4,693 research outputs found
No Spare Parts: Sharing Part Detectors for Image Categorization
This work aims for image categorization using a representation of distinctive
parts. Different from existing part-based work, we argue that parts are
naturally shared between image categories and should be modeled as such. We
motivate our approach with a quantitative and qualitative analysis by
backtracking where selected parts come from. Our analysis shows that in
addition to the category parts defining the class, the parts coming from the
background context and parts from other image categories improve categorization
performance. Part selection should not be done separately for each category,
but instead be shared and optimized over all categories. To incorporate part
sharing between categories, we present an algorithm based on AdaBoost to
jointly optimize part sharing and selection, as well as fusion with the global
image representation. We achieve results competitive to the state-of-the-art on
object, scene, and action categories, further improving over deep convolutional
neural networks
Objects2action: Classifying and localizing actions without any video example
The goal of this paper is to recognize actions in video without the need for
examples. Different from traditional zero-shot approaches we do not demand the
design and specification of attribute classifiers and class-to-attribute
mappings to allow for transfer from seen classes to unseen classes. Our key
contribution is objects2action, a semantic word embedding that is spanned by a
skip-gram model of thousands of object categories. Action labels are assigned
to an object encoding of unseen video based on a convex combination of action
and object affinities. Our semantic embedding has three main characteristics to
accommodate for the specifics of actions. First, we propose a mechanism to
exploit multiple-word descriptions of actions and objects. Second, we
incorporate the automated selection of the most responsive objects per action.
And finally, we demonstrate how to extend our zero-shot approach to the
spatio-temporal localization of actions in video. Experiments on four action
datasets demonstrate the potential of our approach
High-level feature detection from video in TRECVid: a 5-year retrospective of achievements
Successful and effective content-based access to digital
video requires fast, accurate and scalable methods to determine the video content automatically. A variety of contemporary approaches to this rely on text taken from speech within the video, or on matching one video frame against others using low-level characteristics like
colour, texture, or shapes, or on determining and matching objects appearing within the video. Possibly the most important technique, however, is one which determines the presence or absence of a high-level or semantic feature, within a video clip or shot. By utilizing dozens, hundreds or even thousands of such semantic features we can support many kinds of content-based video navigation. Critically however, this depends on being able to determine whether each feature is or is not present in a video clip.
The last 5 years have seen much progress in the development of techniques to determine the presence of semantic features within video. This progress can be tracked in the annual TRECVid benchmarking activity where dozens of research groups measure the effectiveness of their techniques on common data and using an open, metrics-based approach. In this chapter we summarise the work
done on the TRECVid high-level feature task, showing the
progress made year-on-year. This provides a fairly comprehensive statement on where the state-of-the-art is regarding this important task, not just for one research group or for one approach, but across the spectrum. We then use this past and on-going work as a basis for highlighting the trends that are emerging in this area, and the questions which remain to be addressed before we can
achieve large-scale, fast and reliable high-level feature detection on video
Theory of Ultracold Superstrings
The combination of a vortex line in a one-dimensional optical lattice with
fermions bound to the vortex core makes up an ultracold superstring. We give a
detailed derivation of the way to make this supersymmetric string in the
laboratory. In particular, we discuss the presence of a fermionic bound state
in the vortex core and the tuning of the laser beams needed to achieve
supersymmetry. Moreover, we discuss experimental consequences of supersymmetry
and identify the precise supersymmetry in the problem. Finally, we make the
mathematical connection with string theory.Comment: 16 pages, 9 figures, important factor 2 corrected, accepted for
publication in PR
Decision for reconstructive interventions of the upper limb in individuals with tetraplegia: the effect of treatment characteristics
Objective: To determine the effect of treatment characteristics on the\ud
decision for reconstructive interventions for the upper extremities (UE) in\ud
subjects with tetraplegia. - \ud
Setting: Seven specialized spinal cord injury centres in the Netherlands. - \ud
Method: Treatment characteristics for UE reconstructive interventions were\ud
determined. Conjoint analysis (CA) was used to determine the contribution\ud
and the relative importance of the treatment characteristics on the decision\ud
for therapy. Therefore, a number of different treatment scenarios using these\ud
characteristics were established. Different pairs of scenarios were presented\ud
to subjects who were asked to choose the preferred scenario of each set. - \ud
Results: forty nine subjects with tetraplegia with a stable C5, C6 or C7\ud
lesion were selected. All treatment characteristics significantly influenced\ud
the choice for treatment. Relative importance of treatment characteristics\ud
were: intervention type (surgery or surgery with FES implant) 13%, number\ud
of operations 15%, in patient rehabilitation period 22%, ambulant\ud
rehabilitation period 9%, complication rate 15%, improvement of elbow\ud
function 10%, improvement of hand function 15%. In deciding for therapy\ud
40% of the subjects focused on one characteristic. - \ud
Conclusion: CA is applicable in Spinal Cord Injury medicine to study the\ud
effect of health outcomes and non-health outcomes on the decision for\ud
treatment. Non-health outcomes which relate to the intensity of treatment\ud
are equally important or even more important than functional outcome in the\ud
decision for reconstructive UE surgery in subjects with tetraplegia
Mott Transition and Spin Structures of Spin-1 Bosons in Two-Dimensional Optical Lattice at Unit Filling
We study the ground state properties of spin-1 bosons in a two-dimensional
optical lattice, by applying a variational Monte Carlo method to the S=1
Bose-Hubbard model on a square lattice at unit filling. A doublon-holon binding
factor introduced in the trial state provides a noticeable improvement in the
variational energy over the conventional Gutzwiller wave function and allows us
to deal effectively with the inter-site correlations of particle densities and
spins. We systematically show how spin-dependent interactions modify the
superfluid-Mott insulator transitions in the S=1 Bose-Hubbard model due to the
interplay between the density and spin fluctuations of bosons. Furthermore,
regarding the magnetic phases in the Mott region, the calculated spin structure
factor elucidates the emergence of nematic and ferromagnetic spin orders for
antiferromagnetic () and ferromagnetic () couplings,
respectively.Comment: 5 pages, 5 figures, to appear in Journal of the Physical Society of
Japa
Many-Body Physics with Ultracold Gases
This article reviews recent experimental and theoretical progress on
many-body phenomena in dilute, ultracold gases. Its focus are effects beyond
standard weak-coupling descriptions, like the Mott-Hubbard-transition in
optical lattices, strongly interacting gases in one and two dimensions or
lowest Landau level physics in quasi two-dimensional gases in fast rotation.
Strong correlations in fermionic gases are discussed in optical lattices or
near Feshbach resonances in the BCS-BEC crossover.Comment: revised version, accepted for publication in Rev. Mod. Phy
Survey of the needs of patients with spinal cord injury: impact and priority for improvement in hand function in tetraplegics\ud
Objective: To investigate the impact of upper extremity deficit in subjects with tetraplegia.\ud
\ud
Setting: The United Kingdom and The Netherlands.\ud
\ud
Study design: Survey among the members of the Dutch and UK Spinal Cord Injury (SCI) Associations.\ud
\ud
Main outcome parameter: Indication of expected improvement in quality of life (QOL) on a 5-point scale in relation to improvement in hand function and seven other SCI-related impairments.\ud
\ud
Results: In all, 565 subjects with tetraplegia returned the questionnaire (overall response of 42%). Results in the Dutch and the UK group were comparable. A total of 77% of the tetraplegics expected an important or very important improvement in QOL if their hand function improved. This is comparable to their expectations with regard to improvement in bladder and bowel function. All other items were scored lower.\ud
\ud
Conclusion: This is the first study in which the impact of upper extremity impairment has been assessed in a large sample of tetraplegic subjects and compared to other SCI-related impairments that have a major impact on the life of subjects with SCI. The present study indicates a high impact as well as a high priority for improvement in hand function in tetraplegics.\ud
\u
Single-atom imaging of fermions in a quantum-gas microscope
Single-atom-resolved detection in optical lattices using quantum-gas
microscopes has enabled a new generation of experiments in the field of quantum
simulation. Fluorescence imaging of individual atoms has so far been achieved
for bosonic species with optical molasses cooling, whereas detection of
fermionic alkaline atoms in optical lattices by this method has proven more
challenging. Here we demonstrate single-site- and single-atom-resolved
fluorescence imaging of fermionic potassium-40 atoms in a quantum-gas
microscope setup using electromagnetically-induced-transparency cooling. We
detected on average 1000 fluorescence photons from a single atom within 1.5s,
while keeping it close to the vibrational ground state of the optical lattice.
Our results will enable the study of strongly correlated fermionic quantum
systems in optical lattices with resolution at the single-atom level, and give
access to observables such as the local entropy distribution and individual
defects in fermionic Mott insulators or anti-ferromagnetically ordered phases.Comment: 7 pages, 5 figures; Nature Physics, published online 13 July 201
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