Tensorflow Lite, Edge Computing, Model Quantization, Energy Disaggregation.
quantization to all parts of the model, including weights, activations, and also the input and output layers. Advantages: This approach results in the smallest possible model size and is optimized for performance on devices with int8 accelerators. Usage Scenario: Best suited for edge devices with