Results 51 to 60 of about 2,879 (227)
Automatic Receipt Recognition System Based on Artificial Intelligence Technology
In this study, an automatic receipt recognition system (ARRS) is developed. First, a receipt is scanned for conversion into a high-resolution image. Receipt characters are automatically placed into two categories according to the receipt characteristics:
Cheng-Jian Lin +2 more
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A system for the off-line recognition of handwritten text [PDF]
A new system for the recognition of handwritten text is described. The system goes from raw, binary scanned images of census forms to ASCII transcriptions of the fields contained within the forms. The first step is to locate and extract the handwritten input from the forms.
openaire +2 more sources
SCUT-EPT: New Dataset and Benchmark for Offline Chinese Text Recognition in Examination Paper
Most existing studies and public datasets for handwritten Chinese text recognition are based on the regular documents with clean and blank background, lacking research reports for handwritten text recognition on challenging areas such as educational ...
Yuanzhi Zhu +5 more
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Data‐Driven Materials Science for Energy‐Sustainable Applications
Data‐driven approaches powered by artificial intelligence are transforming materials discovery for energy sustainability. This review examines how auto‐generated high‐quality materials databases and domain‐specific language models accelerate research in photovoltaics, thermoelectrics, batteries and magnetic materials. Applications involve extraction of
Jacqueline M. Cole
wiley +1 more source
Machine Learning Approach for Arabic Handwritten Recognition
Text recognition is an important area of the pattern recognition field. Natural language processing (NLP) and pattern recognition have been utilized efficiently in script recognition.
A. M. Mutawa +2 more
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A Research on Handwritten Text Recognition
Over the years we have started accumulating handwritten documents, like pdfs, doc files and numerous other formats for reading, writing and studying. Often we come across situations where we need to utilize the text of those documents. Manually transcribing large amounts of handwritten data is an arduous process that’s bound to be fraught with errors ...
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On‐Chip Photonic Neural Network Architectures
This review presents a comprehensive overview of on‐chip photonic neural network architectures, covering key photonic building blocks, representative network types, and emerging applications. Recent advances, implementation challenges, and future directions are examined, highlighting the potential of integrated photonics to enable ultrafast, energy ...
Seokjin Hong +7 more
wiley +1 more source
Multimodal Handwritten Exam Text Recognition Based on Deep Learning
To address the complex challenge of recognizing mixed handwritten text in practical scenarios such as examination papers and to overcome the limitations of existing methods that typically focus on a single category, this paper proposes MHTR, a Multimodal
Hua Shi +4 more
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This study explores how information processing is distributed between brains and bodies through a codesign approach. Using the “backpropagation through soft body” framework, brain–body coupling agents are developed and analyzed across several tasks in which output is generated through the agents’ physical dynamics.
Hiroki Tomioka +3 more
wiley +1 more source
Handwritten documents are, as always, highly challenging for recognition tasks compared to printed documents. Rather than using isolated characters as elementary components for recognition, practical documents use words or character strings.
Mamatarani Das, Mrutyunjaya Panda
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