3D Convolutional Neural Network input shape
I'm having a problem feeding a 3D CNN using Keras and Python to classify 3D shapes. I have a folder with some models in JSON format. I read those models into a Numpy Array. The models are 25*25*25 and represent the occupancy grid of the voxelized model (each position represents if the voxel in position (i,j,k) has points in it or no), so I only have 1 channel of input, like grayscale images in 2D
One year as a Data Scientist at Stack Overflow
David Robinson Director of Engineering at Contentsquare Email Twitter Github Stack Overflow Subscribe Recommended R Bloggers RStudio Blog R4Stats Simply Statistics Upfront One day in January 2013 I found myself wasting time on the internet. This wasn’t a good idea: I was as busy as anyone 2.5 years into their PhD. I had to finish a presentation on some yeast genetics research, I was months behind
What are advantages of Artificial Neural Networks over Support Vector Machines?
As it currently stands, this question is not a good fit for our Q&A format. We expect answers to be supported by facts, references, or expertise, but this question will likely solicit debate, arguments, polling, or extended discussion. If you feel that this question can be improved and possibly reopened, visit the help center for guidance. ANN (Artificial Neural Networks) and SVM (Support Vector M
Convolutional Neural Network (CNN) for Audio
I have been following the tutorials on DeepLearning.net to learn how to implement a convolutional neural network that extracts features from images. The tutorial are well explained, easy to understand and follow. I want to extend the same CNN to extract multi-modal features from videos (images + audio) at the same time. I understand that video input is nothing but a sequence of images (pixel inten
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