2,388 research outputs found
Learning to Extract Motion from Videos in Convolutional Neural Networks
This paper shows how to extract dense optical flow from videos with a
convolutional neural network (CNN). The proposed model constitutes a potential
building block for deeper architectures to allow using motion without resorting
to an external algorithm, \eg for recognition in videos. We derive our network
architecture from signal processing principles to provide desired invariances
to image contrast, phase and texture. We constrain weights within the network
to enforce strict rotation invariance and substantially reduce the number of
parameters to learn. We demonstrate end-to-end training on only 8 sequences of
the Middlebury dataset, orders of magnitude less than competing CNN-based
motion estimation methods, and obtain comparable performance to classical
methods on the Middlebury benchmark. Importantly, our method outputs a
distributed representation of motion that allows representing multiple,
transparent motions, and dynamic textures. Our contributions on network design
and rotation invariance offer insights nonspecific to motion estimation
Fast and flexible selection with a single switch
Selection methods that require only a single-switch input, such as a button
click or blink, are potentially useful for individuals with motor impairments,
mobile technology users, and individuals wishing to transmit information
securely. We present a single-switch selection method, "Nomon," that is general
and efficient. Existing single-switch selection methods require selectable
options to be arranged in ways that limit potential applications. By contrast,
traditional operating systems, web browsers, and free-form applications (such
as drawing) place options at arbitrary points on the screen. Nomon, however,
has the flexibility to select any point on a screen. Nomon adapts automatically
to an individual's clicking ability; it allows a person who clicks precisely to
make a selection quickly and allows a person who clicks imprecisely more time
to make a selection without error. Nomon reaps gains in information rate by
allowing the specification of beliefs (priors) about option selection
probabilities and by avoiding tree-based selection schemes in favor of direct
(posterior) inference. We have developed both a Nomon-based writing application
and a drawing application. To evaluate Nomon's performance, we compared the
writing application with a popular existing method for single-switch writing
(row-column scanning). Novice users wrote 35% faster with the Nomon interface
than with the scanning interface. An experienced user (author TB, with > 10
hours practice) wrote at speeds of 9.3 words per minute with Nomon, using 1.2
clicks per character and making no errors in the final text.Comment: 14 pages, 5 figures, 1 table, presented at NIPS 2009 Mini-symposi
Psychosis and relapse in bipolar disorder are related to GRM3, DAOA, and GRIN2B genotype
Objective:Â Â Key Words: Manic-Depressive Psychosis; Glutamate; GRIN2B receptor; mGluR3; G72 protein; HumanDysfunction in glutamate signalling is thought to play a role in the pathophysiology of bipolar disorder (BD). There is evidence of associations between single nucleotide polymorphisms (SNPs) in GRM3, GRIN2B, and DAOA genes and the diagnosis of BD. In this pilot study, we investigated the frequency of SNP variants in these 3 genes within South African population groups, and assessed interactions between genes and phenotypes of BD disease severity. Method: Multiplex SNaPshotTM PCR was used to genotype 191 case and 188 control samples. Cases comprised of 191 individuals in a South African cohort of mixed ancestry and Caucasians, with BD Type 1. Phenotypes of BD disease severity were: age of onset, number of illness episodes, number of hospitalisations for depression or mania and history of psychotic symptoms. Results: There were no significant difference in SNP allele frequencies between cases and controls. In the case-only analysis, the GRM3 rs6465084 heterozygote was associated with a 4-fold increased risk of lifetime history of psychotic symptoms, and the specific variants within the gene pair, DAOA and GRIN2B, had a significant interaction with the number of hospitalisations for mania, with lowest admission rates associated with both pairs of ancestral alleles. Conclusion: In BD, variations in glutamatergic genes may influence phenotypes related to the severity of illness. Speculatively, newly derived genes associated with various evolutionary advantages, may also increase the risk for more severe BD. These preliminary findings deserve validation in a larger cohort
Playing for Data: Ground Truth from Computer Games
Recent progress in computer vision has been driven by high-capacity models
trained on large datasets. Unfortunately, creating large datasets with
pixel-level labels has been extremely costly due to the amount of human effort
required. In this paper, we present an approach to rapidly creating
pixel-accurate semantic label maps for images extracted from modern computer
games. Although the source code and the internal operation of commercial games
are inaccessible, we show that associations between image patches can be
reconstructed from the communication between the game and the graphics
hardware. This enables rapid propagation of semantic labels within and across
images synthesized by the game, with no access to the source code or the
content. We validate the presented approach by producing dense pixel-level
semantic annotations for 25 thousand images synthesized by a photorealistic
open-world computer game. Experiments on semantic segmentation datasets show
that using the acquired data to supplement real-world images significantly
increases accuracy and that the acquired data enables reducing the amount of
hand-labeled real-world data: models trained with game data and just 1/3 of the
CamVid training set outperform models trained on the complete CamVid training
set.Comment: Accepted to the 14th European Conference on Computer Vision (ECCV
2016
Novel X-Ray Imaging Method for Evaluating Defect Evolution in Ceramic Tapes
Ceramic tape casting is critical to the electronics industry for manufacturing a wide range of components including piezoelectric actuators, MLC capacitors, and substrates for VLSI and LSI chips [1â3]. Recent regulatory changes, led by the Environmental Protection Agency concerning hazardous chemicals used in ceramic tape-casting, have renewed interest in the development of environmentally-friendly modifications to this process. In turn, this has increased interest in developing a better, fundamental understanding of how microstructural defects form and evolve during the sequence of processing steps associated with tape casting. In order to form more reliable electronic components, there is a need to develop a better, basic understanding of how to eliminate these defects by optimizing critical processing variables
A multi-layer extension of the stochastic heat equation
Motivated by recent developments on solvable directed polymer models, we
define a 'multi-layer' extension of the stochastic heat equation involving
non-intersecting Brownian motions.Comment: v4: substantially extended and revised versio
Cross-polarized photon-pair generation and bi-chromatically pumped optical parametric oscillation on a chip
Nonlinear optical processes are one of the most important tools in modern optics with a broad spectrum of applications in, for example, frequency conversion, spectroscopy, signal processing and quantum optics. For practical and ultimately widespread implementation, on-chip devices compatible with electronic integrated circuit technology offer great advantages in terms of low cost, small footprint, high performance and low energy consumption. While many on-chip key components have been realized, to date polarization has not been fully exploited as a degree of freedom for integrated nonlinear devices. In particular, frequency conversion based on orthogonally polarized beams has not yet been demonstrated on chip. Here we show frequency mixing between orthogonal polarization modes in a compact integrated microring resonator and demonstrate a bi-chromatically pumped optical parametric oscillator. Operating the device above and below threshold, we directly generate orthogonally polarized beams, as well as photon pairs, respectively, that can find applications, for example, in optical communication and quantum optics
Rapid and High-Throughput Detection of Highly Pathogenic Bacteria by Ibis PLEX-ID Technology
In this manuscript, we describe the identification of highly pathogenic bacteria using an assay coupling biothreat group-specific PCR with electrospray ionization mass spectrometry (PCR/ESI-MS) run on an Ibis PLEX-ID high-throughput platform. The biothreat cluster assay identifies most of the potential bioterrorism-relevant microorganisms including Bacillus anthracis, Francisella tularensis, Yersinia pestis, Burkholderia mallei and pseudomallei, Brucella species, and Coxiella burnetii. DNA from 45 different reference materials with different formulations and different concentrations were chosen and sent to a service screening laboratory that uses the PCR/ESI-MS platform to provide a microbial identification service. The standard reference materials were produced out of a repository built up in the framework of the EU funded project âEstablishment of Quality Assurances for Detection of Highly Pathogenic Bacteria of Potential Bioterrorism Riskâ (EQADeBa). All samples were correctly identified at least to the genus level
On Poincare and logarithmic Sobolev inequalities for a class of singular Gibbs measures
This note, mostly expository, is devoted to Poincar{\'e} and log-Sobolev
inequalities for a class of Boltzmann-Gibbs measures with singular interaction.
Such measures allow to model one-dimensional particles with confinement and
singular pair interaction. The functional inequalities come from convexity. We
prove and characterize optimality in the case of quadratic confinement via a
factorization of the measure. This optimality phenomenon holds for all beta
Hermite ensembles including the Gaussian unitary ensemble, a famous exactly
solvable model of random matrix theory. We further explore exact solvability by
reviewing the relation to Dyson-Ornstein-Uhlenbeck diffusion dynamics admitting
the Hermite-Lassalle orthogonal polynomials as a complete set of
eigenfunctions. We also discuss the consequence of the log-Sobolev inequality
in terms of concentration of measure for Lipschitz functions such as maxima and
linear statistics.Comment: Minor improvements. To appear in Geometric Aspects of Functional
Analysis -- Israel Seminar (GAFA) 2017-2019", Lecture Notes in Mathematics
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