作者: 清真寺 時(shí)間: 2025-3-21 22:39 作者: judiciousness 時(shí)間: 2025-3-22 02:21
M. C. Sacchi,I. Tritto,P. Locatellie, represents each character as a sequence of control points of stroke contours and is frequently used in born-digital documents. T. is organized by a deep neural network, so-called Transformer. Transformer is originally proposed for sequential data, such as text, and therefore appropriate for handl作者: exceed 時(shí)間: 2025-3-22 05:06
N. Kashiwa,J. Yoshitake,T. Tsutsuispond to words, a text line is a cluster of boxes and a paragraph is a cluster of lines. These clusters form a two-level tree that represents a major part of the layout of a document. We use a graph convolutional network to predict the relations between text detection boxes and then build both level作者: 密碼 時(shí)間: 2025-3-22 12:26 作者: ineptitude 時(shí)間: 2025-3-22 16:33 作者: ineptitude 時(shí)間: 2025-3-22 20:12 作者: decode 時(shí)間: 2025-3-23 00:40 作者: Curmudgeon 時(shí)間: 2025-3-23 02:40
https://doi.org/10.1057/9781403907714lly adapted to Information Extraction in business documents. However, most pre-training tasks proposed in the literature for business documents are too generic and not sufficient to learn more complex structures. In this paper, we use LayoutLM, a language model pre-trained on a collection of busines作者: DIS 時(shí)間: 2025-3-23 07:49 作者: Crepitus 時(shí)間: 2025-3-23 13:02
Sustainable Communities and Moral Valuesed of about 100,000 handwritten simple pages in a tabular format. We created a complete pipeline that goes from the scan of double pages to text prediction while minimizing the need for segmentation labels. We describe how weighted finite state transducers, writer specialization and self-training fu作者: 輕率的你 時(shí)間: 2025-3-23 14:45 作者: FLINT 時(shí)間: 2025-3-23 20:08 作者: FORGO 時(shí)間: 2025-3-24 01:52 作者: Petechiae 時(shí)間: 2025-3-24 03:55 作者: Ancestor 時(shí)間: 2025-3-24 10:09
Transition Towards a Sustainable Futures, to automatically generated data from advanced acquisition techniques. The manual analysis of this data is typically time consuming, and can be subject to human error and bias. Therefore, we present in this work a set of Pattern Analysis Software Tools (PAST), which are dedicated to the automatic 作者: 彈藥 時(shí)間: 2025-3-24 13:43
The Rise and Fall of Socialist Planningall its attested variants. It is usually created with high effort by scholars in the humanities, possibly separated by chronological or geographical boundaries, over several years. During the editing process, scholars in the humanities prefer to work with any tools and documents in any format they a作者: Bucket 時(shí)間: 2025-3-24 15:52 作者: Visual-Field 時(shí)間: 2025-3-24 19:14 作者: frivolous 時(shí)間: 2025-3-25 02:45 作者: Synchronism 時(shí)間: 2025-3-25 03:25 作者: 污點(diǎn) 時(shí)間: 2025-3-25 09:21 作者: 樣式 時(shí)間: 2025-3-25 14:22
Font Shape-to-Impression Translatione analysis, i.e., multi-label classification and translation. A quantitative evaluation shows that our Transformer-based approaches estimate the font impressions from a set of local parts more accurately than other approaches. A qualitative evaluation then indicates the important local parts for a specific impression.作者: 擦試不掉 時(shí)間: 2025-3-25 16:41 作者: relieve 時(shí)間: 2025-3-25 21:46
Recognition and?Information Extraction in?Historical Handwritten Tables: Toward Understanding Early rther improved our results. We also introduce through this communication two annotated datasets for handwriting recognition that are now publicly available, and an open-source toolkit to apply WFST on CTC lattices.作者: 刻苦讀書 時(shí)間: 2025-3-26 02:28
Historical Map Toponym Extraction for Efficient Information Retrievalor research and educational purposes. Then, we propose a novel approach for toponym classification based on KAZE descriptor. Next we compare and evaluate several state-of-the-art methods for text and object detection on our toponym detection task. We further show the results of toponym text recognition using popular Tesseract engine.作者: apiary 時(shí)間: 2025-3-26 08:19
The Winner Takes It All: Choosing the?“best” Binarization Algorithm for?Photographed Documentsor portable devices have space and processing limitations that allow to implement only the “best” algorithm. This paper presents the methodology and assesses the time-quality performance of 61 binarization algorithms to choose the most time-quality efficient one, under two criteria.作者: grovel 時(shí)間: 2025-3-26 10:38
Information Extraction from Handwritten Tables in Historical Documentsach that is based on heuristic rules to extract information in historical pre-printed forms with handwritten information. We analyze how each approach performs at each step of the extraction process. The proposed approaches improve the heuristic-rule baseline by up to 0.14 F-measure points throughout the information extraction pipeline.作者: Interim 時(shí)間: 2025-3-26 16:40
Tsuyoshi Kato,Eddy Maerten,Antoine Baceiredoe analysis, i.e., multi-label classification and translation. A quantitative evaluation shows that our Transformer-based approaches estimate the font impressions from a set of local parts more accurately than other approaches. A qualitative evaluation then indicates the important local parts for a specific impression.作者: exorbitant 時(shí)間: 2025-3-26 20:26 作者: 阻止 時(shí)間: 2025-3-26 21:25
Sustainable Communities and Moral Valuesrther improved our results. We also introduce through this communication two annotated datasets for handwriting recognition that are now publicly available, and an open-source toolkit to apply WFST on CTC lattices.作者: Axillary 時(shí)間: 2025-3-27 05:06
Chandrakanta B. Prasan,Joshua N. Danielor research and educational purposes. Then, we propose a novel approach for toponym classification based on KAZE descriptor. Next we compare and evaluate several state-of-the-art methods for text and object detection on our toponym detection task. We further show the results of toponym text recognition using popular Tesseract engine.作者: 蠟燭 時(shí)間: 2025-3-27 06:08
M. C. Sacchi,I. Tritto,P. Locatellis suitable for font style classification, where such structures are very important. In this paper, we experimentally show the applicability of T. in character and font style recognition tasks, while observing how the individual control points contribute to classification results.作者: metropolitan 時(shí)間: 2025-3-27 12:57 作者: 松雞 時(shí)間: 2025-3-27 13:43
Transition States of Biochemical Processes pipeline. Furthermore, we propose a novel method to align the output with the input text, thus facilitating system inspection and auditing. Our experiments on four real-world datasets show that the proposed method is an alternative to classical pipelines. The source code is available at ..作者: SUGAR 時(shí)間: 2025-3-27 20:50 作者: GUEER 時(shí)間: 2025-3-27 22:31
A Multilingual Approach to?Scene Text Visual Question Answeringilingual VQA models with a minimal loss in performance in languages not used during training, as well as a multilingual model trained in multiple languages that match the performance of the respective monolingual baselines.作者: 調(diào)整 時(shí)間: 2025-3-28 02:17 作者: 油膏 時(shí)間: 2025-3-28 08:37 作者: Firefly 時(shí)間: 2025-3-28 10:41 作者: HAIRY 時(shí)間: 2025-3-28 16:18
https://doi.org/10.1007/978-981-97-5756-5ach that is based on heuristic rules to extract information in historical pre-printed forms with handwritten information. We analyze how each approach performs at each step of the extraction process. The proposed approaches improve the heuristic-rule baseline by up to 0.14 F-measure points throughout the information extraction pipeline.作者: sterilization 時(shí)間: 2025-3-28 20:52 作者: LAITY 時(shí)間: 2025-3-28 23:59 作者: AIL 時(shí)間: 2025-3-29 04:51 作者: 最后一個(gè) 時(shí)間: 2025-3-29 08:42 作者: 增強(qiáng) 時(shí)間: 2025-3-29 13:30
Unified Line and?Paragraph Detection by?Graph Convolutional Networksspond to words, a text line is a cluster of boxes and a paragraph is a cluster of lines. These clusters form a two-level tree that represents a major part of the layout of a document. We use a graph convolutional network to predict the relations between text detection boxes and then build both level作者: Cognizance 時(shí)間: 2025-3-29 16:44
The Winner Takes It All: Choosing the?“best” Binarization Algorithm for?Photographed Documentshe time elapsed in binarization varies widely between algorithms and also depends on the document features. On the other hand, document applications for portable devices have space and processing limitations that allow to implement only the “best” algorithm. This paper presents the methodology and a作者: Guaff豪情痛飲 時(shí)間: 2025-3-29 21:13 作者: 放逐 時(shí)間: 2025-3-30 03:05 作者: 團(tuán)結(jié) 時(shí)間: 2025-3-30 06:32 作者: 無思維能力 時(shí)間: 2025-3-30 11:43 作者: Inexorable 時(shí)間: 2025-3-30 12:42 作者: Dysplasia 時(shí)間: 2025-3-30 18:27
Recognition and?Information Extraction in?Historical Handwritten Tables: Toward Understanding Early ed of about 100,000 handwritten simple pages in a tabular format. We created a complete pipeline that goes from the scan of double pages to text prediction while minimizing the need for segmentation labels. We describe how weighted finite state transducers, writer specialization and self-training fu作者: 鋼筆記下懲罰 時(shí)間: 2025-3-30 22:40
Importance of Textlines in Historical Document Classificationleading to its design, and the main findings. The solved tasks include script and font classification, document origin localization, and dating. We combined patch-level and line-level approaches, where the line-level system utilizes an existing, publicly available page layout analysis engine. In bot作者: 合唱隊(duì) 時(shí)間: 2025-3-31 03:53
Historical Map Toponym Extraction for Efficient Information Retrieval villages and landscape features such as rivers, forests etc. The detected and recognized toponyms are utilized as keywords in an information retrieval system that allows intelligent and efficient searching in historical map collections. We create a novel annotated dataset that is freely available f作者: 有斑點(diǎn) 時(shí)間: 2025-3-31 08:32
Information Extraction from Handwritten Tables in Historical Documentsn information extraction from handwritten structured historical documents. In this paper, we compare two Machine Learning approaches and another approach that is based on heuristic rules to extract information in historical pre-printed forms with handwritten information. We analyze how each approach作者: voluble 時(shí)間: 2025-3-31 09:13
