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Qarshi davlat universiteti international scientific and practical conference on algorithms and current problems of programming
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Bog'liq Asosiy oxirgi 17.05.2023 18.20Results and Discussion:
This research paper discusses a task involving recognition of
sign language and proposes a two-stage transfer learning approach for Sign Language
Recognition (SLR). The Inception V3 pre-existing model was utilized for this task, where
the model was initially trained on the ImageNet dataset, and then on the Kaggle ASL
dataset. Subsequently, we applied the two-stage transfer learning approach and trained the
model with our UzSL dataset. The obtained results are present in Table 1, which illustrates
that the letters Oʻ and Gʻ exhibited lower accuracy values.
Conclusion:
The objective of this research is to achieve accurate recognition of Kazakh
sign language. To attain this objective, a dataset consisting of over 3000 images for 30
gestures was create. However, the limited number of images affected the clarity of our
results. We also considered lighting as a parameter affecting recognition quality, to ensure
that our development yields satisfactory results.
Gesture classification was carry out using three classification algorithms. The random
classifier had an average accuracy of 93.2%. In addition, the performance of the algorithm
was evaluate based on its speed of execution and training time.
References
1. Ahmed, M. A., Zaidan, B. B., Zaidan, A. A., Salih, M. M., Lakulu, M. M. bin. (2018). A
Review on Systems-Based Sensory Gloves for Sign Language Recognition State of the Art
between 2007 and 2017. Sensors, 18 (7), 2208. doi: http://doi.org/10.3390/s18072208
2. R. Bhavani, S. Ananthakumaran. Development of a smart walking stick for visually
impaired people, Turkish Journal of Computer and Mathematics Education, Vol.12 No.2
(2021), DOI:10.17762/TURCOMAT.V12I2.1112
3. P. Mell and T. Grance, “The NIST Definition of Cloud Computing” (Technical report),
National Institute of Standards and Technology: U.S. Department of Commerce, pp. 1-7,
September 2011. doi:10.6028/NIST.SP.800-145. Special publication 800-145.
4. Kudubayeva, S.; Amangeldy, N.; Sundetbayeva, A.; Sarinova, A. The Use Of Correlation
Analysis In The Algorithm Of Dynamic Gestures Recognition In Video Sequence. In
Proceedings Of The 5th International Conference On Engineering And Mis, Pahang,
Malaysia, 6–8 June 2019. Https://Doi.Org/10.1145/3330431.3330439.
5. Pozilova, S.K., Mnpcanneaa, M.T., Kayumov, O.A., Development of Professional
Creativity of Professional Teachers in Professional Courses on The Basis of E-Pedagogy
Principle. Apr 2022 | ICETT International Conference on Education and Training
Technologies. DOI: 10.1145/3535756.3535767
6. O Turakulov, O Kayumov, O Kayumov Improving the quality of independent education
by creating an interactive intellectual electronic learning resource in higher education
209
institutions. International Journal of Contemporary Scientific and Technical Research. DOI:
10.5281/zenodo.7612814
7. O Turakulov, O Kayumov, O Kayumov Methodology of creating interactive electronic
educational resources and using them in the educational process. DOI:
10.5281/zenodo.7643543
8. O Kayumov Interaktiv intellektual elektron ta’lim resursidan o‘quv va mustaqil ish
jarayonilarida foydalanish metodikasi. RESEARCH AND EDUCATION, 2022
9. O Kayumov Methodological foundations of modeling the process of creating an
interactive intellectual electronic educational resource. Инновационные научные
исследования 2022
Raufov R.U. Aholining salomatlik darajasini baholashda qo‘llaniladigan usullar
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Qarshi davlat universiteti international scientific and practical conference on algorithms and current problems of programming
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