找回密碼
 To register

QQ登錄

只需一步,快速開始

掃一掃,訪問微社區(qū)

打印 上一主題 下一主題

Titlebook: Document Analysis and Recognition – ICDAR 2023 Workshops; San José, CA, USA, A Mickael Coustaty,Alicia Fornés Conference proceedings 2023 T

[復(fù)制鏈接]
樓主: LEVEE
41#
發(fā)表于 2025-3-28 15:39:06 | 只看該作者
42#
發(fā)表于 2025-3-28 20:55:37 | 只看該作者
43#
發(fā)表于 2025-3-29 00:08:30 | 只看該作者
Electron Holography: AlAs/GaAs Superlatticesgnition, is ligatures. A combination of a specific two or more character sequence takes a different shape than what those characters normally look like when they appear in a similar position. Deep learning-based systems are widely used for text recognition these days. In this work, we investigate th
44#
發(fā)表于 2025-3-29 05:25:09 | 只看該作者
Hugh Rudnick,Constantin Velásquezble performance in addressing the task; however, most of these approaches rely on vast amounts of data from large-scale knowledge graphs or language models pretrained on voluminous corpora. In this paper, we hone in on the effective utilization of solely the knowledge supplied by a corpus to create
45#
發(fā)表于 2025-3-29 10:47:32 | 只看該作者
46#
發(fā)表于 2025-3-29 13:32:11 | 只看該作者
Hugh Rudnick,Constantin Velásquezwas not left behind with first Transformer based models for DU dating from late 2019. However, the computational complexity of the self-attention operation limits their capabilities to small sequences. In this paper we explore multiple strategies to apply Transformer based models to long multi-page
47#
發(fā)表于 2025-3-29 18:47:18 | 只看該作者
Final-drive/Differential and Axle Shafts,e-art results. In this paper, we propose KAP a pre-trained model adapted for the domain specificity for corporate documents. KAP takes into account the domain specificity of corporate documents and proposes a model that integrates the local context of each word (i.e the words at the top, bottom, and
48#
發(fā)表于 2025-3-29 22:58:14 | 只看該作者
49#
發(fā)表于 2025-3-30 02:42:27 | 只看該作者
50#
發(fā)表于 2025-3-30 07:25:48 | 只看該作者
Macmillan Motor Vehicle Engineering Seriess always a challenging task. On the other hand, large volumes of public training datasets related to administrative documents such as invoices are rare to find. In this work, we use Graph Attention Network model for information extraction. This type of model makes it easier to understand the mechani
 關(guān)于派博傳思  派博傳思旗下網(wǎng)站  友情鏈接
派博傳思介紹 公司地理位置 論文服務(wù)流程 影響因子官網(wǎng) 吾愛論文網(wǎng) 大講堂 北京大學 Oxford Uni. Harvard Uni.
發(fā)展歷史沿革 期刊點評 投稿經(jīng)驗總結(jié) SCIENCEGARD IMPACTFACTOR 派博系數(shù) 清華大學 Yale Uni. Stanford Uni.
QQ|Archiver|手機版|小黑屋| 派博傳思國際 ( 京公網(wǎng)安備110108008328) GMT+8, 2025-10-31 04:58
Copyright © 2001-2015 派博傳思   京公網(wǎng)安備110108008328 版權(quán)所有 All rights reserved
快速回復(fù) 返回頂部 返回列表
六安市| 精河县| 潼南县| 新丰县| 武汉市| 砚山县| 贵德县| 小金县| 揭阳市| 綦江县| 南涧| 阿巴嘎旗| 绥宁县| 罗山县| 江津市| 沁水县| 庆城县| 宣汉县| 永安市| 封丘县| 绥棱县| 班戈县| 博爱县| 聂荣县| 牡丹江市| 福贡县| 项城市| 绥德县| 和平县| 淮北市| 当雄县| 巴马| 阜宁县| 韩城市| 普陀区| 彭泽县| 察雅县| 宜兰县| 宜良县| 平谷区| 四川省|