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Метод автоматичного розпізнавання та безпечної обробки даних користувачів в логістичних системах

Метод автоматичного розпізнавання та безпечної обробки даних користувачів в логістичних системах

Abstract

Обробка рукописних даних користувачів у логістиці залишається актуальною проблемою. Дослідження спрямоване на розробку методу, що автоматизує обробку таких даних та забезпечує їх безпечне передавання. Метою роботи є підвищення ефективності обробки та передачі даних користувачів при виконанні логістичних операцій

Keywords

EasyOCR, optical character recognition, handwritten text processing, data protection, AES, cryptography, автоматичне розпізнавання тексту, Raspberry Pi, оптичне розпізнавання символів, алгоритм Левенштейна, Levenshtein algorithm, image processing, OCR, криптографія, RSA, logistics systems, обробка рукописного тексту, automatic text recognition, обробка зображень, захист даних, логістичні системи, Python

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    popularity
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    influence
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    impulse
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Green