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Titlebook: Document Analysis Systems; 16th IAPR Internatio Giorgos Sfikas,George Retsinas Conference proceedings 2024 The Editor(s) (if applicable) an

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樓主: collude
11#
發(fā)表于 2025-3-23 12:31:53 | 只看該作者
12#
發(fā)表于 2025-3-23 15:53:11 | 只看該作者
https://doi.org/10.1007/978-1-349-06578-3g the outcome of legal decisions concerning the appellant. In contrast, the LJEE refers to extracting out the phrases/clauses that led to the final decision. To promote research in developing such a system for Pakistani legal documents, this paper also introduces the VerdictVaultPK dataset. The data
13#
發(fā)表于 2025-3-23 19:36:11 | 只看該作者
d signatures as distinct classes within an object detection framework, effectively handling both detection and verification. We employ a DINO-based network augmented with a dilation module to detect and verify signatures on check images simultaneously. Our approach achieves an AP of 99.2 for genuine
14#
發(fā)表于 2025-3-23 23:36:46 | 只看該作者
15#
發(fā)表于 2025-3-24 02:44:54 | 只看該作者
16#
發(fā)表于 2025-3-24 08:02:20 | 只看該作者
other hand, the CFP uses a Local-Fusion Attention mechanism(LFA) to capture Discrepancy information adaptively among different scales. This approach reduces the model’s sensitivity to scale variations and significantly improves its generalization capabilities across diverse document layouts. Further
17#
發(fā)表于 2025-3-24 14:10:44 | 只看該作者
18#
發(fā)表于 2025-3-24 15:16:35 | 只看該作者
19#
發(fā)表于 2025-3-24 19:50:26 | 只看該作者
20#
發(fā)表于 2025-3-25 01:59:08 | 只看該作者
sent work focuses on occlusions caused by the spotlight effect. We propose a new algorithm, DocLightDetect, which uses image segmentation as a preprocessing step to improve the accuracy of classifying occlusions caused by the spotlight effect in identification documents. The effectiveness of DocLigh
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