particles,
yet this method is limited by its sample volume and short time scales. Here we
demonstrate a different, high-speed tomographic imaging method capable of
tracking individual particles. We use a scanning laser sheet coupled to a
single high-speed camera. We are able to identify and track tens of individual
particles over centimeter length scales for several minutes, corresponding to
more than 10,000 frames.Comment: 7 pages, 5 figure
The Current Research Feature and Prospect of Bronchoalveolar Lavage in Diagnosing Lung Cancer
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