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Questions tagged [convolutional-neural-network]

A convolutional neural network is a form of neural network with an additional convolutional layer, typically used in image & audio analysis. The convolutional layer is essentially a filtering stage defined by the kernel which is used. For example, a convolutional layer could have a kernel which extracts edges from an image towards the goal of learning which objects are in a scene.

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Dealing with noise in softmax output

I have a device with an accelerometer and gyroscope (6-axis). The device sends live raw telemetry data to the model 40 samples for each input, 6 values per sample (accelerometer xyz, gyroscope xyz). ...
Sterling Duchess's user avatar
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Shape of Flattened Layer in CNN

If I have a convolutional layer with dimension (5,5,4), (i.e, 4 no. of 5x5x1 feature maps), what will be the dimension of the flattened layer, if I apply flattening ...
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Why do I get such a low accuracy despite having good metrics?

I'm working on an image segmentation problem. I'm fine-tuning the network, and when displaying the metrics I obtain, I have some doubts. I am going to provide some details about the network: Solver: ...
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How to align the description of a convolutional neural network in keras with wikipedia's conceptual model?

I was going through the introductory guide to convolutional neural networks in tensor flow here And I was trying to logically map some of the code I saw to my actual understanding of how convolutional ...
Sidharth Ghoshal's user avatar
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What kind of learning do I need ? (use-case specific)

Consider a scenario where I have a model trained on gesture videos (say a 3D ResNet). I am looking for a technique (or a combination) that allows me to further train the model every time I have a new ...
batman's user avatar
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How to backpropagate transposed convolution with stride and padding

Please, help! I have deadlines and I do not have time to figure out the topic on my own. And now about the problem. I'm currently trying to figure out back propagation in transposed convolution. I ...
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Does one need a understanding in Convolutional Neural Networks before learning about Quantum Convolutional Neural Networks

I have a degree in Physcis and want to learn about Quantum Convolutional Neural Networks. Is it recommeneded that i known about Convolutional Neural Networks before learning about Quantum ...
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Conv1d() input and output dimensions?

I'm unclear how does the PyTorch Conv1d() work. Consider the following model which takes raw mono audio samples at input: ...
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precision and recall is zero

Why my model shows metrics like this? While my model was training recall and precision was equal to zero? I trying to do binary classification of mushrooms [edible, poisonous]. I have CNN model with ...
User Name's user avatar
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How do I implement convolution partially on my dataset?

I'm training a neural network on the results of a CFD simulation (or rather, 300-ish simulations with different initial conditions). The dataset contains the values for temperature, density, velocity, ...
Sisyphus's user avatar
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Convolution neural network loss increasing instead of decreasing

I am working on a binary image classification task in which I have greyscale images of size (1, 224, 224) (all normalized between 0 and 1) and a set of labels (0 or 1). I have around 2.6k images with ...
Akshit Sharma's user avatar
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How do I interpret GRAD-CAM's feature attribution to time series zero-padding in a CNN classifier?

Problem setting: MTS Classification with CNN architecture I have a multivariate time series (MTS) dataset that contains 30 features. The goal is to solve a classification problem on this MTS dataset. ...
Victor Neverland's user avatar
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How to implement CNN crop area as learnable parameter?

I'm currently implementing a 1D CNN to forecast a time series for an industrial process. Essentially, I give the model 30 time steps (1 time step = 1 minute) of input data captured from 7 different ...
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Questions about receptive field in the context of a practical CNN

I'm trying to understand the concept of receptive field better in the context of a practical CNN. All of the online info I can find on receptive field seems to be in a non-practical context so I'll ...
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How to correct ValueError about incompatible dimensions of training data set in locallyconnected1D layer NN

I'm training this simple network with a few points, but it can't train. The model looks okay, but when training it raises a ValueError about the dimension of the training data sets. Could someone help?...
KaRJ XEN's user avatar
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Keras CNN model is throwing as error message as 'ValueError: Layer 'conv1d_12' expected 2 variables, but received 0 variables during loading'

Hope you're in good health and doing great. I am trying to implement a CNN model to help predict kidney stones. Now, this model is running as expected on my local machine, but when I try deploying the ...
Suvam Kumar's user avatar
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How to copy and crop feature map in Unet?

I am confused about the principle of copy and crop in U-net, like the grey line shown above. For example, the first grey line, how to convert a (64, 568, 568)(C,W,H) to a (128, 392, 392), did the ...
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Python Tensorflow - Predict human vs horses images always same value

I'm trying to follow a tutorial about Tensorflow in Python and computer vision. In this exercise I'm using a pre-trained model (InceptionV3) and some image augmentation about a datasets of humans vs ...
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Fast Fourier Transform in computer vision

Can someone explain me how does FFT works in computer vision, please. I know something about FFT as an algorithm of competitive programming but I can't understand how it perform an image in computer ...
prostak's user avatar
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Pytorch mat1 and mat2 shapes cannot be multiplied

The error message shows RuntimeError: mat1 and mat2 shapes cannot be multiplied (32x32768 and 512x256) I have built the following model: ...
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CNN sharing weights in feature map

what do they mean when they say all neurons in a channel share weights with one another? Do they mean that in a chanel or a featue map the weights are the same ?
heyoka955's user avatar
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Transpose Convolution Output Size

I have been learning GAN (Generative Adversarial Networks) lately and having a hard time understanding the output size for transpose convolution. Let's say I am using a Tensor of [1, 64, 1, 1] as an ...
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Visualizing convolutional neural networks embedding

In this article, the author creates a graph (at the end of the post) from the embeddings of different words found by transformer model. I would like to do a similar thing for a convolutional neural ...
Zan's user avatar
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S-Shaped Learning Curve

For a model that I'm currently testing, I get an S-Shaped curve when plotting the MAE over consecutive epochs, as shown in the image below. I was curious if this indicates a problem with the model or ...
Colin Dumitru's user avatar
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Data augmentation layer based on physical model for time series data

I am quite new to the Keras API, so forgive me if I use incorrect terminology and for my lack of knowledge about the API. This is for a mathematical (wave modelling) research project and I am quite ...
LightninBolt74's user avatar
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Manual computation of the predictions in a convolutional neural network

I am trying to manually compute the predictions of the Keras library for a convolutional neural network. However, I am struggling a lot to match my final result with the ones provided by Keras. I do ...
mdslt's user avatar
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Is it possible to reverse the layers of a convolutional neural network?

From my understanding typically a convolutional neural network has a matrix (e.g. an image) as input and output is either an integer or a vector of integers in regression and in classification a ...
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Bad performance with CNN for basic image classification task

how are you doing? I'm playing around with CNN in FastAI. My model with 2 millions parameters only has around 80% accuracy. I also tried with Data normalization, Batch normalization, Label smoothing, ...
Toan Nguyen's user avatar
1 vote
2 answers
121 views

Should a CNN generalize to arbitrary positions in the data?

I have trained a CNN on one dimensional data that is the power spectral density (PSD) of a $N$ different classes of signals ($N=4$). Each of the $N$ signals has a different spectral shape (not shown ...
BigBrownBear00's user avatar
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Python dataset normalization for convolutional autoencoder

I have a csv files which contain pixel neighboorhood information. Here an example of the dataset: ...
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Python train convolutional on numerical values shape issue

I want to train a convolutional neural network autoencoder on a csv file which contains values pixel neighborhood position of an original image of 1024x1024. When I try to train it, I have the ...
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ValueError: Input 0 of layer "model_12" is incompatible with the layer: expected shape=(None, 256, 256, 3), found shape=(256, 256, 3)

I am following this keras example with my own dataset, which has 3 classes. I load the images using ...
Javi's user avatar
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Predict the values of variable features over timestamps

HI i am having a dataset which contain timestamps and number of users at that timestamp. Each user has resource values which change per timestamp. How can i make predictions of number of users ...
God gives Pizza's user avatar
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1 answer
127 views

Matching nodes in two directed graphs

How to match a node of graph X with the same node in graph G if: Every node has only one feature: text string, and Nodes in different graphs are considered to be equal if: ...
dokondr's user avatar
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Why is my segmentation model not returning a heat map?

I have implemented two CNN architectures to perform segmentations on medical images: the classic UNet and a modified version called the Attention UNet. I have been training the models on roughly 50,...
Noam's user avatar
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1 answer
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Training a CNN in production on new data

How should I approach training a convolutional neural network in production on new data when I detect model performance degradation due to data or concept drift? Resources like this one and this one ...
Fijoy Vadakkumpadan's user avatar
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` TypeError: int() argument must be a string, a bytes-like object or a number ` raised when fitting a multi input Keras model

I'm currently building a U-net model handling multiple input streams of data with Keras/Tensorflow's Functional API. Even though my model compiles, it raises a TypeError when I try to fit it. This ...
ydemers's user avatar
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1 answer
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Strange results from CNN in Keras

I have a binary classification problem. I designed a model with convolution kernels in first layers and then dense layers. As the output layer, however, I used a softmax layer with size 2, and then ...
Farzad's user avatar
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3 answers
2k views

Why is resizing images is important when applying CNN or deep learning models?

I have images from deep sea, some are good quality and some barely anything is visible I want to classify the images (they're already labelled) I performed few image enhancement tested it on few ...
yellowAndriod's user avatar
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1 answer
266 views

Model does not learn when using Keras 'flow_from_directory', but learns fine with 'image_dataset_from_directory'?

When classifying images with Keras, I am able to achieve a validation accuracy around 90-95%, however, I am trying to improve with the use of augmentation so have switched from ...
BDI's user avatar
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Keras Custom Layer Aware of Position in Network

I'm writing a custom Layer in TF/Keras (tf.keras.layers.Layer) for a CNN, and I need each layer to know its own depth in the model. Is there any way I can do this, ...
Liam F-A's user avatar
1 vote
0 answers
21 views

How to design and use CNNs for sentence classification?

I'm playing around with using CNNs for sentence classification. Basically all models I found implement the same model proposed in Convolutional Neural Networks for Sentence Classification (Kim, 2014), ...
Christian's user avatar
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5k views

Keras Graph Execution Error When fitting the model

I am using this https://keras.io/examples/vision/conv_lstm/ code and providing my own dataset, which consists of frame size 550x775. But When I try to execute the ...
Muhammad Iqbal's user avatar
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1 answer
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By what mechanism would a convolutional network identify features across an image?

I have a network which takes a 256x256x128 input image which has a bunch of 3D convolutional and 3D transpose convolutional layers and ends up as a 128x128x64 reconstructed image. And it's working ...
Omroth's user avatar
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Loss is very erratic in the 100s and val_loss is at 0, something - what is the reason for that?

I have a problem. I would like to solve a NLP classification problem. For this I have trained a CNN and since I have other features, I wanted to include them in the model training. Thus I have ...
Test's user avatar
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Sigmoid Activation Function (Output layer) Alternative

I have a Convolutional-VAE architecture where the target images are in the range [0, 1], their pixel values. To synthesize/reconstruct images in this scale, I am using a sigmoid activation function in ...
Arun's user avatar
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Will a pre-trained model work in a totally different data domain?

Pre-trained model is widely ultilized in different jobs. I wouder whether a pre-trained model which is trained on data domain A will work well on data domain B. For example, if I fine-tune a model(...
Nik Li's user avatar
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1 answer
819 views

CNN model why is ReLu used in Conv1D layer and in the first Dense Layer?

I have a problem. I have a CNN model which is used for an NLP problem. This is written in Python. I have questions about this, which I can't find an answer to. Why is ReLu used inside the Conv1D ...
Test's user avatar
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2 answers
181 views

Regression Using Image Data

I am trying to build a model to predict how much time does it cost to produce a component. I am using 600 images for training and validation. I also use data augmentation. I tried many combinations ...
misafirmisim's user avatar
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1 answer
21 views

Is it ok to separate data to train on different time instead of putting all in one go?

So let say i have 10,000 images ready to be trained on. But my GPU cannot handle all of that. So the questions is: Can i train the model 10 times with 1000 images each time, with same epochs and ...
huanidz's user avatar

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