標題: Titlebook: Document Analysis and Recognition - ICDAR 2023; 17th International C Gernot A. Fink,Rajiv Jain,Richard Zanibbi Conference proceedings 2023 [打印本頁] 作者: Constrict 時間: 2025-3-21 18:43
書目名稱Document Analysis and Recognition - ICDAR 2023影響因子(影響力)
書目名稱Document Analysis and Recognition - ICDAR 2023影響因子(影響力)學科排名
書目名稱Document Analysis and Recognition - ICDAR 2023網絡公開度
書目名稱Document Analysis and Recognition - ICDAR 2023網絡公開度學科排名
書目名稱Document Analysis and Recognition - ICDAR 2023被引頻次
書目名稱Document Analysis and Recognition - ICDAR 2023被引頻次學科排名
書目名稱Document Analysis and Recognition - ICDAR 2023年度引用
書目名稱Document Analysis and Recognition - ICDAR 2023年度引用學科排名
書目名稱Document Analysis and Recognition - ICDAR 2023讀者反饋
書目名稱Document Analysis and Recognition - ICDAR 2023讀者反饋學科排名
作者: 四海為家的人 時間: 2025-3-22 00:04
Document Analysis and Recognition - ICDAR 2023978-3-031-41685-9Series ISSN 0302-9743 Series E-ISSN 1611-3349 作者: tattle 時間: 2025-3-22 03:19 作者: prostate-gland 時間: 2025-3-22 08:37 作者: 假 時間: 2025-3-22 10:05
Paola Gentile,María Luisa Rodríguez Mu?ozion accuracy and non-character rejection capability. The classifier can be trained on both character samples and string samples but real string samples are usually insufficient. In this paper, we proposed a learning method for segmentation-based online handwritten Chinese text recognition with a con作者: 車床 時間: 2025-3-22 14:49 作者: 車床 時間: 2025-3-22 18:12 作者: NAIVE 時間: 2025-3-22 23:27
Pharmaceutical Industry Performancel NLP models constitutes an intuitive solution. However, due to the difficulty of recognizing handwriting and the error propagation problem, optimized architectures are required. Recognition-free approaches proved to be robust, but often produce poorer results compared to recognition-based methods. 作者: 向外 時間: 2025-3-23 03:21
Pharmaceutical Industry Performancepower of language models in this context is the existence of many specialized domains with language statistics very different from those implied by a general language model - think of checks, medical prescriptions, and many other specialized document classes. This paper introduces an algorithm for e作者: inculpate 時間: 2025-3-23 06:05
https://doi.org/10.1007/978-3-319-50042-3sed OCR systems are computationally expensive because they rely on computationally expensive pretraining over text images. To address this challenge, we propose a robust architecture that utilizes a custom CNN block with a Transformer encoder for image understanding and a pre-trained Transformer dec作者: galley 時間: 2025-3-23 10:17
Pharmaceutical Industry Performanceon, spelling correction, and beautification. Writing is personal and usually the processing is done on-device. Ink generative models thus need to produce high quality content quickly, in a resource constrained environment..In this work, we study ways to maximize the quality of the output of a traine作者: 致敬 時間: 2025-3-23 17:22 作者: obsession 時間: 2025-3-23 20:04 作者: GLUT 時間: 2025-3-24 01:40
Translating Samuel Beckett into Hindicognizes the characters one after the other through an attention-based prediction process until reaching the end of the document. However, this autoregressive process leads to inference that cannot benefit from any parallelization optimization. In this paper, we propose Faster DAN, a two-step strate作者: Armory 時間: 2025-3-24 02:25 作者: Cirrhosis 時間: 2025-3-24 07:33
Case Study I: Key Concepts and Approachy used models for this task fail to generalize to long-form data and how this problem can be solved by augmenting the training data, changing the model architecture and the inference procedure. These methods use contrastive learning technique and are tailored specifically for the handwriting domain.作者: Omniscient 時間: 2025-3-24 11:06 作者: 帶來的感覺 時間: 2025-3-24 16:59
https://doi.org/10.1007/978-3-030-52527-9 area of HTR that has garnered particular interest is the transcription of historical documents, as there is a vast amount of records available that have yet to be processed, potentially resulting in a loss of information due to deterioration..Currently, the most widely used HTR approach is to train作者: 散步 時間: 2025-3-24 22:22
Critical Approaches to Children‘s Literatureethods can be used to adapt a general model to the target dataset. We show that in the case of neural networks trained for handwriting recognition using CTC, simple fine-tuning with data augmentation works surprisingly well in such scenarios and that it is resistant to overfitting even for very smal作者: Hectic 時間: 2025-3-25 01:47 作者: 和平 時間: 2025-3-25 04:42 作者: Adenocarcinoma 時間: 2025-3-25 08:25
978-3-031-41684-2The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl作者: 健談的人 時間: 2025-3-25 13:24 作者: 歌唱隊 時間: 2025-3-25 15:57 作者: FRET 時間: 2025-3-25 21:20 作者: Highbrow 時間: 2025-3-26 02:11
Translating Statistics to Make Decisionsarameterization, which grows cubically with respect to the hypercomplex dimension. We attain good word and character error rate at only a small fraction of the memory footprint of non-hypercomplex models as well as previous non-shared operation hypercomplex ones (up to . size reduction).作者: Antagonist 時間: 2025-3-26 05:11 作者: COKE 時間: 2025-3-26 09:47 作者: murmur 時間: 2025-3-26 13:27
What a difference gender makes !to add those samples with a high confidence of correctness to the training set. Experimental results on IAM benchmark task show that OCR model trained with augmented DDPM-synthesized training samples can achieve about . relative word error rate reduction compared with the one trained on real data only.作者: 無能性 時間: 2025-3-26 16:52
Paola Gentile,María Luisa Rodríguez Mu?ozd loss function for improving non-character resistance, and weakly supervised learning on both character and string samples for improving recognition performance. Experimental results on the CASIA-OLHWDB and ICDAR2013-Online datasets show that the proposed method can achieve promising recognition performance without training data augmentation.作者: 健談的人 時間: 2025-3-26 21:37
https://doi.org/10.1007/978-3-319-50042-3 several publicly available datasets including UPTI, NUST-UHWR, and MMU-OCR-21. We also combined printed and handwriting datasets to train our architecture and propose a single unified model; capable of recognizing both printed and handwritten text for maximum variations of fonts and writing styles with state-of-the-art results.作者: 卡死偷電 時間: 2025-3-27 02:02 作者: Congestion 時間: 2025-3-27 07:58 作者: Intruder 時間: 2025-3-27 09:41
Improved Learning for?Online Handwritten Chinese Text Recognition with?Convolutional Prototype Netwod loss function for improving non-character resistance, and weakly supervised learning on both character and string samples for improving recognition performance. Experimental results on the CASIA-OLHWDB and ICDAR2013-Online datasets show that the proposed method can achieve promising recognition performance without training data augmentation.作者: 一起平行 時間: 2025-3-27 17:04 作者: Debate 時間: 2025-3-27 20:43
Faster DAN: Multi-target Queries with?Document Positional Encoding for?End-to-End Handwritten Documets compared to standard DAN, while being at least 4 times faster on whole single-page and double-page images of the RIMES 2009, READ 2016 and MAURDOR datasets. Source code and trained model weights are available at ..作者: Commemorate 時間: 2025-3-27 23:58
Shared-Operation Hypercomplex Networks for?Handwritten Text Recognitionarameterization, which grows cubically with respect to the hypercomplex dimension. We attain good word and character error rate at only a small fraction of the memory footprint of non-hypercomplex models as well as previous non-shared operation hypercomplex ones (up to . size reduction).作者: 全部 時間: 2025-3-28 05:13
Precise Segmentation for?Children Handwriting Analysis by?Combining Multiple Deep Models with?Onlineions provided by the detector with a segmentation lattice computed from the online signal. An ablation study shows that both contributions are relevant, and their combination is efficient enough for immediate feedback and achieves state of the art results even compared to more informed systems.作者: Synovial-Fluid 時間: 2025-3-28 07:07
Pharmaceutical Industry Performancebest use this model the paper also introduces a modified CTC beam search decoder which effectively allows hypotheses to remain in contention based on possible future completion of vocabulary words. The result is a substantial reduction in word error rate in recognizing material from specialized domains.作者: 大洪水 時間: 2025-3-28 11:46 作者: 喪失 時間: 2025-3-28 15:03
Critical Approaches to Children‘s Literaturetwork, both in writer-dependent and writer-independent settings. On a large real-world dataset, fine-tuning on new writers provided an average relative CER improvement of 25% for 16 text lines and 50% for 256 text lines.作者: 詩集 時間: 2025-3-28 21:37 作者: PHON 時間: 2025-3-29 00:46 作者: deadlock 時間: 2025-3-29 06:26
Fine-Tuning is a?Surprisingly Effective Domain Adaptation Baseline in?Handwriting Recognitiontwork, both in writer-dependent and writer-independent settings. On a large real-world dataset, fine-tuning on new writers provided an average relative CER improvement of 25% for 16 text lines and 50% for 256 text lines.作者: SEEK 時間: 2025-3-29 08:16 作者: 向外才掩飾 時間: 2025-3-29 13:21
Improving Handwritten OCR with?Training Samples Generated by?Glyph Conditional Denoising Diffusion Pve to collect. To mitigate the issue, we propose a denoising diffusion probabilistic model (DDPM) to generate training samples. This model conditions on a printed glyph image and creates mappings between printed characters and handwritten images, thus enabling the generation of photo-realistic handw作者: 震驚 時間: 2025-3-29 16:00 作者: Juvenile 時間: 2025-3-29 22:28
Vision Conformer: Incorporating Convolutions into?Vision Transformer LayersViT) adapt transformers for image recognition tasks. In order to do this, the images are split into patches and used as tokens. One issue with ViT is the lack of inductive bias toward image structures. Because ViT was adapted for image data from language modeling, the network does not explicitly han作者: 察覺 時間: 2025-3-30 03:50 作者: 抒情短詩 時間: 2025-3-30 04:35
Exploring Semantic Word Representations for?Recognition-Free NLP on?Handwritten Document Imagesl NLP models constitutes an intuitive solution. However, due to the difficulty of recognizing handwriting and the error propagation problem, optimized architectures are required. Recognition-free approaches proved to be robust, but often produce poorer results compared to recognition-based methods. 作者: 忙碌 時間: 2025-3-30 09:26
OCR Language Models with?Custom Vocabulariespower of language models in this context is the existence of many specialized domains with language statistics very different from those implied by a general language model - think of checks, medical prescriptions, and many other specialized document classes. This paper introduces an algorithm for e作者: Foregery 時間: 2025-3-30 16:07 作者: 設施 時間: 2025-3-30 17:02 作者: enlist 時間: 2025-3-30 22:02
Linguistic Knowledge Within Handwritten Text Recognition Models: A Real-World Case Studyon layers, which perform recognition over sequences of characters. This architecture may lead to the model learning statistical linguistic features of the training corpus, over and above graphic features. This in turn could lead to degraded performance if the evaluation dataset language differs from作者: 冰雹 時間: 2025-3-31 02:54 作者: 過份艷麗 時間: 2025-3-31 08:44
Faster DAN: Multi-target Queries with?Document Positional Encoding for?End-to-End Handwritten Documecognizes the characters one after the other through an attention-based prediction process until reaching the end of the document. However, this autoregressive process leads to inference that cannot benefit from any parallelization optimization. In this paper, we propose Faster DAN, a two-step strate作者: Chagrin 時間: 2025-3-31 11:11 作者: 不足的東西 時間: 2025-3-31 17:05
DSS: Synthesizing Long Digital Ink Using Data Augmentation, Style Encoding and?Split Generationy used models for this task fail to generalize to long-form data and how this problem can be solved by augmenting the training data, changing the model architecture and the inference procedure. These methods use contrastive learning technique and are tailored specifically for the handwriting domain.作者: 動機 時間: 2025-3-31 18:24
Precise Segmentation for?Children Handwriting Analysis by?Combining Multiple Deep Models with?Onlineigh performance for both tasks is necessary to give personalized feedback to children who are learning how to write. The first contribution is to combine the predictions of an accurate Seq2Seq model with the predictions of a R-CNN object detector. The second one is to refine the bounding box predict作者: 輕浮女 時間: 2025-3-31 23:04
Fine-Tuning Vision Encoder–Decoder Transformers for?Handwriting Text Recognition on?Historical Docum area of HTR that has garnered particular interest is the transcription of historical documents, as there is a vast amount of records available that have yet to be processed, potentially resulting in a loss of information due to deterioration..Currently, the most widely used HTR approach is to train作者: 吸氣 時間: 2025-4-1 05:47 作者: Substance 時間: 2025-4-1 08:22 作者: hyperuricemia 時間: 2025-4-1 12:54 作者: CURL 時間: 2025-4-1 17:28
María Luisa Rodríguez Mu?oz,Paola Gentilee the CNN, we proposed to reconstruct the image data after the self-attention in a reverse embedding layer. Through the evaluation, we demonstrate that the proposed convolutions help improve the classification ability of ViT.作者: 會議 時間: 2025-4-1 19:46
John S. Morrison,Michael J. Hagemaner interaction is beneficial for the fine-grained Chinese calligraphy style classification task. The multi-scale attention mechanism can highlight the informative part of the image at multiple scales, which can boost the classification performance. Since the profile image can give clues about the st作者: prediabetes 時間: 2025-4-1 23:34
Pharmaceutical Industry Performancedictive at word image level compared to classical static embedding methods. Furthermore, our recognition-free approach with pre-trained semantic information outperforms recognition-free as well as recognition-based approaches from the literature on several Named Entity Recognition benchmark datasets作者: Mobile 時間: 2025-4-2 06:43
Pharmaceutical Industry Performancevement in the recognizability of the synthetic inks, in some cases more than halving the character error rate metric, and describe a way to select the optimal combination of sampling and ranking techniques for any given computational budget.
