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Questions tagged [convolutional-neural-networks]

For questions about convolutional neural networks, also known as CNN or ConvNet.

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Preparation of multivariate time series data

I am doing a university project on index/stock price prediction. I plan to use a combined cnn-lstm model, and I have several different types of data: Open High Low Close Volume, values, fundamental ...
Ivan's user avatar
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Simple CNN without pooling layers, differentiability

I need to be able to produce a convolutional neural network where I am able to extract the gradients of the output pixels with respect to the input pixels. I am not really sure if I can do this using ...
James Li's user avatar
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Find the pixel sensitivity of a Convolutional Neural Network

So assume I have a simple convolutional neural network with 2 or 3 convolutional layers, a pooling layer, and whatever else is typical. The network takes in an image and tries to produce an image that ...
R S's user avatar
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i have a combined pandas dataframe X_train with 22200 samples and 3 features. how can i model this

more info on how data is generated: A signal is passed to a concrete specimen while increasing the frequency of the signal conductance,susceptance of concrete is measured.The experiment is performed ...
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My loss is increasing instead of decreasing when i use a regularizer, but if i don't use regularizer then it stays at 00000e+00 or something

This is my model architecture: ...
Kamruzzaman Uzzal's user avatar
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Need suggestions on neural network framework for mapping spatial polygon data to an output metric

I am working on exploring neural networks to create a model for a specific problem: I have a 3D spatial input which is defined by rectangular polygons (xmin, ymin, xmax, ymax, zcenter). For each ...
funnyfox's user avatar
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CNN model to infer classes from unlabelled, unpartitioned data

I'm wondering if there exists a CNN model (class of models?) designed to receive a single set of unlabelled, unpartitioned data, and attempt to infer classes. For instance, you could theoretically ...
Tom's user avatar
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CNN model configuration: advice

Assume that a CNN model is to be developed to recognize commercial domestic planes flying in the sky. The training data should include images of flying domestic planes for true positives. Additionally,...
KM23's user avatar
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Synthesising Images from Features

I'm currently trying to understand image generation a bit better. I'm working on a DDPM to generate samples from the MNIST set. My question doesn't really have anything to do with that, it's more just ...
euleriwt's user avatar
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How to get Complexity per Layer, Sequential Operations and Maximum Path Length in CNN architecture?

In the paper Attention is all you need, here is Table 1, can someone explain what architecture is referred to in the "Convolution" row and hence describe the other 3 columns in it? The other ...
Harry's user avatar
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How to do object detection for 1 object in the image, with 3 possible classes (in a custom dataset)

I am new to deep learning, I hope you will lead me because I have been stuck for a week. I am trying to build a model for identifying a single object in the image. So, I made my custom dataset, which ...
Lisa Mck's user avatar
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Can we use 3D convolution to do 2D convolution on list of input?

I am trying to run 2D convolution on a set of input tensor. The input dimension would be [batch x channel x N x height x width], where N is the number of input matrices. I want to apply 2D convolution ...
ryan chandra's user avatar
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1D CNN with Single vs. Two Channels for Number Image Recognition

I am taking images of numbers as input, in a convolutional neural network and building a model to predict the number. In particular, I am building a one dimensional convolutional neural network with ...
Ling Guo's user avatar
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Must a CNN (both 1D and 2D) take input of the same size?

I have the notion that CNN input data must always be of the same dimensions. If we are feeding 1D tabular data, columns must be of the same numbers; if we are feeding 2D image data, all the images ...
user366312's user avatar
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Do neural networks have a perception of space, regardless of dimensionality?

Suppose I have a model M which outputs a three-dimensional tensor of size 3x3x3. I have another model N which outputs a one-dimensional tensor of size 27. Train both models on some arbitrary objective ...
schmixi's user avatar
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weighted multi class classification

i'm working on a multi class classification problem which classifies jellyfish and plastic pollution so basically i have 6 classes (barrel_jellyfish, compass_jellyfish, lions_mane_jellyfish, ...
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How to remove random noise from an image (denoising)?

When adding noise to an image, for instance, is the noise added evenly random (equally likely values within some range), or random but following some distribution (like the normal distribution)? Then,...
James's user avatar
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How to perform latent space Interpolation between two images?

I have a variational convolutional autoencoder that has trained on 2 images and outputs a linear interpolation (inserted at the bottleneck stage) between those 2 input images. However, the result ...
James's user avatar
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CNN multioutput regression architecture modification

I am working on a regression task where the model has to predict two values at the same time. The idea is that the dataset consists of 16 features, where the first 8 features represent the first value ...
lukachu03's user avatar
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How to reconstruct a new image using pre-trained autoencoder?

When a single image is assigned for training, an auto-encoder should be able to gradient-descend and find the full set of satisfactory weights that will reconstruct this image. Suppose a second image ...
James's user avatar
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Is there any standardized notation for drawing neural network diagrams?

Is there any standardized notation for drawing neural network diagrams? For example, for circuits there is a universal set of symbols used to draw different types of circuits why not for neural ...
play's user avatar
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CNN Input shape for DQN Q-calculating Network

Context: I want to build a DQN with as CNN for calculating its Q value on each step. Enviroment's status can be described by the attributes of 3 machines (each one with own attributes). I'd also like ...
Oliver Mohr Bonometti's user avatar
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Trained model on cifar10 performs poorly on real images

So I'm trying to train a model using the CIFAR10 dataset. The problem is that while the performance of the model on validation and test sets are good (about 95-96%), the model fails to predict images ...
AlbertDang's user avatar
4 votes
2 answers
1k views

Why different noise in GAN generate different images?

I understand that noise $z$ serves as the input to the generator. Noise $z$ is essentially a vector of random numbers, typically from Gaussian distribution with chosen size of like $100$. However, I ...
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How do transformer-based architectures generate contextual embeddings?

How do transformer-based architectures like Roberta generate contextual embeddings? The articles I've read keep saying that transformer encoders work bidirectionally. Because of self-attention, they ...
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How can I process financial stock data before passing it to an LSTM for time series classification?

I'm trying to make an LSTM that can classify the next day of a stock as either 1 or 0 for going up or down. The issue I've been having is that Keras tuner seems to stay at a constant value of val_loss ...
JhonDenver's user avatar
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How to fine-tune pre-trained model? [closed]

I'm trying to classify a data set of medical images with a pre-trained model EfficientNetB0. I've written a code in Python with Pytorch to train my model and fine-tune it but I would like to know if ...
NitaStack's user avatar
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Extracting features from multiple curves

I am building a model that predicts the SOH of a lithium ion battery. My data are from 600 battery charge cycles as follows: for each cycle I have 3 curves each of length 128 samples: voltage, current ...
deckard1992's user avatar
1 vote
1 answer
181 views

Would AlphaZero perform better if made with transformers?

AlphaZero utilized a residual convolutional neural network to estimate move policy and position value. If it was rebuilt today, would it be more efficient and powerful if they used a transformer ...
Ben G's user avatar
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What are the differences between Inception Score and Fréchet Inception Distance?

From the articles I've read about image generation using GANs, the Inception Score measures two things simultaneously: the variety of images (diversity) and the distinct quality of each image. Does ...
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adversarial training on convnext shows a very strange curve

i am currently working on a research project where I have to train some models for adversarial robustness. I have implemented the algorithm used by a research paper called adversarial training for ...
M Akrm's user avatar
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Classifying Images that Look Like Noise

I'm about to build a system that is supposed to evaluate images (900 x 150) like the following and classify it in to one of five categories: image that looks like noise In case you're wondering, they'...
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5 votes
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How can the discriminator determine the sample is fake or real?

Based on the articles I've read, the discriminator can identify whether a sample is fake or real. However, the articles don't clarify the conditions used to determine if a sample is fake or real. I ...
user avatar
2 votes
1 answer
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What are meaning of parameters $\theta$ in this context?

I'm reading the article about generative model from Open AI, here is the section where they explain them: Our network is a function with parameters $\theta$, and tweaking these parameters will tweak ...
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2 votes
2 answers
97 views

What's the best criterion for evaluating activation maps in a CNN?

I'm currently studying CNNs and I had the idea of building a model without a fully connected layer at the end. I think this could be beneficial, if one can somehow model the desired outputs as a ...
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1 answer
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What is the matrix representation of a dilated convolution?

I am delving into the matrix representation of dilated convolutions, especially after understanding standard 1D convolutions as Toeplitz matrix-vector multiplications. My specific focus is on Dilated ...
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Does ResNext split data or copy it?

I have been learning how to create ResNext neural networks, and am confused how input works with cardinality. In this answer, it seems that it's saying that the data is added together, which I assumed ...
eop3's user avatar
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Help on calculating the right feature vector size from a CNN

I need some help calculating the feature vector size for this network I'm working on from a paper. It says the input image is 96x96x1. The first convolution layer is a filter of 5x5 with a stride of 2,...
Sanjeev Nahulanthran's user avatar
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How does the Yolo loss match bounding boxes to the ground truth?

I've been going over the YOLO paper again and I was wondering something about the loss. Yolo divides an image into grids and then for each grid can have multiple bounding boxes to detect multiple ...
Edan Patt's user avatar
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1 answer
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Why CNN filters (kernels) are randomly initialized?

I learned that when CNN filters are defined, they are initialized with random weights and bias(Im not sure about bias). Then as learning step goes on, the weight values change and each filter makes ...
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Is number of output filters right way to generate multiple output feature maps?

I am doing a CNN U-Net localization network that works on a way of scalar regression of 2D plane using Gaussian peaks in Keras. I have dataset that contains 10 different keypoint PNG's (each about 50k ...
wortelus's user avatar
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How to detect abnormal fetal head size with image classification?

I am a computer science student currently working on my final project, which involves finding a classification-based solution for predicting the head size of a fetus during its third month. Here is a ...
NitaStack's user avatar
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0 answers
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Cannot find appropriate model to classify hidden states

My input data is vector representing encoded image - 22 features, and I try to classify by 3 classes 0, 1, 2 (neutral, good, bad) Original: ...
Max Usanin's user avatar
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0 answers
26 views

Is there a better way for my CNN to handle random values?

I made an autoencoder to, ideally, turn an image into seemingly random numbers(Using a loss that determines randomness) and turn those random numbers into the original image. The results were kind of ...
Nathanael Suarez's user avatar
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Support Vector Machine used in Image Classification

I am looking for a reference preferably a paper that details how Support Vector Machines (SVMs), and OpenCV were used to perform image classification before Convultional Neural Networks (CNNs). I am ...
Jose M Serra's user avatar
3 votes
1 answer
138 views

Understanding the function of attention layers in a convolutional neural network (U-Net in a diffusion model)

I am trying to understand the neural network architecture used by Ho et al. in "Denoising Diffusion Probabilistic Models" (paper, source code). They include self-attention layers in the ...
Rational Function's user avatar
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7 views

Design approach for image classification regarding genders

I am new to the world of AI and wanted to ask your guidance on how to design a ML model to classify genders based on images. There will be only one person in the image. The person could be kids, ...
Doug's user avatar
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Ways to train a neural network continuosly as new data is added [duplicate]

There is a project I'm currently working on that requires object detection with continuous training. The idea is to train a model beforehand with a standard dataset. When I get new images I want to &...
Pedro Carvalho's user avatar
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84 views

ViT fails to detect a white pixel in a black image

I wanted to report you to some experiments in the context of Deep Learning for Computer Vision, in particular for visual reasoning. The main question I am trying to answer is the difference between ...
Fiorenzo Parascandolo's user avatar
3 votes
0 answers
92 views

Is improving a Neural Network really just "trial and error"?

After asking on StackOverflow, I was redirected here, so I'm reposting this question. I am a PhD student in Computational Physics and I've started to study a bit of Neural Networks, and decided to try ...
Mauro Giliberti's user avatar

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