Data Science Stack Exchange
Data Science Stack Exchange

Questions tagged [cnn]

Convolutional Neural Networks (CNN, also called ConvNets) are a tool used for classification tasks and image recognition. The name giving first step is the extraction of features from the input data.

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How to set batch_size, steps_per epoch, and validation steps?

I am starting to learn CNNs using Keras. I am using the theano backend. I don't understand how to set values to: batch_size steps_per_epoch validation_steps What should be the value set to batch_size, steps_per_epoch, and validation_steps, if I…
Ermene
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What's the difference between Attention vs Self-Attention? What problems does each other solve that the other can't?

As stated in the question above..is there a difference between attention and self attention mechanism ? Also additionally can anybody share with me tips and tricks about how self attention mechanism can be implemented in CNN?
Pratik.S
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Why do convolutional neural networks work?

I have often heard people saying that why convolutional neural networks are still poorly understood. Is it known why convolutional neural networks always end up learning increasingly sophisticated features as we go up the layers? What caused them…
Praise the lord
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What is the difference between upsampling and bi-linear upsampling in a CNN?

I am trying to understand this paper and am unsure of what bi-linear upsampling is. Can anyone explain this at a high-level?
JGG
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What is a channel in a CNN?

I was reading an article about convolutional neural networks, and I found something that I don't understand, which is: The filter must have the same number of channels as the input image so that the element-wise multiplication can take place. Now,…
J.D.
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back propagation in CNN

I have the following CNN: I start with an input image of size 5x5 Then I apply convolution using 2x2 kernel and stride = 1, that produces feature map of size 4x4. Then I apply 2x2 max-pooling with stride = 2, that reduces feature map to size 2x2.…
koryakinp
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How to add non-image features along side images as the input of CNNs

I'm training a convolutional neural network to classify images on fog conditions (3 classes). However, for each of about 150.000 images I also have four meteorological variables available that might help in predicting the classes of the images. I…
Josh
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In CNN, why do we increase the number of filters in deeper Convolution layers for complex images?

I have been doing this online course Introduction to TensorFlow for AI, ML and DL. Here in one part, they were showing a CNN model for classifying human and horses. In this model, the first Conv2D layer had 16 filters, followed by two more Conv2D…
Sanjay
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What are the differences between Convolutional1D, Convolutional2D, and Convolutional3D?

I've been learning about Convolutional Neural Networks. When looking at Keras examples, I came across three different convolution methods. Namely, 1D, 2D & 3D. What are the differences between these three layers? What are their use cases? Are there…
Saurabh
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Updating the weights of the filters in a CNN

I am currently trying to understand the architecture of a CNN. I understand the convolution, the ReLU layer, pooling layer, and fully connected layer. However, I am still confused about the weights. In a normal neural network, each neuron has its…
Felix
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How to prepare the varied size input in CNN prediction

I want to make a CNN model in Keras which can be fed images of different sizes. According to other questions, I could understand how to set a model, like Input =(None,None,3). However, I'm not sure how to prepare the input/output…
kainamanama
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what is darknet and why is it needed for YOLO object detection?

what is darknet and why is it needed for YOLO object detection ? I read that its a neural network written in C , but why is it needed for YOLO object detection when we have lot of machine learning framework,api like tensorflow,keras,pytorch . Im…
star
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CNN - How does backpropagation with weight-sharing work exactly?

Consider a Convolutional Neural Network (CNN) for image classification. In order to detect local features, weight-sharing is used among units in the same convolutional layer. In such a network, the kernel weights are updated via the backpropagation…
Andy R
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Finding outliers in Image dataset

I have been working on an image classification tasks for which I am extracting the image frames from the video stream collected for different classes. I have already trained an image classification model (using transfer learning) however due to the…
deepguy
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What is difference between Fully Connected layer and Bilinear layer in CNN?

What is the difference between Fully Connected layers and Bilinear layers in deep learning?
N.IT
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