I provide the Bilinear_CNN (BCNN) implmentation in TensorFlow. bcnn_DD_woft.py and bcnn_DD_woft_with_random_crops.py are TensorFlow files used for the first step of the training procedure where only ...

Tensorflow tutorial on convolutional neural networks. In this tutorial, you’ll learn the architecture of a convolutional neural network (CNN), how to create a CNN in Tensorflow, and provide ...

TensorFlow 2.0, released in October 2019, revamped the framework significantly based on user feedback. The result is a machine learning framework that is easier to work with—for example, by ...

The Keras code calls into the TensorFlow library, which does all the work. In Keras terminology, TensorFlow is the called backend engine. Interestingly, Keras has a modular design, and you can also ...

Looking at other TensorFlow implementations of Faster R-CNN, I stumbled upon the use of tf.stop_gradient() in the regression loss functions in one code base. Lo and behold, this magically fixed the ...

Engineers working on Google’s TensorFlow machine learning framework have revealed a subproject, MLIR, that is intended to be a common intermediate language for machine learning frameworks. MLIR ...

At Google’s inaugural TensorFlow Dev Summit in Mountain View, California, today, Google announced the release of version 1.0 of its TensorFlow open source framework for deep learning, a trendy ...