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Titlebook: Document Analysis and Recognition - ICDAR 2023; 17th International C Gernot A. Fink,Rajiv Jain,Richard Zanibbi Conference proceedings 2023

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樓主: MEDAL
11#
發(fā)表于 2025-3-23 11:45:38 | 只看該作者
Computational Linguistics Techniquesve experiments show that the proposed method outperforms the existing two-stage cascade models and one-stage end-to-end models with a lighter and faster architecture. Furthermore, the ablation studies verify the generalization of our method, where the proposed modal adapter is effective to bridge va
12#
發(fā)表于 2025-3-23 15:48:04 | 只看該作者
Translator’s Workbench and Translation Aidsructed images to a classifier network. Extensive experiments show that both tasks yield satisfying improvements on the OSTR task, and the full model demonstrates decent performance in recognizing both seen and novel characters.
13#
發(fā)表于 2025-3-23 19:19:44 | 只看該作者
14#
發(fā)表于 2025-3-24 01:27:35 | 只看該作者
15#
發(fā)表于 2025-3-24 04:02:48 | 只看該作者
16#
發(fā)表于 2025-3-24 07:15:46 | 只看該作者
17#
發(fā)表于 2025-3-24 13:39:52 | 只看該作者
18#
發(fā)表于 2025-3-24 17:57:38 | 只看該作者
Conference proceedings 2023n Document Analysis and Recognition, ICDAR 2021, held in San José, CA, USA, in August 2023.?The 53 full papers were carefully reviewed and selected from 316 submissions, and are presented with 101 poster presentations...The papers are organized into the following topical sections: Graphics Recogniti
19#
發(fā)表于 2025-3-24 20:04:16 | 只看該作者
https://doi.org/10.1007/978-3-030-30211-5fectively across multi-language datasets that contain various types of images taken in uncontrolled conditions, and it is small enough to be deployed on virtually any platform including mobile devices.
20#
發(fā)表于 2025-3-25 01:47:14 | 只看該作者
Basic Terminology and Background image features, which significantly reduces the number of tokens at the input of the transformer. Experimental results show how our network is able to obtain competitive results on multiple public benchmarks while running at significantly higher speeds.
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