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Add TFLite Edge TPU Docs Integrations Page (#8900)

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Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com>
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Abirami Vina 2024-03-13 18:56:42 +05:30 • committed by GitHub
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docs/en/integrations/index.md
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@ -65,6 +65,8 @@ Welcome to the Ultralytics Integrations page! This page provides an overview of
- [TFLite](tflite.md): Developed by [Google](https://www.google.com), TFLite is a lightweight framework for deploying machine learning models on mobile and edge devices, ensuring fast, efficient inference with minimal memory footprint.
- [TFLite Edge TPU](edge-tpu.md): Developed by [Google](https://www.google.com) for optimizing TensorFlow Lite models on Edge TPUs, this model format ensures high-speed, efficient edge computing.
- [PaddlePaddle](paddlepaddle.md): An open-source deep learning platform by [Baidu](https://www.baidu.com/), PaddlePaddle enables the efficient deployment of AI models and focuses on the scalability of industrial applications.
- [NCNN](ncnn.md): Developed by [Tencent](http://www.tencent.com/), NCNN is an efficient neural network inference framework tailored for mobile devices. It enables direct deployment of AI models into apps, optimizing performance across various mobile platforms.