Which technology behind signlanguagehub.tech ? (1) 🧠We use Convolutional Neural Networks (CNNs) to solve the problem of Image Classification, a common technique in image processing. CNNs work by automatically learning features from input images through convolutional layers. These features include basic elements like edges , corners , lines , and more complex patterns as the network goes deeper . 📍In sign language technology, CNNs are often combined with other advanced techniques like: 1. Pose Estimation: This identifies the position and movement of key body parts, such as hands and fingers, which are crucial for understanding gestures 2, Recurrent Neural Networks (RNNs) or Transformers: These are used to analyze sequences of gestures, as sign language is highly contextual and temporal. 3. Preprocessing and Augmentation: Image preprocessing techniques help normalize input data, and data augmentation generates variations of the training data to improve the model's robustness. ✔️This combination allows the technology to translate sign language into text or speech effectively, bridging communication gaps. 📎 Read more at our White Paper docs.signlanguagehub.tech/te…