In this post, we cover the essential elements required for training Neural Networks for an image classification problem. We will still treat the internal network architecture as a black box so that we ...
In the previous posts of the TFLite series, we introduced TFLite and the process of creating a model. In this post, we will take a deeper dive into the TensorFlow Model Optimization. We will explore ...
In this article, we will learn how to create a TensorFlow Lite model using the TF Lite Model Maker Library. We will fine-tune a pre-trained image classification model on the custom dataset, further ...
The recent trend in developing larger and larger Deep Learning models for a slight increase in accuracy raises concerns about their computational efficiency and wide scaled usability. We can not use ...
In the previous post, we've learned how to work with OpenCV Java API with the example of a PyTorch convolutional neural network, integrated into the Java pipeline. Now we are going to transform ...
Stanford ML Group, led by Andrew Ng, works on important problems in areas such as healthcare and climate change, using AI. Last year they released a knee MRI dataset consisting of 1,370 knee MRI ...
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