Zobrazeno 1 - 10
of 532
pro vyhledávání: '"Document images"'
Autor:
Khan Bahadar, Riaz Ahmad, Khursheed Aurangzeb, Siraj Muhammad, Khalil Ullah, Ibrar Hussain, Ikram Syed, Muhammad Shahid Anwar
Publikováno v:
PeerJ Computer Science, Vol 10, p e2089 (2024)
Layout analysis is the main component of a typical Document Image Analysis (DIA) system and plays an important role in pre-processing. However, regarding the Pashto language, the document images have not been explored so far. This research, for the f
Externí odkaz:
https://doaj.org/article/d9275d3fdea94664b896e070c95f58d1
Autor:
Yuhi Matsuo, Yoshimitsu Aoki
Publikováno v:
Sensors, Vol 24, Iss 2, p 654 (2024)
Shadow removal for document images is an essential task for digitized document applications. Recent shadow removal models have been trained on pairs of shadow images and shadow-free images. However, obtaining a large, diverse dataset for document sha
Externí odkaz:
https://doaj.org/article/e99ee82193ed4974b1f923a63e6c6419
Publikováno v:
Automatika, Vol 63, Iss 2, Pp 378-398 (2022)
The proposed research aims to restore deteriorated text sections that are affected by stain markings, ink seepages and document ageing in ancient document photographs, as these challenges confront document enhancement. A tri-level semi-adaptive thres
Externí odkaz:
https://doaj.org/article/0e5eec3e4ff24840a09916b87345ec5f
Publikováno v:
Applied Sciences, Vol 13, Iss 21, p 11783 (2023)
Spam detection has been a topic of extensive research; however, there has been limited focus on multimodal spam detection. In this study, we introduce a novel approach for multilingual multimodal spam detection, presenting the Multilingual and Multim
Externí odkaz:
https://doaj.org/article/1905fc0199a14931863d0e6ea519bb64
Autor:
Yanglem Loijing Khomba Khuman, Salam Dickeeta Devi, Ch. Ponykumar Singh, H. Mamata Devi, N. Ajith Singh
Publikováno v:
Data in Brief, Vol 45, Iss , Pp 108585- (2022)
The Manipuri language is the official language of the Indian state of Manipur. The language belongs to the Tibeto-Burman family of languages. A benchmark Meitei/Meetei script printed document images dataset is presented in this article. The dataset c
Externí odkaz:
https://doaj.org/article/d7fa792a7fa0470198d3388f7662212d
Publikováno v:
کتابداری و اطلاعرسانی, Vol 24, Iss 1, Pp 174-193 (2021)
Objective: The aim of this study is to present a brief discussion of the digital image watermarking for texts in order to prove the documents authentication and copyright protection and to introduce a new method of digital watermarking of printed and
Externí odkaz:
https://doaj.org/article/e34e87d7abb747108ad8074ebeb25569
Algorithm for choosing the best frame in a video stream in the task of identity document recognition
Publikováno v:
Компьютерная оптика, Vol 45, Iss 1, Pp 101-109 (2021)
During the process of document recognition in a video stream using a mobile device camera, the image quality of the document varies greatly from frame to frame. Sometimes recognition system is required not only to recognize all the specified attribut
Externí odkaz:
https://doaj.org/article/bba90e2a65584c94afa13ef422962f98
Autor:
Khurram Azeem Hashmi, Marcus Liwicki, Didier Stricker, Muhammad Adnan Afzal, Muhammad Ahtsham Afzal, Muhammad Zeshan Afzal
Publikováno v:
IEEE Access, Vol 9, Pp 87663-87685 (2021)
The first phase of table recognition is to detect the tabular area in a document. Subsequently, the tabular structures are recognized in the second phase in order to extract information from the respective cells. Table detection and structural recogn
Externí odkaz:
https://doaj.org/article/53c041a60244406e99b1d162d7487cc1
Autor:
Khurram Azeem Hashmi, Didier Stricker, Marcus Liwicki, Muhammad Noman Afzal, Muhammad Zeshan Afzal
Publikováno v:
IEEE Access, Vol 9, Pp 113521-113534 (2021)
This paper presents the novel approach towards table structure recognition by leveraging the guided anchors. The concept differs from current state-of-the-art systems for table structure recognition that naively apply object detection methods. In con
Externí odkaz:
https://doaj.org/article/58a057f6652f44f2b5aa753c244a39ae
Publikováno v:
IEEE Access, Vol 9, Pp 143448-143457 (2021)
Page object detection is crucial for document understanding. Different granularities for objects can result in different performances. In this study, block level region object detection is considered among the inherent hierarchical structure for docu
Externí odkaz:
https://doaj.org/article/c45e6edecbcf4eec832b0c1202a3f471