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Questions tagged [convolutional-neural-network]

257 questions
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Keras 'Tensor' object has no attribute 'ndim'

I am trying to implement a siamese network (by using triplet loss method). I just cannot make it train. After many tries, I guess that I have my problem in the generator (where I prepare the input data stream for training) but I could not localize…
edn
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keras - flow_from_directory function - target_size parameter

Keras has this function called flow_from_directory and one of the parameters is called target_size. Here is the explanation for it: target_size: Tuple of integers (height, width), default: (256, 256). The dimensions to which all images found will…
edn
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Regression Activation Mapping for a given CNN

This paper https://arxiv.org/pdf/1703.10757.pdf disucces using Regression Activation Mapping (RAM) - instead of Class Activation Mapping (CAM). There are several articles describing how to implement CAM. But i cant find any for RAM - or the code…
Endre Moen
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Keras ImageDataGenerator flow directory with 3D CNN data format error?

I am new in Keras, I have a dataset with multiple folders each indicates to a specific class. I used ImageDataGenerator to read the data from the subfolders. I am trying to use 16 consecutive frames with size 80x100 so the input_shape is (16, 80,…
Meme
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pytorch cnn stride error

I am now using pytorch 0.4.0 in windows to build a CNN and here is my code: class net(nn.Module): def __init__(self): super(net, self).__init__() self.conv1 = nn.Conv2d(in_channels=1, out_channels=16, kernel_size=(1,3),stride=1…
Ddj
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Visualization of the filters of VGG16

I am learning CNN, right now, working on deconvolution of the layers. I have begun the process of learning upsampling and observe how convolution layers see the world by generating feature maps from the filters from the source Visualization of the…
sana
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Monte Carlo (MC) dropout in Keras with R

How to implement Monte Carlo dropout with Keras in Convolutional neural networks to estimate predictive uncertainty as suggested by YARIN GAL? I am using R.R-Code is here I am fitting the model in small batches and want to evaluate the model in…
Ehtasham Billah Mymun
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Adding visualization for every layer activation layer of Convolution Network - Keras

I have a Convolution Network (CNN) as followed. I would like to add visualization for every layer activation layer as in the There are several layer of the CNN that are doing the required task. I only want to probe the output of each layer. def…
Avi
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Conv2D: How can I get the values of each filter

My model: classifier = Sequential() # Convolutional + MaxPooling -> 1 classifier.add(Conv2D(32, (3,3), input_shape = (IMAGE_SIZE, IMAGE_SIZE, 3))) convout1 = Activation('relu') classifier.add(convout1) classifier.add(MaxPooling2D(pool_size =…
Nishit Mehta
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Training a classifier on Human pose estimation

Project description-I am planning to do a project in which I have to recognize various human actions such as yawning,sleeping,walking,etc.To do this I need features on human poses which can be done with human pose estimation. After training the…
clarky
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Pytorch inceptionV3 transfer learning gives error - max() received an invalid combination of arguments

The program for transfer learning inception_v3 in pytorch that i am using is here : https://drive.google.com/file/d/1zn4z7nOp_wJne0En6zq4WJfwHVVftERT/view?usp=sharing I am getting the following error upon running the program : Epoch 0/24 …
Harshit Nagar
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why not use the max value of output tensor instead of Softmax Function?

I built a CNN model on images one-class classification. The output tensor is a list which has 65 elements. I make this tensor input to Softmax Function, and got the classified result. I think the max value in this output tensor is the classified…
Li Shihao
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Conv2D transpose output shape using formula

I get [-1,256,256,3] as the output shape using the transpose layers shown below. I print the output shape. My question is specifically about the height and width which are both 256. The channels seem to be the number of filters from the last…
Mohan Radhakrishnan
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ValueError: Error when checking input: expected conv2d_1_input to have 4 dimensions, but got array with shape (8020, 1)

I am trying to build an image classifier but im running in to the error as mentioned in the title of this post. Below is the code im working on. How do i convert my numpy array that is of shape (8020,) to the shape as required by the function fit()?…
redwolf_cr7
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Can I use rectangle images with a convolution neural network in Keras?

Say I'd like to use Keras's Convolutional2D function to build a CNN, can the input image be of size [224, 320, 3] instead of something like [224, 224, 3]? Should I keep my images in their rectangle format or scale them to be square? I've tried…
Daniel Bourke
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