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

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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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Robust text line detection in historical documents: learning and evaluation methods von Boillet, Mélodie, Kermorvant, Christopher, Paquet, Thierry

“… Text line segmentation is one of the key steps in historical document understanding …”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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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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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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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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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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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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Robust Text Detection in Natural Scene Images von Yin, Xu-Cheng, Yin, Xuwang, Huang, Kaizhu, Hao, Hong-Wei

“… distance metric learning algorithm. The posterior probabilities of text candidates corresponding to non-text are estimated with a character classifier …”
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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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Low-Complexity Approximate Convolutional Neural Networks von Cintra, Renato J., Duffner, Stefan, Garcia, Christophe, Leite, Andre

“… In this paper, we present an approach for minimizing the computational complexity of the trained convolutional neural networks (ConvNets). The idea is to …”
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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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Automatic recognition of conceptualization zones in scientific articles and two life science applications von Liakata, Maria, Saha, Shyamasree, Dobnik, Simon, Batchelor, Colin, Rebholz-Schuhmann, Dietrich

“… Here we present the means to facilitate automatic access to the scientific discourse of articles by automating the recognition of 11 categories at the sentence level, which we call Core Scientific Concepts (CoreSCs). These include …”
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Scene text detection and recognition with advances in deep learning: a survey von Liu, Xiyan, Meng, Gaofeng, Pan, Chunhong

“… Scene text detection and recognition has become a very active research topic in recent several years …”
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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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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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Automatic Text Summarization Methods: A Comprehensive Review von Sharma, Grishma, Sharma, Deepak

“… Automatic text summarization can save time and helps in selecting the important and relevant sentences from the document …”
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PageNet: Towards End-to-End Weakly Supervised Page-Level Handwritten Chinese Text Recognition von Peng, Dezhi, Jin, Lianwen, Liu, Yuliang, Luo, Canjie, Lai, Songxuan

“… Handwritten Chinese text recognition (HCTR) has been an active research topic for decades …”
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From aging to early-stage Alzheimer's: Uncovering handwriting multimodal behaviors by semi-supervised learning and sequential representation learning von El-Yacoubi, Mounîm A., Garcia-Salicetti, Sonia, Kahindo, Christian, Rigaud, Anne-Sophie, Cristancho-Lacroix, Victoria

“… •We propose a paradigm unveiling handwriting changes due to aging and Alzheimer‘s.•Our new semi-supervised learning and sequential representation learning are key …”
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