Artykuły w czasopismach na temat „Handwritten characters”
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Jehangir, Sardar, Sohail Khan, Sulaiman Khan, Shah Nazir i Anwar Hussain. "Zernike Moments Based Handwritten Pashto Character Recognition Using Linear Discriminant Analysis". January 2021 40, nr 1 (1.01.2021): 152–59. http://dx.doi.org/10.22581/muet1982.2101.14.
Pełny tekst źródłaZhu, Cheng Hui, Wen Jun Xu, Jian Ping Wang i Xiao Bing Xu. "Research on a Characteristic Extraction Algorithm Based on Analog Space-Time Process for Off-Line Handwritten Chinese Characters". Advanced Materials Research 433-440 (styczeń 2012): 3649–55. http://dx.doi.org/10.4028/www.scientific.net/amr.433-440.3649.
Pełny tekst źródłaKhan, Sulaiman, Habib Ullah Khan i Shah Nazir. "Offline Pashto Characters Dataset for OCR Systems". Security and Communication Networks 2021 (27.07.2021): 1–7. http://dx.doi.org/10.1155/2021/3543816.
Pełny tekst źródłaMALIK, LATESH, i P. S. DESHPANDE. "RECOGNITION OF HANDWRITTEN DEVANAGARI SCRIPT". International Journal of Pattern Recognition and Artificial Intelligence 24, nr 05 (sierpień 2010): 809–22. http://dx.doi.org/10.1142/s0218001410008123.
Pełny tekst źródłaAmulya, K., Lakshmi Reddy, M. Chandara Kumar i Rachana D. "A Survey on Digitization of Handwritten Notes in Kannada". International Journal of Innovative Technology and Exploring Engineering 12, nr 1 (30.12.2022): 6–11. http://dx.doi.org/10.35940/ijitee.a9350.1212122.
Pełny tekst źródłaKhan, Majid A., Nazeeruddin Mohammad, Ghassen Ben Brahim, Abul Bashar i Ghazanfar Latif. "Writer verification of partially damaged handwritten Arabic documents based on individual character shapes". PeerJ Computer Science 8 (20.04.2022): e955. http://dx.doi.org/10.7717/peerj-cs.955.
Pełny tekst źródłaWijaya, Aditya Surya, Nurul Chamidah i Mayanda Mega Santoni. "Pengenalan Karakter Tulisan Tangan Dengan K-Support Vector Nearest Neighbor". IJEIS (Indonesian Journal of Electronics and Instrumentation Systems) 9, nr 1 (30.04.2019): 33. http://dx.doi.org/10.22146/ijeis.38729.
Pełny tekst źródłaRevathi, Buddaraju, M. V. D. Prasad i Naveen Kishore Gattim. "Computationally efficient handwritten Telugu text recognition". Indonesian Journal of Electrical Engineering and Computer Science 34, nr 3 (1.06.2024): 1618. http://dx.doi.org/10.11591/ijeecs.v34.i3.pp1618-1626.
Pełny tekst źródłaZhang, Yan, i Liumei Zhang. "SGooTY: A Scheme Combining the GoogLeNet-Tiny and YOLOv5-CBAM Models for Nüshu Recognition". Electronics 12, nr 13 (26.06.2023): 2819. http://dx.doi.org/10.3390/electronics12132819.
Pełny tekst źródłaBhat, Mohammad Idrees, i B. Sharada. "Spectral Graph-based Features for Recognition of Handwritten Characters: A Case Study on Handwritten Devanagari Numerals". Journal of Intelligent Systems 29, nr 1 (21.07.2018): 799–813. http://dx.doi.org/10.1515/jisys-2017-0448.
Pełny tekst źródłaZhao, Yuliang, Xinyue Zhang, Boya Fu, Zhikun Zhan, Hui Sun, Lianjiang Li i Guanglie Zhang. "Evaluation and Recognition of Handwritten Chinese Characters Based on Similarities". Applied Sciences 12, nr 17 (25.08.2022): 8521. http://dx.doi.org/10.3390/app12178521.
Pełny tekst źródłaWadaskar, Ghanshyam, Vipin Bopanwar, Prayojita Urade, Shravani Upganlawar i Prof Rakhi Shende. "Handwritten Character Recognition". International Journal for Research in Applied Science and Engineering Technology 11, nr 12 (31.12.2023): 508–11. http://dx.doi.org/10.22214/ijraset.2023.57366.
Pełny tekst źródłaSomashekar, Thatikonda. "A Survey on Handwritten Character Recognition using Machine Learning Technique". Journal of University of Shanghai for Science and Technology 23, nr 06 (18.06.2021): 1019–24. http://dx.doi.org/10.51201/jusst/21/05304.
Pełny tekst źródłaKanmani, Dr S., B. Sujitha, K. Subalakshmi, S. Umamaheswari i Karimreddy Punya Sai Teja Reddy. "Off-Line and Online Handwritten Character Recognition Using RNN-GRU Algorithm". International Journal for Research in Applied Science and Engineering Technology 11, nr 4 (30.04.2023): 2518–26. http://dx.doi.org/10.22214/ijraset.2023.50184.
Pełny tekst źródłaTeja, K. Sai. "Hindi-Handwritten-Character- Recognition using Deep Learning". International Journal for Research in Applied Science and Engineering Technology 11, nr 7 (31.07.2023): 369–73. http://dx.doi.org/10.22214/ijraset.2023.54606.
Pełny tekst źródłaMahto, Manoj Kumar, Karamjit Bhatia i Rajendra Kumar Sharma. "Deep Learning Based Models for Offline Gurmukhi Handwritten Character and Numeral Recognition". ELCVIA Electronic Letters on Computer Vision and Image Analysis 20, nr 2 (18.01.2022): 69–82. http://dx.doi.org/10.5565/rev/elcvia.1282.
Pełny tekst źródłaAlwaqfi, Yazan, Mumtazimah Mohamad i Ahmad Al-Taani. "Generative Adversarial Network for an Improved Arabic Handwritten Characters Recognition". International Journal of Advances in Soft Computing and its Applications 14, nr 1 (28.03.2022): 177–95. http://dx.doi.org/10.15849/ijasca.220328.12.
Pełny tekst źródłaYadav, Bharati, Ajay Indian i Gaurav Meena. "HDevChaRNet: A deep learning-based model for recognizing offline handwritten devanagari characters". Journal of Autonomous Intelligence 6, nr 2 (15.08.2023): 679. http://dx.doi.org/10.32629/jai.v6i2.679.
Pełny tekst źródłaLin, Cheng-Jian, Yu-Cheng Liu i Chin-Ling Lee. "Automatic Receipt Recognition System Based on Artificial Intelligence Technology". Applied Sciences 12, nr 2 (14.01.2022): 853. http://dx.doi.org/10.3390/app12020853.
Pełny tekst źródłaHuang, Juanjuan, Ihtisham Ul Haq, Chaolan Dai, Sulaiman Khan, Shah Nazir i Muhammad Imtiaz. "Isolated Handwritten Pashto Character Recognition Using a K-NN Classification Tool based on Zoning and HOG Feature Extraction Techniques". Complexity 2021 (24.03.2021): 1–8. http://dx.doi.org/10.1155/2021/5558373.
Pełny tekst źródłaSuthar, Sanket B., i Amit R. Thakkar. "CNN-Based Optical Character Recognition for Isolated Printed Gujarati Characters and Handwritten Numerals". International Journal of Mathematical, Engineering and Management Sciences 7, nr 5 (1.10.2022): 643–55. http://dx.doi.org/10.33889/ijmems.2022.7.5.042.
Pełny tekst źródłaNaidu, D. J. Samatha, i T. Mahammad Rafi. "HANDWRITTEN CHARACTER RECOGNITION USING CONVOLUTIONAL NEURAL NETWORKS". International Journal of Computer Science and Mobile Computing 10, nr 8 (30.08.2021): 41–45. http://dx.doi.org/10.47760/ijcsmc.2021.v10i08.007.
Pełny tekst źródłaDevi, N. "Offline Handwritten Character Recognition using Convolutional Neural Network". International Journal for Research in Applied Science and Engineering Technology 9, nr 8 (31.08.2021): 1483–89. http://dx.doi.org/10.22214/ijraset.2021.37610.
Pełny tekst źródłaSharma, Kartik, S. V. Jagadeesh Kona, Anshul Jangwal, Aarthy M, Prayline Rajabai C i Deepika Rani Sona. "Handwritten Digits and Optical Characters Recognition". International Journal on Recent and Innovation Trends in Computing and Communication 11, nr 4 (4.05.2023): 20–24. http://dx.doi.org/10.17762/ijritcc.v11i4.6376.
Pełny tekst źródłaLee, Hahn-Ming, Chin-Chou Lin i Jyh-Ming Chen. "A Preclassification Method for Handwritten Chinese Character Recognition Via Fuzzy Rules and Seart Neural Net". International Journal of Pattern Recognition and Artificial Intelligence 12, nr 06 (wrzesień 1998): 743–61. http://dx.doi.org/10.1142/s0218001498000427.
Pełny tekst źródłaAhsan, Shahrukh, Shah Tarik Nawaz, Talha Bin Sarwar, M. Saef Ullah Miah i Abhijit Bhowmik. "A machine learning approach for Bengali handwritten vowel character recognition". IAES International Journal of Artificial Intelligence (IJ-AI) 11, nr 3 (1.09.2022): 1143. http://dx.doi.org/10.11591/ijai.v11.i3.pp1143-1152.
Pełny tekst źródłaAsraful, Md, Md Anwar Hossain i Ebrahim Hossen. "Handwritten Bengali Alphabets, Compound Characters and Numerals Recognition Using CNN-based Approach". Annals of Emerging Technologies in Computing 7, nr 3 (1.07.2023): 60–77. http://dx.doi.org/10.33166/aetic.2023.03.003.
Pełny tekst źródłaNing, Zihao. "Research on Handwritten Chinese Character Recognition Based on BP Neural Network". Modern Electronic Technology 6, nr 1 (23.06.2022): 12. http://dx.doi.org/10.26549/met.v6i1.11359.
Pełny tekst źródłaKhatri, Suman, i Irphan Ali. "Hindi Numeral Recognition using Neural Network". International Journal of Advance Research and Innovation 1, nr 3 (2013): 29–39. http://dx.doi.org/10.51976/ijari.131304.
Pełny tekst źródłaJbrail, Mohammed Widad, i Mehmet Emin Tenekeci. "Character Recognition of Arabic Handwritten Characters Using Deep Learning". Journal of Studies in Science and Engineering 2, nr 1 (19.03.2022): 32–40. http://dx.doi.org/10.53898/josse2022213.
Pełny tekst źródłaAmin, Muhammad Sadiq, Siddiqui Muhammad Yasir i Hyunsik Ahn. "Recognition of Pashto Handwritten Characters Based on Deep Learning". Sensors 20, nr 20 (17.10.2020): 5884. http://dx.doi.org/10.3390/s20205884.
Pełny tekst źródłaSiddiqui, Sayma Shafeeque A. W., Rajashri G. Kanke, Ramnath M. Gaikwad i Manasi R. Baheti. "Review on Isolated Urdu Character Recognition: Offline Handwritten Approach". International Journal for Research in Applied Science and Engineering Technology 11, nr 8 (31.08.2023): 384–88. http://dx.doi.org/10.22214/ijraset.2023.55164.
Pełny tekst źródłaN S, Aswin. "Malayalam Handwritten Words Recognition: A Review". INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 08, nr 04 (6.04.2024): 1–5. http://dx.doi.org/10.55041/ijsrem30057.
Pełny tekst źródłaPremachandra, H. Waruna H., Maika Yamada, Chinthaka Premachandra i Hiroharu Kawanaka. "Low-Computational-Cost Algorithm for Inclination Correction of Independent Handwritten Digits on Microcontrollers". Electronics 11, nr 7 (29.03.2022): 1073. http://dx.doi.org/10.3390/electronics11071073.
Pełny tekst źródłaDevaraj, Anjali Yogesh, Anup S. Jain, Omisha N i Shobana TS. "Kannada Text Recognition". International Journal for Research in Applied Science and Engineering Technology 10, nr 9 (30.09.2022): 73–78. http://dx.doi.org/10.22214/ijraset.2022.46520.
Pełny tekst źródłaLi, Ling Hua, Shou Fang Mi i Heng Bo Zhang. "Template-Based Handwritten Numeric Character Recognition". Advanced Materials Research 586 (listopad 2012): 384–88. http://dx.doi.org/10.4028/www.scientific.net/amr.586.384.
Pełny tekst źródłaLi, Kangying, Biligsaikhan Batjargal i Akira Maeda. "A Prototypical Network-Based Approach for Low-Resource Font Typeface Feature Extraction and Utilization". Data 6, nr 12 (16.12.2021): 134. http://dx.doi.org/10.3390/data6120134.
Pełny tekst źródłaHe, Rong. "Skeletonization of broken handwritten characters". Optical Engineering 39, nr 11 (1.11.2000): 2882. http://dx.doi.org/10.1117/1.1315024.
Pełny tekst źródłaSrinivasa Chakravarthy, V., i Bhaskar Kompella. "The shape of handwritten characters". Pattern Recognition Letters 24, nr 12 (sierpień 2003): 1901–13. http://dx.doi.org/10.1016/s0167-8655(03)00017-5.
Pełny tekst źródłaSrivastav, Ankita, i Neha Sahu. "Segmentation of Devanagari Handwritten Characters". International Journal of Computer Applications 142, nr 14 (18.05.2016): 15–18. http://dx.doi.org/10.5120/ijca2016909994.
Pełny tekst źródłaVaidehi K. i Manivannan R. "Automated Math Symbol Classification Using SVM". International Journal of e-Collaboration 18, nr 2 (1.03.2022): 1–14. http://dx.doi.org/10.4018/ijec.304037.
Pełny tekst źródłaAli, Aree, i Bayan Omer. "Invarianceness for Character Recognition Using Geo-Discretization Features". Computer and Information Science 9, nr 2 (17.03.2016): 1. http://dx.doi.org/10.5539/cis.v9n2p1.
Pełny tekst źródłaR, Mr Venkatesh. "Handwritten Telugu Character Recognition & Signature Verification". INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 08, nr 04 (28.04.2024): 1–5. http://dx.doi.org/10.55041/ijsrem31955.
Pełny tekst źródłaHA, JIN-YOUNG, SE-CHANG OH i JIN H. KIM. "RECOGNITION OF UNCONSTRAINED HANDWRITTEN ENGLISH WORDS WITH CHARACTER AND LIGATURE MODELING". International Journal of Pattern Recognition and Artificial Intelligence 09, nr 03 (czerwiec 1995): 535–56. http://dx.doi.org/10.1142/s0218001495000511.
Pełny tekst źródłaFirdous, Arusa, Neha Pawar, Muheet Ahmed Butt i Majid Zaman. "Review of Optical Character Recognition Techniques& Applications". International Journal of Advanced Research in Computer Science and Software Engineering 7, nr 7 (30.07.2017): 206. http://dx.doi.org/10.23956/ijarcsse/v7i7/0158.
Pełny tekst źródłaRehman, Muhammad Zubair, Nazri Mohd. Nawi, Mohammad Arshad i Abdullah Khan. "Recognition of Cursive Pashto Optical Digits and Characters with Trio Deep Learning Neural Network Models". Electronics 10, nr 20 (15.10.2021): 2508. http://dx.doi.org/10.3390/electronics10202508.
Pełny tekst źródłaKumar, J., i A. Roy. "DograNet – a comprehensive offline dogra handwriting character dataset". Journal of Physics: Conference Series 2251, nr 1 (1.04.2022): 012008. http://dx.doi.org/10.1088/1742-6596/2251/1/012008.
Pełny tekst źródłaDas, Mamatarani, Mrutyunjaya Panda i Shreela Dash. "Enhancing the Power of CNN Using Data Augmentation Techniques for Odia Handwritten Character Recognition". Advances in Multimedia 2022 (22.12.2022): 1–13. http://dx.doi.org/10.1155/2022/6180701.
Pełny tekst źródłaUddin, Imran, Dzati A. Ramli, Abdullah Khan, Javed Iqbal Bangash, Nosheen Fayyaz, Asfandyar Khan i Mahwish Kundi. "Benchmark Pashto Handwritten Character Dataset and Pashto Object Character Recognition (OCR) Using Deep Neural Network with Rule Activation Function". Complexity 2021 (4.03.2021): 1–16. http://dx.doi.org/10.1155/2021/6669672.
Pełny tekst źródłaNISHIDA, HIROBUMI, i SHUNJI MORI. "A MODEL-BASED SPLIT-AND-MERGE METHOD FOR CHARACTER STRING RECOGNITION". International Journal of Pattern Recognition and Artificial Intelligence 08, nr 05 (październik 1994): 1205–22. http://dx.doi.org/10.1142/s0218001494000607.
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