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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…
Sign Language Hub retweeted
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…
19th training results of SLHUB model
train/box_loss: Decreases steadily over epochs, indicating better bounding box predictions.
📔Read more: docs.signlanguagehub.tech/ar…
Sign Language Hub retweeted
The @grok summary for $SLHUB.
This is a wonderful humanitarian project that is truly innovating for the betterment of the language barriers often surrounding the deaf Community.
@SignLanguageHub ❤️ 🤗
Nice to know that Grok likes us,
Thanks @elon
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Sign Language Hub retweeted
I highly recommend checking out @SignLanguageHub's website, since lots of the tech is already up and running.
I'm a linguist by trade, and I always wanted to learn sign language, so I'll definitely dive into that AI online course 🫳🤏✌️
Gud tek $SLHUB
signlanguagehub.tech/learnin…
For those who don't understand our final product, watch this video.
I accidentally saw this lenovo video 1 year ago and felt very impressed by it. This video inspired me to create Sign Language Hub. Currently Lenovo has not announced the product, this is just their trailer!
We are currently building, big thing need time to cook, thank you for your patience with Sign Language Hub, I love you all 💕
I've seen some people say our project is just "fake" technology. This post I will prove the opposite.
Please read the comments section below 👇
(sorry for bad quality camera, i will buy a new one tomorrow)
