TRAINING OF A CONVOLUTIONAL NEURAL NETWORK FOR HAND GESTURE RECOGNIZING ON THE KAGGLE ASL ALPHABET DATASET

Authors

  • Gļebs Vituškins Rēzeknes Tehnoloģiju akadēmija
  • Sergejs Kodors Zinātniskā darba vadītājs, Dr.sc.ing., Rēzeknes Tehnoloģiju akadēmija

DOI:

https://doi.org/10.17770/het2023.27.7377

Keywords:

neural network, Kaggle, recognizing, sign language, TensorFlow,

Abstract

Nowadays, hand gesture recognizing is important topic. It is used in virtual assistant work, for sign language translation, in virtual and augmented reality applications, and in entertainment services. The paper deals with the convolutional neural network training using different technologies. The neural network is trained to classify American manual alphabet and 3 extended gestures using photographs. The open access dataset Kaggle ASL Alphabet was used for training. Kaggle ASL Alphabet provides 87000 images of 29 classes for image classification and hand gesture recognizing.

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References

Google, Use gestures to control your Google Assistant on headphones https://support.google.com/assistant/answer/7513985?hl=en&co=GENIE.Platform%3DAndroid

Sumit Saha, A Comprehensive Guide to Convolutional Neural Networks — the ELI5 way. https://towardsdatascience.com/a-comprehensive-guide-to-convolutional-neural-networks-the-eli5-way-3bd2b1164a53

Benjamin Zeman, What is Google Colab? https://www.androidpolice.com/google-colab-explainer/

TensorFlow. https://www.tensorflow.org/tutorials

Kiprono Elijah Koech, The Basics of Neural Networks (Neural Network Series). https://towardsdatascience.com/the-basics-of-neural-networks-neural-network-series-part-1-4419e343b2b

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Published

2023-10-30