Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Trial and Error and Algorithm01:12

Trial and Error and Algorithm

A problem-solving strategy is a plan of action used to find a solution. Different strategies have distinct action plans. Trial and error involves trying different solutions until one works. For instance, to fix a broken printer, you might check ink levels, ensure the paper tray isn't jammed, and verify the printer's connection to your laptop. This method can be time-consuming but is commonly used. Thomas Edison, for example, used trial and error to find a suitable filament for the light bulb,...
Improving Translational Accuracy02:07

Improving Translational Accuracy

Base complementarity between the three base pairs of mRNA codon and the tRNA anticodon is not a failsafe mechanism. Inaccuracies can range from a single mismatch to no correct base pairing at all. The free energy difference between the correct and nearly correct base pairs can be as small as 3 kcal/ mol. With complementarity being the only proofreading step, the estimated error frequency would be one wrong amino acid in every 100 amino acids incorporated. However, error frequencies observed in...
Improving Translational Accuracy02:07

Improving Translational Accuracy

Base complementarity between the three base pairs of mRNA codon and the tRNA anticodon is not a failsafe mechanism. Inaccuracies can range from a single mismatch to no correct base pairing at all. The free energy difference between the correct and nearly correct base pairs can be as small as 3 kcal/ mol. With complementarity being the only proofreading step, the estimated error frequency would be one wrong amino acid in every 100 amino acids incorporated. However, error frequencies observed in...
Methods of Classification and Identification01:28

Methods of Classification and Identification

Bacterial identification relies on a diverse array of techniques to classify and understand microorganisms, each tailored to uncover specific characteristics. Traditional morphological approaches, while still valuable, are limited for closely related or structurally simple organisms. Modern methods integrate biochemical, serological, genetic, and advanced molecular tools to achieve greater accuracy.Morphological and Biochemical TechniquesMorphological characteristics, such as cell shape and...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Knockdown of a metathoracic scent gland desaturase enhances the production of (E)-4-oxo-2-hexenal and suppresses female sexual attractiveness in the plant bug Adelphocoris suturalis.

Insect molecular biology·2017
Same author

RNA interference-mediated knockdown of the Halloween gene Spookiest (CYP307B1) impedes adult eclosion in the western tarnished plant bug, Lygus hesperus.

Insect molecular biology·2016
Same author

Identification and functional characterization of four transient receptor potential ankyrin 1 variants in Apolygus lucorum (Meyer-Dür).

Insect molecular biology·2016
Same author

Identification and characterization of a sex peptide receptor-like transcript from the western tarnished plant bug Lygus hesperus.

Insect molecular biology·2014
Same author

Cloning and expression profiling of odorant-binding proteins in the tarnished plant bug, Lygus lineolaris.

Insect molecular biology·2013
Same author

A string correction algorithm for cursive script recognition.

IEEE transactions on pattern analysis and machine intelligence·2012
Same journal

Relation DETR+: Exploring Explicit Position Relation Prior for Dense Prediction.

IEEE transactions on pattern analysis and machine intelligence·2026
Same journal

RBF++: Quantifying and Optimizing Reasoning Boundaries across Measurable and Unmeasurable Capabilities for Chain-of-Thought Reasoning.

IEEE transactions on pattern analysis and machine intelligence·2026
Same journal

CAFE: Cross-View Adaptive Fusion and Cluster Center Enhancement for Robust Multi-View Clustering.

IEEE transactions on pattern analysis and machine intelligence·2026
Same journal

DIVER: Reinforced Diffusion Breaks Imitation Bottlenecks in End-to-End Autonomous Driving.

IEEE transactions on pattern analysis and machine intelligence·2026
Same journal

Ethics-Aware Safe Reinforcement Learning for Rare-Event Risk Control in Interactive Urban Driving.

IEEE transactions on pattern analysis and machine intelligence·2026
Same journal

Learning Shape Anchors for Holistic Indoor Scene Understanding.

IEEE transactions on pattern analysis and machine intelligence·2026
See all related articles

Related Experiment Videos

Experiments in Text Recognition with Binary n-Gram and Viterbi Algorithms.

J J Hull1, S N Srihari

  • 1Department of Computer Science, State University of New York at Buffalo, Amherst, NY 14226.

IEEE Transactions on Pattern Analysis and Machine Intelligence
|August 27, 2011
PubMed
Summary
This summary is machine-generated.

Binary n-gram and Viterbi algorithms offer improved contextual postprocessing for noisy text, like that from optical character recognition. New implementations enhance efficiency and performance for these powerful text correction methods.

Related Experiment Videos

Area of Science:

  • Natural Language Processing
  • Computational Linguistics
  • Information Theory

Background:

  • Contextual postprocessing is crucial for correcting errors in text generated by noisy channels, such as optical character recognition (OCR).
  • Traditional methods may lack efficiency or require significant computational resources.
  • Binary n-gram and Viterbi algorithms are recognized as promising alternatives for enhancing text accuracy.

Purpose of the Study:

  • To provide a unified theoretical framework for understanding binary n-gram and Viterbi algorithms in text postprocessing.
  • To introduce novel, efficient implementation algorithms for both binary n-gram and Viterbi approaches.
  • To evaluate the performance of these new implementations through extensive experimentation.

Main Methods:

  • Developed a storage-efficient data structure specifically for the binary n-gram algorithm.
  • Formulated a recursive approach for implementing the Viterbi algorithm.
  • Conducted comprehensive experiments to compare the effectiveness of the proposed algorithms.

Main Results:

  • The proposed implementation algorithms demonstrate practical utility and efficiency.
  • Experimental results validate the effectiveness of both binary n-gram and Viterbi algorithms for noisy channel text correction.
  • The new algorithms offer advantages in terms of storage and computational aspects.

Conclusions:

  • Binary n-gram and Viterbi algorithms provide robust solutions for contextual postprocessing of OCR-generated text.
  • The novel implementation strategies enhance the practicality and performance of these algorithms.
  • Further research can leverage these findings for improved text recognition and correction systems.