作者: OPINE 時間: 2025-3-21 23:07
ALEC: An Accurate, Light and Efficient Network for CAPTCHA Recognitionplaced by depthwise separable convolutions to improve computational efficiency. The architecture utilizes group convolution and convolution channels reduction to build a deep narrow network, which reduces the model parameters and improves generalization performance. Additionally, effective and effic作者: Exterior 時間: 2025-3-22 01:52 作者: 異常 時間: 2025-3-22 08:18 作者: FIR 時間: 2025-3-22 09:34
Background Removal of French University Diplomasd. So, we propose an approach for the separation of textual and non-textual components, based on Fuzzy C-Means clustering. After obtaining clustered pixels, a local window based thresholding approach and the Savoula binarization technique is used to correctly classify pixels, into the category of te作者: Mingle 時間: 2025-3-22 16:07 作者: Mingle 時間: 2025-3-22 20:44 作者: macabre 時間: 2025-3-22 22:14 作者: Obliterate 時間: 2025-3-23 01:27 作者: Ventilator 時間: 2025-3-23 06:22 作者: indices 時間: 2025-3-23 12:09 作者: 漂泊 時間: 2025-3-23 14:06
Arie Kuyvenhoven,Olga Memedovic,Nico Windtd. So, we propose an approach for the separation of textual and non-textual components, based on Fuzzy C-Means clustering. After obtaining clustered pixels, a local window based thresholding approach and the Savoula binarization technique is used to correctly classify pixels, into the category of te作者: angiography 時間: 2025-3-23 21:49 作者: 國家明智 時間: 2025-3-23 23:34
Arie Kuyvenhoven,Olga Memedovic,Nico Windtdetection in both business documents and technical articles. By training with .-13., we demonstrate the feasibility of a single solution that can report superior performance compared to the equivalent ones trained with a much larger amount of data, for table detection. We hope that our dataset helps作者: Communal 時間: 2025-3-24 05:18 作者: ERUPT 時間: 2025-3-24 07:02
https://doi.org/10.1007/978-3-319-14042-1 Besides, it is worth mentioning that this module does not have any trainable parameters. Experiments conducted on the ICDAR 2019 ReCTS competition dataset demonstrate that our approach significantly outperforms the state-of-the-art techniques. In addition, we also verify the generalization performance of our method on the CTW dataset.作者: mortuary 時間: 2025-3-24 11:18
Approach to the Adult Hypospadias Patientii) Fine Tuning?+?Self Training. We discuss details on how these popular approaches in Machine Learning can be adapted to the text recognition problem of our interest. We hope, our empirical observations on two different languages will be of relevance to wider use cases in text recognition.作者: Somber 時間: 2025-3-24 15:34
Th. Mayer,K. Fritzsche,S. Weiss,M. T. Lutzents (image and text), which performs better than other popular self-supervised methods, including supervised ImageNet pre-training, on document image classification scenarios with a limited amount of data.作者: 展覽 時間: 2025-3-24 22:56
Funktionelle neurologische St?rungenents, we point out the problems caused by the use of SE-blocks in existing CMU-Nets and suggest how to use SE-blocks in CMU-Nets. We use the Document Image Binarization?(DIBCO) 2017 dataset to evaluate the proposed model.作者: oxidant 時間: 2025-3-25 00:13 作者: Virtues 時間: 2025-3-25 05:15
Shinichi Ichimura,Tsuneaki Satority and monotonicity to predict the quality of document images. Based on the proposed network along with the new losses, the obtained DCNN achieves the state-of-the-art quality assessment performance on the public datasets. The source codes and pre-trained models are available at ..作者: curettage 時間: 2025-3-25 09:28 作者: 青少年 時間: 2025-3-25 11:50 作者: 包裹 時間: 2025-3-25 18:55
Adapting OCR with Limited Supervisionii) Fine Tuning?+?Self Training. We discuss details on how these popular approaches in Machine Learning can be adapted to the text recognition problem of our interest. We hope, our empirical observations on two different languages will be of relevance to wider use cases in text recognition.作者: 整理 時間: 2025-3-25 22:48 作者: Myofibrils 時間: 2025-3-26 01:17 作者: BIPED 時間: 2025-3-26 07:37
Dewarping Document Image by Displacement Flow Estimation with Fully Convolutional Networkth Constraint (LSC) in regularization. Our approach is easy to implement and consumes moderate computing resource. Experiments proved that our approach can dewarp document images effectively under various geometric distortions, and has achieved the state-of-the-art performance in terms of local details and overall effect.作者: 結果 時間: 2025-3-26 10:45 作者: 設施 時間: 2025-3-26 16:26
Conference proceedings 2020wing topical sections: character and text recognition; document image processing; segmentation and layout analysis; word embedding and spotting; text detection; and font design and classification..Due to the Corona pandemic the conference was held as a virtual event ..作者: 丑惡 時間: 2025-3-26 20:35 作者: zonules 時間: 2025-3-26 23:08
Classification of Phonetic Characters by Space-Filling Curvesof diacritics. In this paper, we propose a phonetic character recognition process based on a space-filling curves approach. We proposed an original method adapted to this particular data set, able to finely classify, with more than 70% of accuracy, noisy and specific characters.作者: Phonophobia 時間: 2025-3-27 04:33 作者: 責任 時間: 2025-3-27 07:24 作者: MAL 時間: 2025-3-27 11:01
Conference proceedings 2020in July 2020...The 40 full papers presented in this book were carefully reviewed and selected from 57 submissions. The papers are grouped in the following topical sections: character and text recognition; document image processing; segmentation and layout analysis; word embedding and spotting; text 作者: 類似思想 時間: 2025-3-27 17:24 作者: CORE 時間: 2025-3-27 18:31 作者: 交響樂 時間: 2025-3-28 01:57
https://doi.org/10.1007/978-3-030-57058-3deep learning for document analysis systems; document analysis systems; historical document analysis; d作者: 信條 時間: 2025-3-28 03:00
978-3-030-57057-6Springer Nature Switzerland AG 2020作者: 自愛 時間: 2025-3-28 08:35
Lecture Notes in Computer Sciencehttp://image.papertrans.cn/e/image/282299.jpg作者: minaret 時間: 2025-3-28 13:30 作者: Robust 時間: 2025-3-28 18:38 作者: 常到 時間: 2025-3-28 19:18
Approach to the Adult Hypospadias Patientype of data that is used for training. In the presence of diverse style in the document images (eg. fonts, print, writer, imaging process), creating a large amount of training data is impossible. In this paper, we explore the problem of adapting an existing OCR, already trained for a specific collec作者: ARIA 時間: 2025-3-29 00:37 作者: Jejune 時間: 2025-3-29 05:56 作者: PALSY 時間: 2025-3-29 10:36 作者: 并入 時間: 2025-3-29 11:39
https://doi.org/10.1007/978-981-16-8603-0he Linguistic Atlas of France (ALF) maps are composed of printed phonetic words used to locate how words were pronounced over the country. Those words were printed using the Rousselot-Gillieron alphabet (extension of Latin alphabet) which bring character recognition problems due to the large number 作者: collateral 時間: 2025-3-29 17:49 作者: 時代錯誤 時間: 2025-3-29 21:32
Funktionelle neurologische St?rungenearch is suggested for solving complex document analysis studies. However, improving performance by adding U-Net modules requires using too many parameters in cascaded U-Nets. Therefore, in this paper, we propose a method for enhancing the performance of cascaded U-Nets. We suggest a novel document 作者: apiary 時間: 2025-3-30 03:42
https://doi.org/10.1057/9780230244986 In this paper, we propose a novel framework for both rectifying distorted document image and removing background finely, by estimating pixel-wise displacements using a fully convolutional network (FCN). The document image is rectified by transformation according to the displacements of pixels. The 作者: 同謀 時間: 2025-3-30 04:44
Shinichi Ichimura,Tsuneaki Satoacter recognition (OCR) accuracy. However, even despite the ill-posed nature of image super-resolution (SR) problem, how do we treat the finer details of text with large upscale factors and suppress noises and artifacts at the same time, especially for low quality document images is still a challeng作者: 淺灘 時間: 2025-3-30 08:26 作者: Delectable 時間: 2025-3-30 15:31
Shinichi Ichimura,Tsuneaki Satoical character recognition (OCR) performance prior to any actual recognition, but also provides immediate feedback on whether the documents meet the quality requirements for other high level document processing and analysis tasks. In this work, we present a deep neural network (DNN) to accomplish th作者: Benzodiazepines 時間: 2025-3-30 20:18
Arie Kuyvenhoven,Olga Memedovic,Nico Windts work we focus on decorated background removal and the extraction of textual components from French university diploma. As far as we know, this is the very first attempt to resolve this kind of problem on French university diploma images. Hence, we make our dataset public for further research, rela作者: 最初 時間: 2025-3-30 21:24
Transition in Central and Eastern Europeon is a key step in table understanding. Nowadays, the most successful methods for table detection in document images employ deep learning algorithms; and, particularly, a technique known as .. In this context, such a technique exports the knowledge acquired to detect objects in natural images to de作者: 琺瑯 時間: 2025-3-31 03:00
Arie Kuyvenhoven,Olga Memedovic,Nico Windtmanually annotating the bounding boxes of graphical or page objects in publicly available annual reports. This dataset contains a total of 13. annotated page images with objects in five different popular categories—table, figure, natural image, logo, and signature. It is the largest manually annotat作者: abduction 時間: 2025-3-31 08:43 作者: 致命 時間: 2025-3-31 12:27
Maximum Entropy Regularization and Chinese Text Recognitionlasses, which causes a serious overfitting problem. We propose to apply Maximum Entropy Regularization to regularize the training process, which is to simply add a negative entropy term to the canonical cross-entropy loss without any additional parameters and modification of a model. We theoreticall
