MosChip®

Hand Gesture Recognition for Low Power FPGA Devices

A case study of AI Engineering

The client is a manufacturer of low-power semiconductor based in United States. They solve customer problems across the network, from Edge to Cloud, in the growing communications, computing, industrial, automotive and consumer markets. With advanced technology, they enable their customers to quickly and easily unleash their innovation to create a smart, secure, and connected world. The client approached MosChip to build a custom hand gesture recognition model using neural network which will act as a reference model to build other similar applications.

  • Delivered NN based hand gesture recognition model with 91% accuracy, quick deployment, and scalability

Hand Gesture Recognition for Low Power FPGA Devices

A case study of AI Engineering

The client is a manufacturer of low-power semiconductor based in United States. They solve customer problems across the network, from Edge to Cloud, in the growing communications, computing, industrial, automotive and consumer markets. With advanced technology, they enable their customers to quickly and easily unleash their innovation to create a smart, secure, and connected world. The client approached MosChip to build a custom hand gesture recognition model using neural network which will act as a reference model to build other similar applications.

  • Delivered NN based hand gesture recognition model with 91% accuracy, quick deployment, and scalability
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