Suchergebnisse - computer learning and pattern recognition::text/((document OR dokumenty) OR document) processing

PICK: Processing Key Information Extraction from Documents using Improved Graph Learning-Convolutional Networks von Yu, Wenwen, Lu, Ning, Qi, Xianbiao, Gong, Ping, Xiao, Rong

“… Computer vision with state-of-the-art deep learning models has achieved huge success in the field of Optical Character Recognition (OCR …”
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Robust text line detection in historical documents: learning and evaluation methods von Boillet, Mélodie, Kermorvant, Christopher, Paquet, Thierry

“… Text line segmentation is one of the key steps in historical document understanding …”
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Hate speech recognition in multilingual text: hinglish documents von Yadav, Arun Kumar, Kumar, Mohit, Kumar, Abhishek, Shivani, Kusum, Yadav, Divakar

“… Sometimes users wield abusive or inflammatory language, that may provoke readers. This paper aims to evaluate various machine learning and deep learning techniques to detect hate speech on various social media platforms in the Hinglish …”
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Document-level sentiment classification: An empirical comparison between SVM and ANN von Moraes, Rodrigo, Valiati, João Francisco, Gavião Neto, Wilson P.

“… ► SVM have been extensively and successfully used as a sentiment learning approach …”
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Deformity removal from handwritten text documents using variable cycle GAN von Nigam, Shivangi, Behera, Adarsh Prasad, Verma, Shekhar, Nagabhushan, P.

“… Text recognition systems typically work well for printed documents but struggle with handwritten documents due to different writing styles, background complexities, added noise of image acquisition …”
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Evaluation of algorithms for Multi-Modality Whole Heart Segmentation: An open-access grand challenge von Zhuang, Xiahai, Li, Lei, Payer, Christian, Štern, Darko, Urschler, Martin, Heinrich, Mattias P., Oster, Julien, Wang, Chunliang, Smedby, Örjan, Bian, Cheng, Yang, Xin, Heng, Pheng-Ann, Mortazi, Aliasghar, Bagci, Ulas, Yang, Guanyu, Sun, Chenchen, Galisot, Gaetan, Ramel, Jean-Yves, Brouard, Thierry, Tong, Qianqian, Si, Weixin, Liao, Xiangyun, Zeng, Guodong, Shi, Zenglin, Zheng, Guoyan, Wang, Chengjia, MacGillivray, Tom, Newby, David, Rhode, Kawal, Ourselin, Sebastien, Mohiaddin, Raad, Keegan, Jennifer, Firmin, David, Yang, Guang

“… ) challenge, in conjunction with MICCAI 2017.•This work introduces the related information to the challenge, discusses the results from the conventional methods and deep learning-based algorithms, and provides insights to the future research …”
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Metric learning for text documents von Lebanon, G.

“… Many algorithms in machine learning rely on being given a good distance metric over the input space …”
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DANIEL: A fast Document Attention Network for Information Extraction and Labelling of handwritten documents von Constum, Thomas, Tranouez, Pierrick, Paquet, Thierry

“… : Document Layout Analysis, Handwritten Text Recognition, and Named Entity Recognition. Recent approaches have attempted to integrate these steps into a single process using fully end-to-end architectures …”
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A segmentation-free method for image retrieval and pattern spotting in historical documents using convolutional features von Curi, Zacarias, Nicolas, Stéphane, Tranouez, Pierrick, M. Saavedra, Jose, de Souza Britto Jr, Alceu, Heutte, Laurent

“… This paper describes a new segmentation-free method for retrieving images and spotting patterns in historical document image collections …”
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Multimodal interactive handwritten text transcription von Romero, Verónica, Romero, Verónica, Toselli, Alejandro Héctor, Vidal, Enrique

“… This book presents an interactive multimodal approach for efficient transcription of handwritten text images …”
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I2DFormer+: Learning Image to Document Summary Attention for Zero-Shot Image Classification von Naeem, Muhammad Ferjad, Xian, Yongqin, Gool, Luc Van, Tombari, Federico

“… Despite the tremendous progress in zero-shot learning (ZSL), the majority of existing methods still rely on human-annotated attributes, which are difficult to annotate and scale …”
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Multiple Document Datasets Pre-training Improves Text Line Detection With Deep Neural Networks von Boillet, Melodie, Kermorvant, Christopher, Paquet, Thierry

“… In this paper, we introduce a fully convolutional network for the document layout analysis task …”
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ROBDD-TrOCRBERTa: a novel robust-optimized blurred document text deblurring and completion with DCGAN-TrOCR and DistilRoBERTa von Ranjan, Arti, Ravinder, M.

“… because the quality of the text has deteriorated over time. The proposed Robust Optimized Blurred Document Text Deblurring and Text Recognition (ROBDD-TrOCRBERTa …”
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Contribution of recurrent connectionist language models in improving LSTM-based Arabic text recognition in videos von Yousfi, Sonia, Berrani, Sid-Ahmed, Garcia, Christophe

“… Unconstrained text recognition in videos is a very challenging task that begins to draw the attention of the OCR community …”
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Large text document summarization based on an enhanced fuzzy logic approach von Yadav, Avaneesh Kumar, Ranvijay, Ranvijay, Yadav, Rama Shankar, Kumar, Vivek

“… looking for. In this paper, we propose an extractive text summarization approach that utilizes fuzzy logic to determine the relevance and importance of sentences in a multi-document such as legal documents, news …”
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An end-to-end pipeline for historical censuses processing von Petitpierre, Rémi, Kramer, Marion, Rappo, Lucas

“… Censuses are structured documents of great value for social and demographic history, which became widespread from the nineteenth century …”
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EAML: ensemble self-attention-based mutual learning network for document image classification von Bakkali, Souhail, Ming, Zuheng, Coustaty, Mickaël, Rusiñol, Marçal

“… As many document types have a distinct visual style, learning only visual features with deep CNNs to classify document images has encountered the problem of low inter-class discrimination, and high …”
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A survey of historical document image datasets von Nikolaidou, Konstantina, Seuret, Mathias, Mokayed, Hamam, Liwicki, Marcus

“… Finding appropriate datasets for historical document analysis is a crucial prerequisite to facilitate research using different machine learning algorithms …”
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Learning to detect, localize and recognize many text objects in document images from few examples von Moysset, Bastien, Kermorvant, Christopher, Wolf, Christian

“… In this work, we particularly target the detection of text in document images and we propose a new neural model which directly predicts object coordinates …”
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In-domain versus out-of-domain transfer learning for document layout analysis: In-domain versus out-of-domain transfer learning von De Nardin, Axel, Zottin, Silvia, Piciarelli, Claudio, Foresti, Gian Luca, Colombi, Emanuela

“… on which to train deep learning models. A notable example is represented by the task of document layout analysis in handwritten documents, which requires pixel-precise …”
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