Zobrazeno 1 - 10
of 15
pro vyhledávání: '"Ashok C. Popat"'
Autor:
Chen-Yu Lee, Chu Wang, Yasuhisa Fujii, Chun-Liang Li, Ashok C. Popat, Renshen Wang, Tomas Pfister, Siyang Qin
Publikováno v:
ACL/IJCNLP (2)
Natural reading orders of words are crucial for information extraction from form-like documents. Despite recent advances in Graph Convolutional Networks (GCNs) on modeling spatial layout patterns of documents, they have limited ability to capture rea
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b89a00b489f35e16ef6f144927934194
http://arxiv.org/abs/2106.10786
http://arxiv.org/abs/2106.10786
Autor:
R. Channing Moore, Manoj Plakal, Shawn Hershey, Aren Jansen, Rif A. Saurous, Daniel P. W. Ellis, Ashok C. Popat
Publikováno v:
ICASSP
Humans do not acquire perceptual abilities in the way we train machines. While machine learning algorithms typically operate on large collections of randomly-chosen, explicitly-labeled examples, human acquisition relies more heavily on multimodal uns
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3533adfecacf51f3482a45c45cde20b0
Publikováno v:
ICDAR
Many studies on (Offline) Handwritten Text Recognition (HTR) systems have focused on building state-of-the-art models for line recognition on small corpora. However, adding HTR capability to a large scale multilingual OCR system poses new challenges.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b2db5b81b2ea4fd46a8d94b247032d88
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783030022839
GREC
GREC
This document summarizes the discussion of the interest group on Graphics Syntax in the Deep Learning Age that took place in the 12th IAPR International Workshop on Graphics Recognition (GREC).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::36ca9e3077df5007385504903dc2275c
https://doi.org/10.1007/978-3-030-02284-6_13
https://doi.org/10.1007/978-3-030-02284-6_13
Publikováno v:
ICDAR
We describe a novel line-level script identification method. Previous work repurposed an OCR model generating per-character script codes, counted to obtain line-level script identification. This has two shortcomings. First, as a sequence-to-sequence
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::fd989e5a86502c3a8553b3973814aa82
http://arxiv.org/abs/1708.04671
http://arxiv.org/abs/1708.04671
Publikováno v:
HIP@ICDAR
This paper describes an approach to estimating the unknown publication date for printed historical documents from their scanned page images, using Convolutional Neural Networks (CNN). The method primarily harnesses visual features from small image pa
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::20bc0bd448ebb5de4e5fa81718424c6d
https://doi.org/10.1145/2809544.2809550
https://doi.org/10.1145/2809544.2809550
Publikováno v:
ICDAR
Hidden Markov Model (HMM)-based classifiers have been successfully used for sequential labeling problems such as speech recognition and optical character recognition for decades. They have been especially successful in the domains where the segmentat
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::640ed11f734f46e410fe68a3991b9f2c
https://doi.org/10.1109/icdar.2015.7333863
https://doi.org/10.1109/icdar.2015.7333863
Publikováno v:
MOCR@ICDAR
While current OCR systems are able to recognize text in an increasing number of scripts and languages, typically they still need to be told in advance what those scripts and languages are. We propose an approach that repurposes the same HMM-based sys
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::97776d94e191e4690eea6ff78baa7a5d
https://doi.org/10.1145/2505377.2505382
https://doi.org/10.1145/2505377.2505382
Autor:
Andrew W. Senior, Frank Yung-Fong Tang, Ashok C. Popat, Eugene Ie, Nemanja Spasojevic, Dmitriy Genzel, Michael Edward Jahr
Publikováno v:
ICDAR
Optical character recognition is carried out using techniques borrowed from statistical machine translation. In particular, the use of multiple simple feature functions in linear combination, along with minimum-error-rate training, integrated decodin
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::77b3712e3afe281b05b0b3056eee26e9
https://doi.org/10.1109/icdar.2011.269
https://doi.org/10.1109/icdar.2011.269
Autor:
Ashok C. Popat
Publikováno v:
ACM Symposium on Document Engineering
In a large-scale book scanning operation, material can vary widely in language, script, genre, domain, print quality, and other factors, giving rise to a corresponding variability in the OCRed text. It is often desirable to automatically detect error
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a3d2287a7eb978e4e69d2399a0425236
https://doi.org/10.1145/1600193.1600237
https://doi.org/10.1145/1600193.1600237