Comments (2)
Thanks for taking the time to write a clear question. However, I think it has been more than a year since I did the video so I honestly can't remember the details of the tutorial. You do ask for anybody to help you, but I think it is unlikely that anyone will answer as it is mostly only me who responds to issues here, so I've closed the issue again. You could try writing this as a comment to the video on YouTube and see if anyone can help you there.
What may also be helpful is to add a lot of print-statements so you can see the shape of the tensors that are being sent through the neural network.
In general I can say that the convolution operator is a bit tricky to understand for multi-channel inputs. Perhaps it may be helpful to watch the video a second time? As I recall, there is a part that discusses the convolution for multi-channel inputs.
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I can understand with time It becomes difficult to keep track of minute details. I was just asking for a simple intuitive explanation, not rigor details. By the way, I have posted it on Facebook lets see.
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Related Issues (20)
- when i was trying to run this code in pycharm it unables to download inception package and it results to an error ImportError: No module named 'inception' so please help me to overcome on this issue HOT 1
- Tutorial 23: Memory Error HOT 1
- ValueError: Unknown loss function:sparse_cross_entropy HOT 2
- Tutorial 21 Already Exists Error HOT 1
- 23_Time-Series-Prediction.ipynb - Predicting future values when have no test data? HOT 2
- Deprecated scipy libraries HOT 3
- acc = sess.run(accuracy, feed_dict={x: mnist.test.images, y: mnist.test.Lables}) AttributeError: 'DataSet' object has no attribute 'Lables' HOT 2
- using Elmo embedding layer in image captioning model ( Tutorial #22) HOT 1
- Image Caption works poorly HOT 6
- Tutorial 20 ValueError in Keras HOT 3
- TensorFlow 2.0 HOT 3
- Now how to forecast the future without knowing the known values? HOT 2
- AttributeError: module 'tensorflow' has no attribute 'gfile' in style transfer notebook HOT 3
- model.prediction does not match model.evaluation loss error HOT 3
- Tutorial 23 Error: Supplying multiple axes to axis is no longer supported. HOT 1
- ValueError: could not convert string to float: '28-12-2017'. I am training the time series prediction model on stock market data set and faced this error HOT 1
- issue when implementing image caption model HOT 4
- module 'tensorflow.python.ops.variable_scope' has no attribute '_VARSCOPE_KEY' HOT 2
- Korean translation HOT 2
- Tutorial 22_Image_Captioning.ipynb is not working in Colab because of disk space limit HOT 2
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