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Journals / Avrupa Bilim ve Teknoloji Dergisi / 2026 / Sayı: 36 Özel Sayı

Detecting Sign Language from Hand Gestures and Translating it into Text

El Hareketlerinden İşaret Dilini Algılayıp Yazıya Dönüştürme

Pınar Kırcı(Bursa Uludağ Üniversitesi)0000-0002-0442-0235
Burçin Berk Durusan(Bursa Uludağ Üniversitesi)0000-0002-6510-8122
Baha Özşahin(Bursa Uludağ Üniversitesi)0000-0002-8463-5737
Pages
32–35
Publication Date
2022-05-31
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

The object recognition method to be used was chosen as MediaPipe Holistic.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:The sign language recognition project to be designed is aimed to be realized in an optimized way using up-to-date technologies.
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Key Findings & Data:The machine learning part of the project will be done over TensorFlow using Keras and Sklearn.
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Conclusion & Impact:The object recognition method to be used was chosen as MediaPipe Holistic.
🔬Design:Modeling & Simulation
📍Scope:Comprehensive Sample
⚙️Variables:Gerçek Zamanlı İşaret Dili Tanıma · Makine Öğrenmesi · Derin Öğrenme

Abstract

The sign language recognition project to be designed is aimed to be realized in an optimized way using up-to-date technologies. The machine learning part of the project will be done over TensorFlow using Keras and Sklearn. TensorFlow was chosen considering the possibility of moving the project to a mobile environment in the future. The object recognition method to be used was chosen as MediaPipe Holistic.

Özet

Tasarlanacak işaret dili tanıma projesinin güncel teknolojiler kullanılarak optimize biçimde gerçeklenmesi amaçlanmıştır. Projenin makine öğrenmesi bölümü Keras ve Sklearn kullanılarak TensorFlow üzerinden yapılacaktır. TensorFlow, ilerleyen aşamalarda projeyi mobil bir ortama taşıma ihtimali göz önünde bulundurularak seçilmiştir. Kullanılacak nesne tanıma yöntemi MediaPipe Holistic olarak seçilmiştir.

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Cite This Article

Kırcı, P., Durusan, B. B., Özşahin, B. (2022). Detecting Sign Language from Hand Gestures and Translating it into Text. Avrupa Bilim ve Teknoloji Dergisi, Sayı: 36 Özel Sayı, 32–35. https://doi.org/10.31590/ejosat.1097389

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References (7)

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