18,030 research outputs found
Doing and Showing
The persisting gap between the formal and the informal mathematics is due to
an inadequate notion of mathematical theory behind the current formalization
techniques. I mean the (informal) notion of axiomatic theory according to which
a mathematical theory consists of a set of axioms and further theorems deduced
from these axioms according to certain rules of logical inference. Thus the
usual notion of axiomatic method is inadequate and needs a replacement.Comment: 54 pages, 2 figure
Revisiting noninteracting string partition functions in Rindler space
We revisit non-interacting string partition functions in Rindler space by
summing over fields in the spectrum. In field theory, the total partition
function splits in a natural way in a piece that does not contain surface terms
and a piece consisting of solely the so-called edge states. For open strings,
we illustrate that surface contributions to the higher spin fields correspond
to open strings piercing the Rindler origin, unifying the higher spin surface
contributions in string language. For closed strings, we demonstrate that the
string partition function is not quite the same as the sum over the partition
functions of the fields in the spectrum: an infinite overcounting is present
for the latter. Next we study the partition functions obtained by excluding the
surface terms. Using recent results of JHEP 1505 (2015) 106, this construction,
first done by Emparan, can be put on much firmer ground. We generalize to type
II and heterotic superstrings and demonstrate modular invariance. All of these
exhibit an IR divergence that can be interpreted as a maximal acceleration
close to the black hole horizon. Ultimately, since these partition functions
are only part of the full story, divergences here should not be viewed as a
failure of string theory: maximal acceleration is a feature of a faulty
treatment of the higher spin fields in the string spectrum. We comment on the
relevance of this to Solodukhin's recent proposal. A possible link with the
firewall paradox is apparent.Comment: 33 pages, v2: added several clarifications including a section on the
difference between closed strings and the sum-of-fields approach, matches
published versio
Integrating Multiple Sketch Recognition Methods to Improve Accuracy and Speed
Sketch recognition is the computer understanding of hand drawn diagrams. Recognizing sketches instantaneously is necessary to build beautiful interfaces with real time feedback. There are various techniques to quickly recognize sketches into ten or twenty classes. However for much larger datasets of sketches from a large number of classes, these existing techniques can take an extended period of time to accurately classify an incoming sketch and require significant computational overhead. Thus, to make classification of large datasets feasible, we propose using multiple stages of recognition.
In the initial stage, gesture-based feature values are calculated and the trained model is used to classify the incoming sketch. Sketches with an accuracy less than a threshold value, go through a second stage of geometric recognition techniques. In the second geometric stage, the sketch is segmented, and sent to shape-specific recognizers. The sketches are matched against predefined shape descriptions, and confidence values are calculated. The system outputs a list of classes that the sketch could be classified as, along with the accuracy, and precision for each sketch. This process both significantly reduces the time taken to classify such huge datasets of sketches, and increases both the accuracy and precision of the recognition
Integrating Multiple Sketch Recognition Methods to Improve Accuracy and Speed
Sketch recognition is the computer understanding of hand drawn diagrams. Recognizing sketches instantaneously is necessary to build beautiful interfaces with real time feedback. There are various techniques to quickly recognize sketches into ten or twenty classes. However for much larger datasets of sketches from a large number of classes, these existing techniques can take an extended period of time to accurately classify an incoming sketch and require significant computational overhead. Thus, to make classification of large datasets feasible, we propose using multiple stages of recognition.
In the initial stage, gesture-based feature values are calculated and the trained model is used to classify the incoming sketch. Sketches with an accuracy less than a threshold value, go through a second stage of geometric recognition techniques. In the second geometric stage, the sketch is segmented, and sent to shape-specific recognizers. The sketches are matched against predefined shape descriptions, and confidence values are calculated. The system outputs a list of classes that the sketch could be classified as, along with the accuracy, and precision for each sketch. This process both significantly reduces the time taken to classify such huge datasets of sketches, and increases both the accuracy and precision of the recognition
Interactive interpretation of structured documents: Application to the recognition of handwritten architectural plans
International audienceThis paper addresses a whole architecture, including the IMISketch method. IMISketch method incorporates two aspects: document analysis and interactivity. This paper describes a global vision of all the parts of the project. IMISketch is a generic method for an interactive interpretation of handwritten sketches. The analysis of complex documents requires the management of uncertainty. While, in practice the similar methods often induce a large combinatorics, IMISketch method presents several optimization strategies to reduce the combinatorics. The goal of these optimizations is to have a time analysis compatible with user expectations. The decision process is able to solicit the user in the case of strong ambiguity: when it is not sure to make the right decision, the user explicitly validates the right decision to avoid a fastidious a posteriori verification phase due to propagation of errors.This interaction requires solving two major problems: how interpretation results will be presented to the user, and how the user will interact with analysis process. We propose to study the effects of those two aspects. The experiments demonstrate that (i) a progressive presentation of the analysis results, (ii) user interventions during it and (iii) the user solicitation by the analysis process are an efficient strategy for the recognition of complex off-line documents.To validate this interactive analysis method, several experiments are reported on off-line handwritten 2D architectural floor plans
Interacting Dipoles from Matrix Formulation of Noncommutative Gauge Theories
We study the IR behavior of noncommutative gauge theory in the matrix
formulation. We find that in this approach, the nature of the UV/IR mixing is
easily understood, which allows us to perform a reliable calculation of the
quantum effective action for the long wavelength modes of the noncommutative
gauge field. At one loop, we find that our description is weakly coupled only
in the supersymmetric theory. At two loops, we find non-trivial interaction
terms suggestive of dipole degrees of freedom. These dipoles exhibit a channel
duality reminiscent of string theory.Comment: LaTeX 11 pages, 4 figures; v.2 minor changes and some references
added; v.3 many more technical details added and significantly different
presentation, use REVTeX 4, to appear in PR
ChemInk: A Natural Real-Time Recognition System for Chemical Drawings
We describe a new sketch recognition framework for chemical structure drawings that combines multiple levels of visual features using a jointly trained conditional random field. This joint model of appearance at different levels of detail makes our framework less sensitive to noise and drawing variations, improving accuracy and robustness. In addition, we present a novel learning-based approach to corner detection that achieves nearly perfect accuracy in our domain. The result is a recognizer that is better able to handle the wide range of drawing styles found in messy freehand sketches. Our system handles both graphics and text, producing a complete molecular structure as output. It works in real time, providing visual feedback about the recognition progress. On a dataset of chemical drawings our system achieved an accuracy rate of 97.4%, an improvement over the best reported results in literature. A preliminary user study also showed that participants were on average over twice as fast using our sketch-based system compared to ChemDraw, a popular CAD-based tool for authoring chemical diagrams. This was the case even though most of the users had years of experience using ChemDraw and little or no experience using Tablet PCs.National Science Foundation (U.S.) (Grant 0729422)United States. Dept. of Homeland Security (Graduate Research Fellowship)Pfizer Inc
On-line hand-drawn electric circuit diagram recognition using 2D dynamic programming
9 pagesInternational audienceIn order to facilitate sketch recognition, most online existing works assume that people will not start to draw a new symbol before the current one has been finished. We propose in this paper a method that relaxes this constraint. The proposed methodology relies on a two-dimensional dynamic programming (2D-DP) technique allowing symbol hypothesis generation, which can correctly segment and recognize interspersed symbols. In addition, as discriminative classifiers usually have limited capability to reject outliers, some domain specific knowledge is included to circumvent those errors due to untrained patterns corresponding to erroneous segmentation hypotheses. With a point-level measurement, the experiment shows that the proposed novel approach is able to achieve an accuracy of more than 90 percent
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