Abstract: Stochastic gradient descent and other adaptive optimization methods have been proved effective for training deep neural networks. Within each epoch of these methods, the whole training set ...

Bayesian Neural Networks ... of BNNs in image classification tasks, specifically including the quantification and utilization of uncertainty to enhance model reliability and decision support ...

This paper proposes an end-to-end trained fully convolutional neural network model to process 3D image volumes. Unlike previous works ... operations reduces the memory footprint during training.

A generic image classification program that uses Google's Machine Learning library, Tensorflow and a pre-trained Deep Learning Convolutional Neural Network model called Inception ... In order to start ...

This model has been ... the transfer learning process, a folder named training_dataset needs to be created in the root of the project folder. This folder will contain the image data sets for all the ...

An example of an image classification problem is to identify a photograph of an animal as a "dog" or "cat" or "monkey." The two most common approaches for image classification are to use a standard ...