… can be utilized efficiently with the integration of the internet of things (IoT) and deep learning
model. … By integrating the trained model on TensorFlow Lite and Raspberry Pi 4, the camera …

… This part of OTA-TinyML enables IoT devices to download ML models from the internet, whose
… Machine learning meets internet of things: from theory to practice. In ECML PKDD, 2021. …

… This CNN model was initially trained and verified in MATLAB and then implemented on the
Machine Learning (ML) framework to generate a TensorFlow lite (TF-lite) flat buffer format. …

… The first half also mentions the tensorflow results as a part of human identification and tells
the result as “person” with the amount of percentage by which the tensorflow model identified …

… Third step (Model conversion) After getting a trained model, we will convert it to a TensorFlow
Lite version. TensorFlow lite model is on a special format model called Lite flat buffer file (.…

… are used to implement TensorFlow Lite [1] kernel operations such as convolution and
matrix multiplication. We added these optimized functions to TensorFlow Lite source code and …

… MATERIALS AND METHODS Our proposed methodology to predict TensorFlow Lite …
TensorFlow Lite (TFLite) models were selected for the experiment because of several key …

… with Tensorflow Lite compared to the original Tensorflow. Using the MobileNetV2 model with
Tensorflow Lite… Tensorflow. As for the ResNet50, the inference time is only slightly faster on …

… We use the TensorFlow Lite platform with quantization techniques to convert the models into
lighter … when optimized with TensorFlow Lite without sacrificing the accuracy of the models. …

… implementations and programming frameworks (eg, Tensorflow lite1, Apache MXNet2, Cloud3).
… At the end of part I, the audience would have an idea of TensorFlow Lite, Arduino IDE, a …