A convolutional neural network (CNN, or ConvNet) is a class of deep, feed-forward artificial neural networks that has successfully been applied to analyzing visual imagery.
I was running TensorFlow and I happen to have something yielding a NaN. I'd like to know what it is …
python machine-learning neural-network tensorflow conv-neural-networkI'm going through the neural transfer pytorch tutorial and am confused about the use of retain_variable(deprecated, now referred …
neural-network conv-neural-network backpropagation pytorch automatic-differentiationMy team is training a CNN in Tensorflow for binary classification of damaged/acceptable parts. We created our code by …
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tensorflow conv-neural-networkI have a trained model that I've exported the weights and want to partially load into another model. My model …
machine-learning tensorflow keras conv-neural-networkI have been trying to understand how unpooling and deconvolution works in DeConvNets. Unpooling While during the unpooling stage, the …
image-processing machine-learning neural-network deep-learning conv-neural-networkI would like to use 1D-Conv layer following by LSTM layer to classify a 16-channel 400-timestep signal. The input shape …
python keras time-series conv-neural-network lstmIn this tutorial about object detection, the fast R-CNN is mentioned. The ROI (region of interest) layer is also mentioned. …
deep-learning computer-vision conv-neural-network object-detectionI was testing some network architectures in Keras for classifying the MNIST dataset. I have implemented one that is similar …
machine-learning neural-network deep-learning keras conv-neural-networkI've working on a CNN over several hundred GBs of images. I've created a training function that bites off 4Gb …
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