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Khoshgoftaar, &quot;A survey on Image Data Augmentation for Deep Learning,&quot; Journal of Big Data, vol. 6, no. 1, Jul. 2019, DOI: http://doi.org/10.1186/s40537-019-0197-0</unstructured_citation></citation><citation key="ref7"><doi>10.1142/S0218126623503218</doi><unstructured_citation>U. Poudel, A. M. Regmi, Z. Stamenkovic, and S. P. Raja, &quot;Applicability of OCR engines for text recognition in vehicle number plates, receipts and handwriting,&quot; Journal of Circuits Systems and Computers, Nov. 2023, DOI: http://doi.org/10.1142/s0218126623503218</unstructured_citation></citation><citation key="ref8"><doi>10.4236/jilsa.2024.163011</doi><unstructured_citation>M. A. M. Ali, T. Aly, A. T. Raslan, M. Gheith, and E. A. Amin, &quot;Advancing Crowd Object Detection: A review of YOLO, CNN and VITs hybrid approach,&quot; Journal of Intelligent Learning Systems and Applications, vol. 16, no. 03, pp. 175-221, Jan. 2024,</unstructured_citation></citation><citation key="ref9"><doi>10.4236/jilsa.2024.163011</doi><unstructured_citation>DOI: http://doi.org/10.4236/jilsa.2024.163011</unstructured_citation></citation><citation key="ref10"><unstructured_citation>Gonzalez, R. C., Woods, R. E. (2008). Digital image processing. Italy: Prentice Hall. https://www.google.co.in/books/edition/Digital_Image_Processing/8uGOnjRGEzoC?hl=en</unstructured_citation></citation><citation key="ref11"><unstructured_citation>Kaehler, A., Bradski, G. (2016). Learning OpenCV 3: Computer Vision in C++ with the OpenCV Library. Japan: O'Reilly Media. https://www.google.co.in/books/edition/Learning_OpenCV_3/LPm3DQAAQBAJ?hl=en</unstructured_citation></citation><citation key="ref12"><unstructured_citation>A. G. Howard et al.., &quot;MobileNets: efficient convolutional neural networks for mobile vision applications,&quot; arXiv (Cornell University), Jan. 2017, DOI: http://doi.org/10.48550/arxiv.1704.04861</unstructured_citation></citation><citation key="ref13"><doi>10.1109/TPAMI.2016.2646371</doi><unstructured_citation>B. Shi, X. Bai and C. Yao, &quot;An End-to-End Trainable Neural Network for Image-Based Sequence Recognition and Its Application to Scene Text Recognition,&quot; in IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 39, no. 11, pp. 2298-2304, 1 Nov. 2017,</unstructured_citation></citation><citation key="ref14"><doi>10.1109/TPAMI.2016.2646371</doi><unstructured_citation>DOI: http://doi.org/10.1109/TPAMI.2016.2646371</unstructured_citation></citation><citation key="ref15"><journal_title>In International Journal of Engineering and Advanced Technology (Vol</journal_title><author>Vishal</author><cYear>2019</cYear><doi>10.35940/ijeat.A1842.109119</doi><article_title>Object Detection: Automatic License Plate Detection using Deep Learning and OpenCV</article_title><unstructured_citation>Vishal, R. M., Maram, D., Chaitanya, P. K., &amp; Angeline, R. (2019). Object Detection: Automatic License Plate Detection using Deep Learning and OpenCV. In International Journal of Engineering and Advanced Technology (Vol. 9, Issue 1, pp. 6022-6028).</unstructured_citation></citation><citation key="ref16"><doi>10.35940/ijeat.A1842.109119</doi><unstructured_citation>DOI: https://doi.org/10.35940/ijeat.a1842.109119</unstructured_citation></citation><citation key="ref17"><doi>10.35940/ijitee.F3079.049620</doi><unstructured_citation>Doan, H.-G. (2020). Real-time License Plate Recognition in Overweight Vehicle Balance System. In International Journal of Innovative Technology and Exploring Engineering (Vol. 9, Issue 6, pp. 615-619). DOI: https://doi.org/10.35940/ijitee.f3079.049620</unstructured_citation></citation><citation key="ref18"><journal_title>In International Journal of Recent Technology and Engineering (IJRTE) (Vol</journal_title><author>Ramasamy</author><cYear>2020</cYear><doi>10.35940/ijrte.F9857.038620</doi><article_title>Deep Learning Based Ethiopian Car's License Plate Detection and Recognition</article_title><unstructured_citation>Ramasamy, Dr. A., &amp; Wondwosen, Mr. J. (2020). Deep Learning Based Ethiopian Car's License Plate Detection and Recognition. In International Journal of Recent Technology and Engineering (IJRTE) (Vol. 8, Issue 6, pp. 5730-5737).</unstructured_citation></citation><citation key="ref19"><doi>10.35940/ijrte.F9857.038620</doi><unstructured_citation>DOI: https://doi.org/10.35940/ijrte.f9857.038620</unstructured_citation></citation><citation key="ref20"><journal_title>In International Journal of Inventive Engineering and Sciences (Vol</journal_title><author>Sharma</author><cYear>2023</cYear><doi>10.35940/ijies.f4263.0810823</doi><article_title>Advancements in OCR: A Deep Learning Algorithm for Enhanced Text Recognition</article_title><unstructured_citation>Sharma, P. (2023). Advancements in OCR: A Deep Learning Algorithm for Enhanced Text Recognition. In International Journal of Inventive Engineering and Sciences (Vol. 10, Issue 8, pp. 1-7).</unstructured_citation></citation><citation key="ref21"><doi>10.35940/ijies.F4263.0810823</doi><unstructured_citation>DOI: https://doi.org/10.35940/ijies.f4263.0810823</unstructured_citation></citation><citation key="ref22"><journal_title>In International Journal of Emerging Science and Engineering (Vol</journal_title><author>Jain</author><cYear>2020</cYear><doi>10.35940/ijese.K2482.1061120</doi><article_title>Game-Based Pedagogy System for Assessment using Features Like OCR and Speech-To-Text Recognition</article_title><unstructured_citation>Jain, A., Shah, P., Punamiya, A., &amp; Sayyad, S. (2020). Game-Based Pedagogy System for Assessment using Features Like OCR and Speech-To-Text Recognition. In International Journal of Emerging Science and Engineering (Vol. 6, Issue 11, pp. 1-8).</unstructured_citation></citation><citation key="ref23"><doi>10.35940/ijese.K2482.1061120</doi><unstructured_citation>DOI: https://doi.org/10.35940/ijese.k2482.1061120</unstructured_citation></citation></citation_list>
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