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Nazmus Saqib, Khandaker Foysal Haque, Venkata Prasanth Yanambaka and Ahmed Abdelgawad
Neural networks have made big strides in image classification. Convolutional neural networks (CNN) work successfully to run neural networks on direct images. Handwritten character recognition (HCR) is now a very powerful tool to detect traffic signals, t...
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Saida Mussakhojayeva, Kaisar Dauletbek, Rustem Yeshpanov and Huseyin Atakan Varol
The primary aim of this study was to contribute to the development of multilingual automatic speech recognition for lower-resourced Turkic languages. Ten languages?Azerbaijani, Bashkir, Chuvash, Kazakh, Kyrgyz, Sakha, Tatar, Turkish, Uyghur, and Uzbek?we...
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Waleed Albattah and Saleh Albahli
Handwritten character recognition is a computer-vision-system problem that is still critical and challenging in many computer-vision tasks. With the increased interest in handwriting recognition as well as the developments in machine-learning and deep-le...
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Hasan S.M Al-Khaffat, Nadia A. Musa
Pág. 1 - 11
Introduction: In this paper, a system for recognizing fonts has been designed and implemented. The system is based on the Eigenfaces method. Because font recognition works in conjunction with other methods like Optical Character Recognition (OCR), we use...
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Qiang He, Guowei Chen, Wenchao Song and Pengzhou Zhang
Named entity recognition (NER) is a subfield of natural language processing (NLP) that identifies and classifies entities from plain text, such as people, organizations, locations, and other types. NER is a fundamental task in information extraction, inf...
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