Gotowe bibliografie tematyczne / Handwritten text Image generation

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  1. Artykuły w czasopismach
  2. Rozprawy doktorskie
  3. Książki
  4. Części książek
  5. Streszczenia konferencji

Gotowa bibliografia na temat „Handwritten text Image generation”

Autor: Grafiati
Data publikacji: 2 czerwca 2025
Data aktualizacji: 31 lipca 2025

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Artykuły w czasopismach na temat "Handwritten text Image generation"

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Dubey, Parul, Manjushree Nayak, Hitesh Gehani, Ashwini Kukade, Vinay Keswani, and Pushkar Dubey. "Enhancing realism in handwritten text images with generative adversarial networks." Bulletin of Electrical Engineering and Informatics 14, no. 3 (2025): 2370–79. https://doi.org/10.11591/eei.v14i3.9190.

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Image synthesis is particularly important for applications that want to create realistic handwritten documents, which is why handwritten text generation is a critical area within its domain. Even with today's highly advanced technology, generating diverse and accurate representations of human handwriting is still a tough problem because of the variability in style. In this study, we tackle the problem of instability during the training phase of generative adversarial networks (GANs) for generating handwritten text images. Using the MNIST dataset, which includes 60,000 training and 10,000 test
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Surolia, Akshat. "Ooze - Handwritten Text Generator." GLS KALP: Journal of Multidisciplinary Studies 1, no. 4 (2024): 35–49. http://dx.doi.org/10.69974/glskalp.01.04.64.

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In this paper we show how Generative Adversarial Network (Goodfellow et al., 2014), more specifically Cycle-GAN(Zhu et al., 2017), can be used for Human like handwriting generation with output size up to a text line. The methodology used in Cycle-GAN is to establish translation between two different domains (e.g., connection between image of horse and zebra), extending this methodology to establishment of translation between machine printed text and handwritten text is mentioned in this paper. The neural network used in this paper is trained for dataset created by the author and can be trained
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Bogatenkova, Anastasiya Olegovna, Oksana Vladimirovna Belyaeva, and Andrey Igorevich Perminov. "Generation of Images with Handwritten Text in Russian." Proceedings of the Institute for System Programming of the RAS 35, no. 2 (2023): 19–34. http://dx.doi.org/10.15514/ispras-2023-35(2)-2.

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Automatic handwriting recognition is an important component in the process of electronic documents analysis, but its solution is still far from ideal. One of the main reasons for the complexity of Russian handwriting recognition is the insufficient amount of data used to train recognition models. Moreover, for the Russian language the problem is more acute and is exacerbated by a large variety of complex handwriting. This paper explores the impact of various methods of generating additional training datasets on the quality of recognition models: the method based on handwritten fonts, the Stack
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Bogatenkova, A. O., O. V. Belyaeva, and A. I. Perminov. "Generation of Images with Handwritten Text in Russian." Programming and Computer Software 50, no. 7 (2024): 483–92. https://doi.org/10.1134/s036176882470021x.

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Li, Rankang, Shanxiong Chen, Fujia Zhao, and Xiaogang Qiu. "Text Detection Model for Historical Documents Using CNN and MSER." Journal of Database Management 34, no. 1 (2023): 1–23. http://dx.doi.org/10.4018/jdm.322086.

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This article introduces a text detection model for historical documents images. The handwritten characters in historical documents are always difficult to detect because they contain fuzzy or missing ink, or weathering features and stains; these features will seriously affect the detection accuracy. In order to reduce the influence mentioned above, an effective ATD model is proposed to detect the textbox of characters in historical documents image, and ATD model includes a CNN-based text-box generation network and an NMS-based MSER text-box generation model. As a post-processing method, a text
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Li, Minghao, Tengchao Lv, Jingye Chen, et al. "TrOCR: Transformer-Based Optical Character Recognition with Pre-trained Models." Proceedings of the AAAI Conference on Artificial Intelligence 37, no. 11 (2023): 13094–102. http://dx.doi.org/10.1609/aaai.v37i11.26538.

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Text recognition is a long-standing research problem for document digitalization. Existing approaches are usually built based on CNN for image understanding and RNN for char-level text generation. In addition, another language model is usually needed to improve the overall accuracy as a post-processing step. In this paper, we propose an end-to-end text recognition approach with pre-trained image Transformer and text Transformer models, namely TrOCR, which leverages the Transformer architecture for both image understanding and wordpiece-level text generation. The TrOCR model is simple but effec
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Zhao, Fuchang. "Research on Handwriting Text Generation Algorithm Based on Generative Adversarial Network." Academic Journal of Science and Technology 9, no. 3 (2024): 194–97. http://dx.doi.org/10.54097/kt3yem44.

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The main task of this paper is to study the handwriting text generation method based on deep learning. Through understanding the development status of the research, It can be found that the current research on the generation of different handwriting styles still has some obvious defects, such as the need for manual intervention in character segmentation, failure to capture the global handwriting style, style collapse, failure to generate arbitrary length characters, and text. Finally, this paper proposes a handwritten text generation algorithm combining advantages of convolutional network and
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Zhang, Likun, Xiaoyan Li, Yi Tang, Fangbin Song, Tian Xia, and Wei Wang. "Contemporary Advertising Text Art Design and Effect Evaluation by IoT Deep Learning under the Smart City." Security and Communication Networks 2022 (July 22, 2022): 1–14. http://dx.doi.org/10.1155/2022/5161398.

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This work intends to solve the problem that the current artistic typeface generation methods rely too much on manual intervention, lack novelty, and the single font local feature and the global feature extraction method cannot fully describe the font features. Firstly, it proposes a handwritten word recognition model based on generalized search trees (GIST) and the pyramid histogram of oriented gradient (PHOG). The local features and global features of the font are fused. Secondly, a model of automatic artistic typeface generation based on generative adversarial networks (GAN) is constructed,
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Dinges, Laslo, Ayoub Al-Hamadi, Moftah Elzobi, Sherif El-etriby, and Ahmed Ghoneim. "ASM Based Synthesis of Handwritten Arabic Text Pages." Scientific World Journal 2015 (2015): 1–18. http://dx.doi.org/10.1155/2015/323575.

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Document analysis tasks, as text recognition, word spotting, or segmentation, are highly dependent on comprehensive and suitable databases for training and validation. However their generation is expensive in sense of labor and time. As a matter of fact, there is a lack of such databases, which complicates research and development. This is especially true for the case of Arabic handwriting recognition, that involves different preprocessing, segmentation, and recognition methods, which have individual demands on samples and ground truth. To bypass this problem, we present an efficient system th
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Han, Sangkwon, Seungbin Ji, and Jongtae Rhee. "Diffusion-Denoising Process with Gated U-Net for High-Quality Document Binarization." Applied Sciences 13, no. 20 (2023): 11141. http://dx.doi.org/10.3390/app132011141.

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The binarization of degraded documents represents a crucial preprocessing task for various document analyses, including optical character recognition and historical document analysis. Various convolutional neural network models and generative models have been used for document binarization. However, these models often struggle to deliver generalized performance on noise types the model has not encountered during training and may have difficulty extracting intricate text strokes. We herein propose a novel approach to address these challenges by introducing the use of the latent diffusion model,
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Rozprawy doktorskie na temat "Handwritten text Image generation"

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Kang, Lei. "Robust Handwritten Text Recognition in Scarce Labeling Scenarios: Disentanglement, Adaptation and Generation." Doctoral thesis, Universitat Autònoma de Barcelona, 2020. http://hdl.handle.net/10803/672067.

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Els documents escrits a mà no només es conserven en arxius històrics, sinó que també s’utilitzen àmpliament en documents administratius, com ara xecs o formularis. Amb l’auge de de l’anomenat aprenentatge profund (Deep Learning), s’ha aconseguit un bon rendiment en conjunts de dades específics per al reconeixement de text manuscrit. Tot i això, encara és difícil resoldre casos d’ús reals a causa de la variació entre estils d’escriptura de diferents escriptors i el fet de tenir dades etiquetades limitades. Per tant, es requereix explorar arquitectures de reconeixement d’escriptura més sòlides a
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Nederhof, Mark-Jan. "OCR of hand-written transcriptions of hieroglyphic text." Universitätsbibliothek Leipzig, 2016. http://nbn-resolving.de/urn:nbn:de:bsz:15-qucosa-201704.

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Encoding hieroglyphic texts is time-consuming. If a text already exists as hand-written transcription, there is an alternative, namely OCR. Off-the-shelf OCR systems seem difficult to adapt to the peculiarities of Ancient Egyptian. Presented is a proof-of-concept tool that was designed to digitize texts of Urkunden IV in the hand-writing of Kurt Sethe. It automatically recognizes signs and produces a normalized encoding, suitable for storage in a database, or for printing on a screen or on paper, requiring little manual correction. The encoding of hieroglyphic text is RES (Revised Encoding Sch
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Alkhoury, Ihab. "Arabic Text Recognition and Machine Translation." Doctoral thesis, Universitat Politècnica de València, 2015. http://hdl.handle.net/10251/53029.

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[EN] Research on Arabic Handwritten Text Recognition (HTR) and Arabic-English Machine Translation (MT) has been usually approached as two independent areas of study. However, the idea of creating one system that combines both areas together, in order to generate English translation out of images containing Arabic text, is still a very challenging task. This process can be interpreted as the translation of Arabic images. In this thesis, we propose a system that recognizes Arabic handwritten text images, and translates the recognized text into English. This system is built from the combination o
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Noghe, Petr. "Vyhodnocení testových formulářů pomocí OCR." Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2013. http://www.nusl.cz/ntk/nusl-219986.

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This thesis deals with the evaluation forms using optical character recognition. Image processing and methods used for OCR is described in the first part of thesis. In the practical part is created database of sample characters. The chosen method is based on correlation between patterns and recognized characters. The program is designed in a graphical environment MATLAB. Finally, several forms are evaluated and success rate of the proposed program is detected.
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Ryan, Elisabeth. "Towards word alignment and dataset creation for shorthand documents and transcripts." Thesis, Uppsala universitet, Institutionen för informationsteknologi, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-452278.

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Analysing handwritten texts and creating labelled data sets can facilitate novel research on languages and advanced computerized analysis of authors works. However, few handwritten works have word wise labelling or data sets associated with them. More often a transcription of the text is available, but without any exact coupling between words in the transcript and word representations in the document images. Can an algorithm be created that will take only an image of handwritten text and a corresponding transcript and return a partial alignment and data set? An algorithm is developed in this t
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Puigcerver, I. Pérez Joan. "A Probabilistic Formulation of Keyword Spotting." Doctoral thesis, Universitat Politècnica de València, 2019. http://hdl.handle.net/10251/116834.

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[ES] La detección de palabras clave (Keyword Spotting, en inglés), aplicada a documentos de texto manuscrito, tiene como objetivo recuperar los documentos, o partes de ellos, que sean relevantes para una cierta consulta (query, en inglés), indicada por el usuario, entre una gran colección de documentos. La temática ha recogido un gran interés en los últimos 20 años entre investigadores en Reconocimiento de Formas (Pattern Recognition), así como bibliotecas y archivos digitales. Esta tesis, en primer lugar, define el objetivo de la detección de palabras clave a partir de una perspectiva basada
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Godard, Caroline. "'Une sorte de vaste sensation collective': Story and Experience in the work of Marcel Proust, Walter Benjamin, and Annie Ernaux." Miami University / OhioLINK, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=miami1563891435485933.

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Barrère, Killian. "Architectures de Transformer légères pour la reconnaissance de textes manuscrits anciens." Electronic Thesis or Diss., Rennes, INSA, 2023. http://www.theses.fr/2023ISAR0017.

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En reconnaissance d’écriture manuscrite, les architectures Transformer permettent de faibles taux d’erreur, mais sont difficiles à entraîner avec le peu de données annotées disponibles. Dans ce manuscrit, nous proposons des architectures Transformer légères adaptées aux données limitées. Nous introduisons une architecture rapide basée sur un encodeur Transformer, et traitant jusqu’à 60 pages par seconde. Nous proposons aussi des architectures utilisant un décodeur Transformer pour inclure l’apprentissage de la langue dans la reconnaissance des caractères. Pour entraîner efficacement nos archit
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Książki na temat "Handwritten text Image generation"

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Group, Delphi Consulting, ed. Information management: The next generation : conferences and seminars on electronic document management systems. 7th ed. Delphi Consulting Group, 1989.

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Klyuchevskaya, Irina, Ol'ga Semikova, and Igor' Zheleznov. Advertising and PR activities of a hotel company. INFRA-M Academic Publishing LLC., 2023. http://dx.doi.org/10.12737/1852505.

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The textbook examines the content and specifics of the advertising and PR activities of a hotel enterprise related to the peculiarities of the development of the market of hotel services and hotel products, analyzes advertising and PR tools and strategies aimed at ensuring the successful positioning of a hotel enterprise in the market. The issues of the organization of advertising and PR activities of hotels are highlighted, the issues of the use of channels for the distribution of advertising appeals and PR materials, the use of Internet technologies in advertising, the principles of creating
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Information management: The next generation : conferences and seminars on text retrieval and image processing. 5th ed. Delphi Consulting Group, 1989.

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Lombardi, Elena. Women as Text, Text as Woman. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198818960.003.0004.

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This chapter explores an ancient cultural theme: the links between women and textuality, involving images of female nudity (‘the naked truth’) and of clothing and make up (ornatus). It begins by exploring the mechanics of reading as a homoerotic exchange between a male author and a male reader through the guise of a personified female text, and it documents the evolution of such a theme in the age of Dante, with the flourishing of a rather independent form of female lyric textuality. In creating an embodied text that moves about, speaks, cries out in joy or sorrow, but also writes and reads it
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Shamma, Yasmine. Joe Brainard’s Collaged Spaces. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198808725.003.0003.

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Brainard was not only an illustrator and friend to many New York School poets, he was also an avid letter writer, collage artist, miniature artist, cartoonist, and serious poet. How is contemporary poetry involved in an overlooked dialogue with collage art? This chapter suggests a general tendency towards assembly across the disciplines of text and image which govern both first- and second-generation New York School aesthetics. This chapter showcases how Brainard’s work instigates and propels the collaged poetry of The New York Schools from the real and influential side-lines of their poems? T
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Hale, Meredith McNeill. The Birth of Modern Political Satire. Oxford University Press, 2020. http://dx.doi.org/10.1093/oso/9780198836261.001.0001.

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This book documents one of the most important moments in the history of printed political imagery, when the political print became what we would recognize as modern political satire. Contrary to conventional historical and art-historical narratives, which place the emergence of political satire in the news-driven coffee-house culture of eighteenth-century London, this study locates the birth of the genre in the late seventeenth-century Netherlands in the contentious political milieu surrounding William III’s invasion of England known as the ‘Glorious Revolution’. The satires produced between 1
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Ufimtseva, Nataliya V., Iosif A. Sternin, and Elena Yu Myagkova. Russian psycholinguistics: results and prospects (1966–2021): a research monograph. Institute of Linguistics, Russian Academy of Sciences, 2021. http://dx.doi.org/10.30982/978-5-6045633-7-3.

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The monograph reflects the problems of Russian psycholinguistics from the moment of its inception in Russia to the present day and presents its main directions that are currently developing. In addition, theoretical developments and practical results obtained in the framework of different directions and research centers are described in a concise form. The task of the book is to reflect, as far as it is possible in one edition, firstly, the history of the formation of Russian psycholinguistics; secondly, its methodology and developed methods; thirdly, the results obtained in different research
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Części książek na temat "Handwritten text Image generation"

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Gurav, Aniket, Narayanan C. Krishnan, and Sukalpa Chanda. "Word-Diffusion: Diffusion-Based Handwritten Text Word Image Generation." In Lecture Notes in Computer Science. Springer Nature Switzerland, 2024. https://doi.org/10.1007/978-3-031-78495-8_4.

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Chang, Chun Chieh, Leibny Paola Garcia Perera, and Sanjeev Khudanpur. "Crosslingual Handwritten Text Generation Using GANs." In Document Analysis and Recognition – ICDAR 2023 Workshops. Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-41501-2_20.

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Solanki, Shivam R., and Drupad K. Khublani. "Text-to-Image Generation." In Generative Artificial Intelligence. Apress, 2024. http://dx.doi.org/10.1007/979-8-8688-0403-8_2.

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Lin, Zhiqiu, Deepak Pathak, Baiqi Li, et al. "Evaluating Text-to-Visual Generation with Image-to-Text Generation." In Lecture Notes in Computer Science. Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-72673-6_20.

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Frinken, Volkmar, and Horst Bunke. "Self-training for Handwritten Text Line Recognition." In Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications. Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-16687-7_18.

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Yan, Kun, Lei Ji, Chenfei Wu, et al. "Trace Controlled Text to Image Generation." In Lecture Notes in Computer Science. Springer Nature Switzerland, 2022. http://dx.doi.org/10.1007/978-3-031-20059-5_4.

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Jindal, Rajni, V. Sriram, Vishesh Aggarwal, and Vishesh Jain. "Text to Image Generation Using Gan." In Pervasive Computing and Social Networking. Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-19-2840-6_51.

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Vidya, V., T. R. Indhu, and V. K. Bhadran. "Classification of Handwritten Document Image into Text and Non-Text Regions." In Lecture Notes in Electrical Engineering. Springer India, 2013. http://dx.doi.org/10.1007/978-81-322-1000-9_10.

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Nikolaidou, Konstantina, George Retsinas, Giorgos Sfikas, and Marcus Liwicki. "DiffusionPen: Towards Controlling the Style of Handwritten Text Generation." In Lecture Notes in Computer Science. Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-73013-9_24.

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Riaz, Nauman, Saifullah Saifullah, Stefan Agne, Andreas Dengel, and Sheraz Ahmed. "StylusAI: Stylistic Adaptation for Robust German Handwritten Text Generation." In Lecture Notes in Computer Science. Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-70536-6_26.

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Streszczenia konferencji na temat "Handwritten text Image generation"

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Gurav, Aniket, Sukalpa Chanda, and Narayanan C. Krishnan. "HTLDIFF: Handwritten Text Line Generation - A Diffusion Model Perspective." In 2024 IEEE Thirteenth International Conference on Image Processing Theory, Tools and Applications (IPTA). IEEE, 2024. http://dx.doi.org/10.1109/ipta62886.2024.10755723.

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Wang, Yiming, Hongxi Wei, and Heng Wang. "AS-Net: Adaptive Style-aware Network for Handwritten Text Generation." In ICASSP 2025 - 2025 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, 2025. https://doi.org/10.1109/icassp49660.2025.10889851.

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Chandila, Rishabh, and Deepak Kumar. "Conversion of Text-to-Image Generation." In 2024 International Conference on Electrical Electronics and Computing Technologies (ICEECT). IEEE, 2024. http://dx.doi.org/10.1109/iceect61758.2024.10739305.

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Haydarov, Kilichbek, Aashiq Muhamed, Xiaoqian Shen, et al. "Adversarial Text to Continuous Image Generation." In 2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). IEEE, 2024. http://dx.doi.org/10.1109/cvpr52733.2024.00604.

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Srinivasan, M., K. Radha, V. Priya, Shaik Mahaboob Basha, and S. Ravi. "Auto-Detection of Handwritten Text Documents using Improved Image Processing Technique." In 2024 15th International Conference on Computing Communication and Networking Technologies (ICCCNT). IEEE, 2024. http://dx.doi.org/10.1109/icccnt61001.2024.10724959.

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Liu, Qingting, Shuying Zhao, and Junjie Cai. "Research on dpo handwritten text generation algorithm based on fine-grained improvement." In 2025 4th International Symposium on Computer Applications and Information Technology (ISCAIT). IEEE, 2025. https://doi.org/10.1109/iscait64916.2025.11010770.

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Xu, Ning, and Serhad Doken. "Automatic Visual Citation Generation for Text-to-Image Generation." In 2024 IEEE 7th International Conference on Multimedia Information Processing and Retrieval (MIPR). IEEE, 2024. http://dx.doi.org/10.1109/mipr62202.2024.00015.

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Zhou, Yufan, Ruiyi Zhang, Jiuxiang Gu, and Tong Sun. "Customization Assistant for Text-to-image Generation." In 2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). IEEE, 2024. http://dx.doi.org/10.1109/cvpr52733.2024.00877.

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Lakhanpal, Sanyam, Shivang Chopra, Vinija Jain, Aman Chadha, and Man Luo. "Refining Text-to-Image Generation: Towards Accurate Training-Free Glyph-Enhanced Image Generation." In 2025 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV). IEEE, 2025. https://doi.org/10.1109/wacv61041.2025.00429.

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Höllein, Lukas, Aljaž Božič, Norman Müller, et al. "ViewDiff: 3D-Consistent Image Generation with Text-to-Image Models." In 2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). IEEE, 2024. http://dx.doi.org/10.1109/cvpr52733.2024.00482.

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