scholarly journals Maximal Coordinate Discrepancy as Accuracy Criterion of Image Projective Normalization for Optical Recognition of Documents

2020 ◽  
Vol 13 (3) ◽  
pp. 43-58
Author(s):  
I.A. Konovalenko ◽  
◽  
V.V. Kokhan ◽  
D.P. Nikolaev ◽  
◽  
...  
Keyword(s):  
Accuracy Criterion ◽  
Optical Recognition

CSM neural network for degraded printed character optical recognition

2014 ◽  
Vol 25 (5) ◽  
pp. 1171-1186 ◽  
Author(s):  
A. Namane ◽  
A. Guessoum ◽  
E.H. Soubari ◽  
P. Meyrueis
Keyword(s):  
Neural Network ◽  
Optical Recognition

Automated optical recognition of degraded handwritten characters

1992 ◽  
Author(s):  
Emade Darwiche ◽  
Abhijit S. Pandya ◽  
Anil D. Mandalia
Keyword(s):  
Optical Recognition

Different strategies in optical recognition of polychromatic images

1992 ◽  
Vol 31 (14) ◽  
pp. 2560 ◽  
Author(s):  
María S. Millán ◽  
María J. Yzuel ◽  
Juan Campos ◽  
Carlos Ferreira
Keyword(s):  
Optical Recognition

ConvNet-Based Optical Recognition for Engineering Drawings

2017 ◽  
Author(s):  
Andrew Brock ◽  
Theodore Lim ◽  
J. M. Ritchie ◽  
Nick Weston
Keyword(s):  
Object Detection ◽  
Character Recognition ◽  
Optical Character Recognition ◽  
Cross Validation ◽  
Convolutional Networks ◽  
Optical Character ◽  
Engineering Drawings ◽  
Machine Analysis ◽  
Fold Cross Validation ◽  
Optical Recognition

End-to-end machine analysis of engineering document drawings requires a reliable and precise vision frontend capable of localizing and classifying various characters in context. We develop an object detection framework, based on convolutional networks, designed specifically for optical character recognition in engineering drawings. Our approach enables classification and localization on a 10-fold cross-validation of an internal dataset for which other techniques prove unsuitable.

Trading accuracy for speed over the course of a decision

2021 ◽  
Author(s):  
Gerard Derosiere ◽  
David Thura ◽  
Paul Cisek ◽  
Julie Duqué
Keyword(s):  
Late Stage ◽  
Human Subjects ◽  
Sensory Information ◽  
Decision Task ◽  
Unique Extension ◽  
Dynamic Changes ◽  
Performance Accuracy ◽  
Accuracy Criterion ◽  
Speed Accuracy ◽  
Accuracy Tradeoff

Humans and other animals often need to balance the desire to gather sensory information (to make the best choice) with the urgency to act, facing a speed-accuracy tradeoff (SAT). Given the ubiquity of SAT across species, extensive research has been devoted to understanding the computational mechanisms allowing its regulation at different timescales, including from one context to another, and from one decision to another. However, animals must frequently change their SAT on even shorter timescales - i.e., over the course of an ongoing decision - and little is known about the mechanisms that allow such rapid adaptations. The present study aimed at addressing this issue. Human subjects performed a decision task with changing evidence. In this task, subjects received rewards for correct answers but incurred penalties for mistakes. An increase or a decrease in penalty occurring halfway through the trial promoted rapid SAT shifts, favoring speeded decisions either in the early or in the late stage of the trial. Importantly, these shifts were associated with stage-specific adjustments in the accuracy criterion exploited for committing to a choice. Those subjects who decreased the most their accuracy criterion at a given decision stage exhibited the highest gain in speed, but also the highest cost in terms of performance accuracy at that time. Altogether, the current findings offer a unique extension of previous work, by suggesting that dynamic changes in accuracy criterion allow the regulation of the SAT within the timescale of a single decision.

Azine based smart probe for optical recognition and enrichment of Mo(vi )

2018 ◽  
Vol 47 (32) ◽  
pp. 11084-11090 ◽  
Author(s):  
Milan Ghosh ◽  
Sabyasachi Ta ◽  
Jesús Sanmartín Matalobos ◽  
Debasis Das
Keyword(s):  
Aqueous Solution ◽  
Single Crystal ◽  
Green Emission ◽  
Selective Detection ◽  
X Ray ◽  
Optical Recognition

Single crystal X-ray structurally characterized azine derivative (L) was explored for selective detection of Molybdenum (Mo(vi)) cation through green emission. The L was very efficient for enrichment of Mo(vi) from aqueous solution.

Structural-parametric synthesis of the tracking filter based on decomposition by the target functional with adaptation to trajectory disturbances

2021 ◽  
Author(s):  
A.A. Kostoglotov ◽  
A.S. Penkov ◽  
S.V. Lazarenko
Keyword(s):  
Numerical Modeling ◽  
State Assessment ◽  
Estimation Accuracy ◽  
Motion Model ◽  
Parametric Synthesis ◽  
Adaptive Motion ◽  
Accuracy Criterion ◽  
Dynamic Errors ◽  
Tracking Filter ◽  
Kinematic Motion

Traditional Kalman-type tracking filters are based on a kinematic motion model, which leads to the occurrence of dynamic errors, which significantly increase during target maneuvering. One of the solutions to this problem is to develop a model of motion dynamics with the ability to adapt its structure to external influences. It is shown that the use of a dynamic model of motion in the filter, which takes into account the inertia of the target and the forces acting on it, makes it possible to significantly increase the efficiency of the state assessment. Purpose is to development of an algorithm for assessing the position of a maneuvering object, effective in terms of accuracy criterion. The use of an adaptive motion model as part of the filter provides an increase in the estimation accuracy in comparison with the classical Kalman filter, which is confirmed by the performed numerical modeling.

Sign in / Sign up

Export Citation Format

Share Document