Tasvirdagi matnlarni tanib olish uchun neyron tarmoqlari
tashabbuskorliklari
Mavzuna Xayrullo qizi Karimova
mavzunakarimova71@gmail.com
Muqaddas Baxtiyor qizi Madayeva
muqaddasmadayeva@gmail.com
Annotatsiya
: Matnni aniqlash, shuningdek, optik belgilarni aniqlash sifatida ham
tanilgan, bosma yoki qo’lda yozilgan matnni tahrirlash, qidirish va tahlil qilish oson
bo’lgan raqamli formatga aylantiradi. Bu matn tasvirlarini tahlil qilishni va ulardagi
belgilar va so’zlarni tanib olishni o’z ichiga oladi. Optik belgilarni aniqlash - bu
hujjatlarni skanerlashga bo’lgan talab ortib borayotgani va ma’lumotlarni samarali va
aniq yozib olish zarurati tufayli tez rivojlanayapti. Optik belgilarni aniqlash ko’plab
sohalarda, jumladan bank, sog’liqni saqlash, hukumat va ta’limda muhim
texnologiyaga aylandi. Optik belgilarni aniqlash bozoridagi ba’zi imkoniyatlarga
quyidagilar kiradi: Katta ma’lumotlar tahlilining yuksalishi: Har kuni hosil bo’ladigan
raqamli ma’lumotlar ortib borayotganligi sababli, optik belgilarni aniqlash tasvir va
hujjatlar kabi tuzilmagan ma’lumotlar manbalaridan ma’lumotlarni skanerlashi va
olishi mumkin. Mashinani o’rganish va chuqur o’rganish yutuqlari: optik belgilarni
aniqlash ilg’or mashinani o’rganish algoritmlari va chuqur neyron tarmoqlar
yordamida sezilarli darajada yaxshilanishi mumkin, bu aniqlik va samaradorlikni
oshiradi.
Kalit so’zlar:
neyron tarmoq, algoritm, rasm, tasvir, CNN, RNN, model
arxitekturasi
Neural network initiatives for image text recognition
Mavzuna Xayrullo kizi Karimova
mavzunakarimova71@gmail.com
Muqaddas Baxtiyor kizi Madayeva
muqaddasmadayeva@gmail.com
Abstract:
Text recognition, also known as optical character recognition, converts
printed or handwritten text into a digital format that is easy to edit, search, and analyze.
It involves analyzing text images and recognizing characters and words in them.
Optical character recognition is rapidly developing due to the increasing demand for
document scanning and the need to capture data efficiently and accurately. Optical
"Science and Education" Scientific Journal / Impact Factor 3.848
May 2023 / Volume 4 Issue 5
www.openscience.uz / ISSN 2181-0842
707
character recognition has become an important technology in many industries,
including banking, healthcare, government, and education. Some of the opportunities
in the optical character recognition market include: The rise of big data analytics:
Digital data generated every day as data increases, optical character recognition can
scan and retrieve data from unstructured data sources such as images and documents.
Advances in machine learning and deep learning: Optical character recognition can be
greatly improved with advanced machine learning algorithms and deep neural
networks, increasing accuracy and efficiency.
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