Optimizing Text Recognition in Mechanical Drawings: A Comprehensive Approach by Javier Villena Toro, Mehdi Tarkian

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Recognition of Handwritten Characters in Birch-Bark Manuscripts via Object Detection by Ivan P. Malashin, Vadim S. Tynchenko, Andrei P. Gantimurov, Vladimir A. Nelyub, Aleksei S. Borodulin

“…This study adapts the YOLO-based object detection framework for detection and recognition of handwritten characters in digital photographs of Novgorod birch-bark fragments. …”
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Advancements and Challenges in Character Recognition: A Comparative Analysis of CNN and Deep Learning Approaches by Yang Ximin

“…The collective findings suggest that while CNN and deep learning models have significantly advanced character recognition, there remains a need for enhanced segmentation techniques and a balanced approach to optimizing training efficiency and accuracy. …”
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Enhanced OCR Recognition for Madurese Text Documents: A Genetic Algorithm Approach with Tesseract 5.5 by Muhammad Nazir Arifin, Muhammad Umar Mansyur, Ali Rahman, Nindian Puspa Dewi, Fauzan Prasetyo Eka Putra

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Ensemble genetic and CNN model-based image classification by enhancing hyperparameter tuning by Wajahat Hussain, Muhammad Faheem Mushtaq, Mobeen Shahroz, Urooj Akram, Ehab Seif Ghith, Mehdi Tlija, Tai-hoon Kim, Imran Ashraf

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Acceleration of Urdu Optical Character Recognition on Zynq UltraScale+ MPSoC Using Deep Convolutional Neural Network by Fauzia Yasir, Majida Kazmi

“…Deploying deep learning–based optical character recognition (OCR) systems for low-resource, complex-script languages like Urdu remains a major challenge due to high computational costs, lack of annotated datasets, and limited hardware support for real-time applications. …”
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FLIP: A Novel Feedback Learning-Based Intelligent Plugin Towards Accuracy Enhancement of Chinese OCR by Xinyue Tao, Yueyue Han, Yakai Jin, Yunzhi Wu

“…Chinese Optical Character Recognition (OCR) technology is essential for digital transformation in Chinese regions, enabling automated document processing across various applications. …”
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Single-Character-Based Embedding Feature Aggregation Using Cross-Attention for Scene Text Super-Resolution by Meng Wang, Qianqian Li, Haipeng Liu

“…In TextZoom benchmarking, the text recognition accuracies of different recognizers are 53.6%, 60.9%, and 64.5%, which are improved by 0.9–1.4% over the baseline TATT, achieving an optimal SSIM value of 0.7951 and a PSNR of 21.84. …”
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Design of Enhanced License Plate Information Recognition Algorithm Based on Environment Perception by Zilu Wang, Limin Zheng, Gang Li

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Auto-Probabilistic Mining Method for Siamese Neural Network Training by Arseniy Mokin, Alexander Sheshkus, Vladimir L. Arlazarov

“…To evaluate the proposed methods, experiments were conducted with the optical character recognition task using the PHD08 and Omniglot datasets. …”
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End-to-end feature fusion for jointly optimized speech enhancement and automatic speech recognition by Mohamed Medani, Nasir Saleem, Fethi Fkih, Manal Abdullah Alohali, Hela Elmannai, Sami Bourouis

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Extrapolating training of neural networks by Ya. A. Bury, D. I. Samal

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Automated and efficient Bangla signboard detection, text extraction, and novel categorization method for underrepresented languages in smart cities by Tanmoy Mazumder, Fariha Nusrat, Abu Bakar Siddique Mahi, Jolekha Begum Brishty, Rashik Rahman, Tanjina Helaly

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Machine learning-based voice assistant: optimizing the efficiency of speech conversion for people with speech disorders by M.H. Antor, N.V. Chudinovskikh, M.V. Bachurin, A.A. Shurpikov, N.A. Khlebnikov, B.A. Bredikhin

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Automatic Ladle Tracking with Object Detection and OCR in Steel Melting Shops by Kabil Murugan, Mahinas Senthilmurugan, Venbha V. Senthilkumar, Harshita Velusamy, Karthiga Sekar, Vasanthan Buvanesan, Manikandan Venugopal

“…This paper proposes two innovative solutions to address these problems: a computer-vision-based ladle tracking system and an integrated approach of preprocessing techniques with optical character recognition (OCR) algorithms. The first method utilizes a YOLOv8 framework for detecting the two classes from the input images, such as the ladles and their unique numbers. …”
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Revealing the Next Word and Character in Arabic: An Effective Blend of Long Short-Term Memory Networks and ARABERT by Fawaz S. Al-Anzi, S. T. Bibin Shalini

“…Baidu’s Deep Speech model was implemented to precisely identify the global optimal value rapidly while preserving a low word and character discrepancy rate by attaining an excellent performance in isolated and end-to-end speech recognition. …”
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Label-Guided Data Augmentation for Chinese Named Entity Recognition by Miao Jiang, Honghui Chen

“…The LGDA model consists of three key components: a data augmentation module, a label semantic fusion module, and an optimized loss function. It operates in two stages: (1) the enhancement of data with a masked entity generation model and (2) the integration of label annotations to refine entity recognition. …”
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Water Meter Reading Based on Text Recognition Techniques and Deep Learning by Bay Nguyen van, Anh Nguyen, Kiet Tran-Trung, Thien Ho Huong, Ha Duong Thi Hong, Hau Nguyen Trung, Vinh Truong Hoang

“…We propose a structured two-step approach to Automated Meter Reading, involving the identification of the counter region followed by digit segmentation and recognition. Using Convolutional Neural Networks, particularly YOLOv8 for detecting the counter region, we evaluate six CNN-based techniques for digit segmentation and recognition: PP-OCRv3, Structure-Preserving Inner Offset Network, Transformer-based Optical Character Recognition, RobustScanner, Show-Attend-and-Read, and Convolutional Recurrent Neural Network.…”
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AILDP: a research on ship number recognition technology for complex scenarios by Tianjiao Wei, Zhuhua Hu, Yaochi Zhao, Xiyu Fan

“…The Character_accuracy of the recognition task can reach 95.23%.…”
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INFORMATION TECHNOLOGY FOR RECOGNITION OF ROAD SIGNS USING A NEURAL NETWORK by Elena Yashina, Roman Artiukh, Nikolai Рan, Andrei Zelensky

“…Results: Different approaches to the identification of symbols on images, various software tools for object recognition, image transformation for optimal fragment are considered. …”
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