Zobrazeno 1 - 3
of 3
pro vyhledávání: '"Arsen Yeghiazaryan"'
Publikováno v:
IEEE Access, Vol 10, Pp 39261-39268 (2022)
Key information extraction from unstructured documents is a practical problem in many industries. Machine learning models aimed at solving this problem should efficiently utilize textual, visual, and 2D spatial layout information of the document. Gri
Externí odkaz:
https://doaj.org/article/9d84748d49cb449c9cba260365ee559c
Publikováno v:
IEEE Access. 10:39261-39268
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::41661b500d0caf0b12c5a16a3e260efd
https://doi.org/10.1109/access.2022.3164674
https://doi.org/10.1109/access.2022.3164674
Autor:
Grigory Sapunov
Accelerate deep learning and other number-intensive tasks with JAX, Google's awesome high-performance numerical computing library.The JAX numerical computing library tackles the core performance challenges at the heart of deep learning and other scie
