Cargando…
A Smart Visual Sensing Concept Involving Deep Learning for a Robust Optical Character Recognition under Hard Real-World Conditions
In this study, we propose a new model for optical character recognition (OCR) based on both CNNs (convolutional neural networks) and RNNs (recurrent neural networks). The distortions affecting the document image can take different forms, such as blur (focus blur, motion blur, etc.), shadow, bad cont...
Autores principales: | Mohsenzadegan, Kabeh, Tavakkoli, Vahid, Kyamakya, Kyandoghere |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9414947/ https://www.ncbi.nlm.nih.gov/pubmed/36015785 http://dx.doi.org/10.3390/s22166025 |
Ejemplares similares
-
A Deep-Learning Based Visual Sensing Concept for a Robust Classification of Document Images under Real-World Hard Conditions
por: Mohsenzadegan, Kabeh, et al.
Publicado: (2021) -
A Visual Sensing Concept for Robustly Classifying House Types through a Convolutional Neural Network Architecture Involving a Multi-Channel Features Extraction
por: Tavakkoli, Vahid, et al.
Publicado: (2020) -
Contribution to Speeding-Up the Solving of Nonlinear Ordinary Differential Equations on Parallel/Multi-Core Platforms for Sensing Systems
por: Tavakkoli, Vahid, et al.
Publicado: (2020) -
A Novel Recurrent Neural Network-Based Ultra-Fast, Robust, and Scalable Solver for Inverting a “Time-Varying Matrix”
por: Tavakkoli, Vahid, et al.
Publicado: (2019) -
A Virtual Sensing Concept for Nitrogen and Phosphorus Monitoring Using Machine Learning Techniques
por: Paepae, Thulane, et al.
Publicado: (2022)