Reading Text on Both Sides of a Sheet of Paper with a Neural Network Classifier

Haolian Shi; Rahul Komatinenir; Yuan Max; Cédric Pradalier; Leor Jacobi; Yikun Jiang; Alexandre Locquet; D. S. Citrin

doi:10.1109/irmmw-thz61557.2025.11319691

Reading Text on Both Sides of a Sheet of Paper with a Neural Network Classifier

Haolian Shi
, Rahul Komatinenir
, Yuan Max
, Cédric Pradalier
, Leor Jacobi
, Yikun Jiang
, Alexandre Locquet
, D. S. Citrin

Department of Jewish Art

GT-CNRS UMI 2958
Georgia Institute of Technology
Peking University

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

This work explores the imaging of characters written in iron gall ink on both sides of a sheet of paper using THz-TDS measurements. A convolutional neural network is trained to classify each pixel, providing an estimation of text presence on both sides. Experimental validation is conducted on single- and two-sheet samples, with limitations observed in the readability of the back side.

Original language	English
Title of host publication	50th International Conference on Infrared, Millimeter, and Terahertz Waves, IRMMW-THz 2025
Publisher	IEEE Computer Society
ISBN (Electronic)	9798350378832
DOIs	https://doi.org/10.1109/irmmw-thz61557.2025.11319691
State	Published - 2025
Event	50th International Conference on Infrared, Millimeter, and Terahertz Waves, IRMMW-THz 2025 - Espoo, Finland Duration: 17 Aug 2025 → 22 Aug 2025

Publication series

Name	International Conference on Infrared, Millimeter, and Terahertz Waves, IRMMW-THz
ISSN (Print)	2162-2027
ISSN (Electronic)	2162-2035

Conference

Conference	50th International Conference on Infrared, Millimeter, and Terahertz Waves, IRMMW-THz 2025
Country/Territory	Finland
City	Espoo
Period	17/08/25 → 22/08/25

Bibliographical note

Publisher Copyright:
© 2025 IEEE.

Access to Document

10.1109/irmmw-thz61557.2025.11319691

Cite this

Shi, H., Komatinenir, R., Max, Y., Pradalier, C., Jacobi, L., Jiang, Y., Locquet, A., & Citrin, D. S. (2025). Reading Text on Both Sides of a Sheet of Paper with a Neural Network Classifier. In 50th International Conference on Infrared, Millimeter, and Terahertz Waves, IRMMW-THz 2025 (International Conference on Infrared, Millimeter, and Terahertz Waves, IRMMW-THz). IEEE Computer Society. https://doi.org/10.1109/irmmw-thz61557.2025.11319691

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abstract = "This work explores the imaging of characters written in iron gall ink on both sides of a sheet of paper using THz-TDS measurements. A convolutional neural network is trained to classify each pixel, providing an estimation of text presence on both sides. Experimental validation is conducted on single- and two-sheet samples, with limitations observed in the readability of the back side.",

author = "Haolian Shi and Rahul Komatinenir and Yuan Max and C{\'e}dric Pradalier and Leor Jacobi and Yikun Jiang and Alexandre Locquet and Citrin, \{D. S.\}",

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Shi, H, Komatinenir, R, Max, Y, Pradalier, C, Jacobi, L, Jiang, Y, Locquet, A & Citrin, DS 2025, Reading Text on Both Sides of a Sheet of Paper with a Neural Network Classifier. in 50th International Conference on Infrared, Millimeter, and Terahertz Waves, IRMMW-THz 2025. International Conference on Infrared, Millimeter, and Terahertz Waves, IRMMW-THz, IEEE Computer Society, 50th International Conference on Infrared, Millimeter, and Terahertz Waves, IRMMW-THz 2025, Espoo, Finland, 17/08/25. https://doi.org/10.1109/irmmw-thz61557.2025.11319691

Reading Text on Both Sides of a Sheet of Paper with a Neural Network Classifier. / Shi, Haolian; Komatinenir, Rahul; Max, Yuan et al.
50th International Conference on Infrared, Millimeter, and Terahertz Waves, IRMMW-THz 2025. IEEE Computer Society, 2025. (International Conference on Infrared, Millimeter, and Terahertz Waves, IRMMW-THz).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AU - Shi, Haolian

AU - Komatinenir, Rahul

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AU - Jacobi, Leor

AU - Jiang, Yikun

AU - Locquet, Alexandre

AU - Citrin, D. S.

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AB - This work explores the imaging of characters written in iron gall ink on both sides of a sheet of paper using THz-TDS measurements. A convolutional neural network is trained to classify each pixel, providing an estimation of text presence on both sides. Experimental validation is conducted on single- and two-sheet samples, with limitations observed in the readability of the back side.

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Shi H, Komatinenir R, Max Y, Pradalier C, Jacobi L, Jiang Y et al. Reading Text on Both Sides of a Sheet of Paper with a Neural Network Classifier. In 50th International Conference on Infrared, Millimeter, and Terahertz Waves, IRMMW-THz 2025. IEEE Computer Society. 2025. (International Conference on Infrared, Millimeter, and Terahertz Waves, IRMMW-THz). doi: 10.1109/irmmw-thz61557.2025.11319691

Reading Text on Both Sides of a Sheet of Paper with a Neural Network Classifier

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