Given a pre-trained ResNet152, in trying to calculate predictions bench-marks using some common datasets (using PyTorch), and the first RGB dataset that came to
How can I make this DNN model in tensorflow? 31 neurons in the first, 10 in the second, 5 in the third hidden layer, and 2 neurons in the output layer. The acti
I am using CNN-LSTM network for image classification. My image size is (224, 224, 3) and batch size is 90. I m getting this error when i passing input to LSTM l
How do I fit two unproportional arrays to a regression model? Is it possible to resize/reshape one without loosing the data? I used the code from here but my tr
set of word vectors are generated from github link:https://github.com/jianwei76/SoliAudit/blob/master/va/features/op.origin.csv.xz. Converted this op.origin.csv
I am getting the same prediction for different inputs. I am trying to use a regressional neural network. I want to predict values instead of class using neural
unknow error I am not sure what is the reason, probably my index exceed the limit of the input? But how can I solve this error? Here is the code I used https://
I am getting error as from pysat.solvers import Glucose3 ModuleNotFoundError: No module named 'pysat.solvers'* when I am trying newer version of pysat. I cann
I am trying to build a classification model, but I don't have enough data. What would be the most appropriate way to create synthetic data based on my existing
I am currently working on instance segmentation. I follow these two tutorials: https://haochen23.github.io/2020/06/fine-tune-mask-rcnn-pytorch.html https://col
The callback is called when specific events occur in an environment (e.g. at the beginning/end of a reset and beginning/end of a step). I have written a stub of
RGB images can be stored in memory in different ways, e.g. see link below planar and interleaved: http://avitevet.com/uncategorized/when-to-use-it-interleaved-v
I'm writing a code with albumentations function and it will give me this error ModuleNotFoundError: No module named 'albumentations' I also installed this pack
I am using VGG19 pre-trained model with ImageNet weights to do transfer-learning on 4 classes with keras. However I do not know if there really is a difference
I've a dataset of almost 3k colored images each of dim 1920x1080 and I want to store it in a numpy array so when calling shape on it in returns (3716,493,491,3)
I am new to speech recognition. I've read some blogs about CTC. It tackles sequence problems where the timing is variable. One piece of speech signal may contai
I am trying to run a yolov4 + DeepSORT object tracker on tensorflow. However, when I attempt to run save_model.py to convert the darknet weights of yolov4 to a
Question I have code that is based on Part 2, Chapter 11 of Deep Learning with PyTorch, by Luca Pietro Giovanni Antiga, Thomas Viehmann, and Eli Stevens. It's
I was wondering how we could use jax (https://github.com/google/jax) to compute a mapping of the derivative. That is to say : we have a vector and we want t
So for example, I have trained a CNN on my data using a learning rate of 0.0003 and 10 epochs, with a minibatch size of 32. After training it, lets say I get an