Neural NetwF. Wang, H. Liu, and J. Cheng. Visualizing deep neural network by alternately image blurring and deblurring. Neural Networks, 97:162-172, January 2018.Feng Wang, Haijun Liu, Jian Cheng, "Visualizing deep neural network by alternately image blurring and deblurring", Neural Networks,...
A Task-and-Technique Centered Survey on Visual Analytics for Deep Learning Model Engineering tools for visualizing a network's architecture, to facilitate the interpretation and analysis of the training process, or to allow for feature understanding... R Garcia,AC Telea,Bruno Castro da Silva,......
"Visualizing Deep Neural Network Decisions: Prediction Difference Analysis" - Luisa M Zintgraf, Taco S Cohen, Tameem Adel, Max Welling which was accepted at ICLR2017, see https://openreview.net/forum?id=BJ5UeU9xx Note that we are only publishing the code for the ImageNet experiments, since...
To visualize the intermediate layers of a neural network, we can use pre-trained models and tools available in popular deep learning libraries such as TensorFlow or PyTorch. Let’s take a look at a simple code example using TensorFlow: importtensorflowastffromtensorflow.keras.applicationsimportVGG16...
Extract 3D feature maps of all volume data with the 3D deep residual autoencoder. Align all 3D volumes and adjust them to share a common frame of reference. Initialize the hyper-parameters of the 3D autoencoder (Table 1). Train the neural network with the 3D volume data to minimize the ...
DeepBoof is a Java library for running deep neural networks trained using other projects (e.g. Torch and Caffe) with a focus on processing image data. Additional tools include visualization and network training. Image processing is done usingBoofCV. While it has been designed to work withTorch...
Hinton, G.E., Srivastave, N., Krizhevsky, A., Sutskever, I., Salakhutdinov, R.R.: Improving neural networks by preventing co-adaptation of feature detectors. In: arXiv:1207.0580 (2012) 15. Howard, A.G.: Some improvements on deep convolutional neural network based image classification. ...
Indeed, if you want to know the algorithm behind a PyTorch model, this is also the way to go. There are only a few tools to create graphics from a PyTorch model. In below, you will learn about the tool Netron. It is a “deep learning model viewer”. It is a software that you ca...
Deep learning models, primarily Graph Neural Networks, have also been used for in-layout optimization and shown to generate graph layouts that satisfy multiple aesthetic indicators [40], thus presenting a potential for balancing computational efficiency with visual quality in large graph layout ...
Maren AJ, Harston CT, Pap RM. Handbook of Neural Computing Applications. Academic Press; 2014. Schmidhuber J. Deep learning in neural networks: an overview. Neural Netw. 2015;61:85–117. ArticleGoogle Scholar McCue C. Data mining and predictive analysis: intelligence gathering and crime analysis...