All Questions
63 questions
0
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0
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19
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Efficient Net V2 M ONNX model infers significantly slower on small input
When I convert an Efficient net v2 m model from Pytorch to Onnx on differently sized inputs, I notice a strange and unexplained behavior. I was hoping to find an explanation to my observations from ...
0
votes
0
answers
37
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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 ...
- 121
1
vote
0
answers
86
views
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 ...
user77925
0
votes
0
answers
81
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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 ...
user77925
5
votes
1
answer
794
views
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 ...
user79662
2
votes
1
answer
152
views
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 ...
user79662
1
vote
1
answer
639
views
Which epoch is the best for me to choose?
I have trained my deep learning model. I also saved the validation loss to a file and plotted on a graph
I have $2$ questions for this:
Does the validation loss look normal? Is there any issue with ...
user78437
1
vote
1
answer
115
views
Do GANs have constant running time?
After the model is trained, you just need to input random noise and the generator will output an image, does this mean GANs have constant running time ? I'm asking about both naïve GAN and variants of ...
user78202
1
vote
2
answers
259
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The training process of a conditional GAN
For example, consider a dataset like MNIST. I give the conditional vector to produce only the number $7$ for both the generator and discriminator. In the following scenarios, what will the ...
user77925
0
votes
1
answer
386
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In the conditional GAN (cGAN) architecture, why does the discriminator need conditional variable?
I'm reading about conditional GAN (cGAN) architecture, what I know is that the generator creates images combining both noise vector and conditional variable, the noise vector brings in random elements ...
user77925
2
votes
0
answers
31
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How can I learn about NN architecture?
I have a pretty good understanding of individual neural net layers (fully connected, convolution, pooling, activation, etc) but struggle to construct combinations of them to solve a given problem. I ...
- 21
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3
answers
1k
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why validation accuracy be greater than training accuracy for deep learning models? [closed]
I hope you are well.
I had a problem and didn't understand the answers given on questions similar to my question.
If possible, please answer this problem in a simpler way.
Val_acc : %99.4 _
Train_acc :...
2
votes
1
answer
694
views
Using GraphSAGE model for multigraph datasets
I checked out applications of GraphSAGE and it seems like its primarily used for single graph datasets. For example - Cora dataset - Its one big graph with 2708 nodes and 5429 edges. The model can ...
- 123
0
votes
0
answers
164
views
Predict placement of an object in 3D space
I am trying to find a way to train a model to predict the correct placement of entities like a tree, dog and cat in a natural 3D environment. Any help regarding how I could use textual data to learn ...
1
vote
1
answer
83
views
Non-sliding kernels for location-aware processing in Convolutional Neural Networks
My understanding of how CNN operates in image detection is through the use of kernels that slide through the image to detect features (edges and so on). So a single kernel could potentially be ...
- 11
2
votes
0
answers
156
views
Decreasing number of neurons in CNN
the conventional way of creating a CNN is using increasing number of neurons:
...
1
vote
0
answers
164
views
How to pass variable length data as feature to a neural network?
I am working on building a model to classify the type of touch the user makes(Long Press, Left Swipe, Right swipe and so on). I have data with features that characterise the user's touch, like ...
- 131
1
vote
1
answer
442
views
Attention mechanism: Why apply multiple different transformations to obtain query, key, value
I have two questions about the structure of attention modules:
Since I work with imagery I will be talking about using convolutions on feature maps in order to obtain attention maps.
If we have a set ...
- 111
0
votes
0
answers
680
views
Computational complexity of a CNN network
In the following network, the convolution operations of convolutional blocks are performed by three 1-D kernels with the sizes 8, 5, and 3 respectively along with stride equal to 1. The final network ...
- 1
1
vote
1
answer
60
views
Expected behavior of adversarial attacks on deep NN?
I am trying adversarial attack (AA) for a simple CNNs. Instead of the clean image, my simple CNN is trained with attacked images as suggested by some papers. As the training goes on, I am not sure if ...
- 113
1
vote
1
answer
1k
views
What happens if there is no activation function in some layers of a neural network?
What if I don't apply an activation function on some layers in a neural network. How will it affect the model?
Take for instance the following code snippet:
...
3
votes
2
answers
3k
views
How to identify if 2 faces contain the same person?
I have got numerous frames and I've detected all the faces in all the frames using Retinaface. However I need to track the faces of people over frames.
For this purpose, I assumed I could try finding ...
- 131
2
votes
0
answers
36
views
How is the data labelled in order to train a region proposal network?
I don't get how the training of the RPN works. From the forward propagation, I have $W \times H \times k$ outputs from the RPN.
How is the training data labeled such that I can use the loss function ...
1
vote
3
answers
277
views
How can I implement 2D CNN filter with channelwise-bound kernel weights?
I would like to bind kernel parameters through channels/feature-maps for each filter. In a conv2d operation, each filter consists of HxWxC parameters I would like to have filters that have HxW ...
- 11
1
vote
0
answers
107
views
How to measure/estimate the energy consumption of CNN models during testing?
Does someone know a method to estimate / measure the total energy consumption during the test phase of the well-known CNN models? So with a tool or a power meter...
MIT has already a tool to estimate ...
- 11
1
vote
0
answers
44
views
Overcome caveats on using Deep Learning for faster inference on limited performance availability
I am working in the field of Machine Vision, where accuracy and performance both play a major factor in deciding the approach towards a problem. Traditional rule based approaches work quite well in ...
- 111
1
vote
0
answers
33
views
How to calibrate model's prediction given past images?
I want to predict how open is the mouth given a face image. It's a regression problem (0= mouth not open, 1=mouth completely open). And something between 0 and 1 is also allowed. ConvNet works fine ...
- 325
1
vote
0
answers
135
views
Automating browser actions using AI
I am at a very initial stage of my research so I will try to describe what I am trying to achieve:
I want to create an AI model which learns how to navigate the browser's component like clicking or ...
- 111
2
votes
0
answers
58
views
Creating Dataset for Image Classification
I want to develop a CNN model to identify 24 hand signs in American Sign Language. I created a custom dataset that contains 3000 images for each hand sign i.e. 72000 images in the entire dataset.
For ...
- 51
2
votes
1
answer
364
views
Can a fully convolutional network always return an image of the same size as the original?
I'm trying to perform a segmentation task on images of multiple sizes using fully convolutional neural networks.
Currently, I'm using EfficientNet as a feature extractor, and adding a deconvolution/...
- 137
1
vote
0
answers
45
views
Human Aggression Detection Community, Competition and dataset
I'm looking for a community or competition website related to human aggression detection using Deep Learning in a video.
Also, I'm looking for a dataset of human aggression activities.
Any ...
- 111
3
votes
2
answers
809
views
How to represent and work with the feature matrix for graph convolutional network (GCN) if the number of features for each node is different?
I have a question regarding features representation for graph convolutional neural network.
For my case, all nodes have a different number of features, and for now, I don't really understand how ...
- 41
1
vote
0
answers
26
views
Training dataset for convolutional neural network classification - will images captured on the ground be useful for training aerial imagery?
I am an agronomy graduate student looking to classify crops from weeds using convolutional neural networks (CNNs).
The basic idea that I am wanting to get into involves separating crops from weeds ...
- 129
2
votes
0
answers
92
views
Which neural network should I use to transform the pixels of a video overtime?
I want to train a network with video data and have it transform pixel values overtime on an input video. This is for an art project and does not need to be super elaborate, but the videos I want to ...
- 21
2
votes
1
answer
208
views
Is it possible to train a CNN to predict the dimensions of primitive objects from point clouds?
Is it possible to train a convolutional neural network (CNN) to predict the dimensions of primitive objects such as (spheres, cylinders, cuboids, etc.) from point clouds?
The input to the CNN will be ...
- 43
2
votes
1
answer
74
views
Should I use my redundant feature as an auxiliary output or as another input feature?
For example, given a face image, and you want to predict the gender. You also have age information for each person, should you feed the age information as input or should you use it as auxiliary ...
- 325
4
votes
1
answer
48
views
Image classification with an associated matrix
I have a dataset of images with 9 different classes. However, there are different categories with the same type of associated image and only can be differentiated with an associated matrix in my ...
- 41
1
vote
1
answer
715
views
What does an oscillating validation error curve represent?
I have been training my CNN for a bit now and, while both the training loss and the training error curves are going down during training, both my validation loss and my validation error curves are ...
- 61
3
votes
2
answers
108
views
How does one create a non-classifying CNN in order to gain information from images?
How do I program a neural network such that, when an image is inputted, the output is a numerical value that is not the probability of the image being a certain class? In other words, a CNN that doesn'...
- 31
2
votes
0
answers
68
views
How to train and update weights of filters
I have some problems with training CNN :(
For example:
Input 6x6x3, 1 core 3x3x3, output = 4x4x1 => pool: 2x2x1
By backpropagation I calculated deltas for output.
This tutor and other tutors are ...
- 21
2
votes
0
answers
29
views
How do I recover the 3D structure of a layer after a fully-connected layer?
I want to implement a CNN, but I want to explore what happens when my first layer is a fully-connected one. I still want to use convolutions, of course, but I want to apply them after the first layer. ...
- 211
0
votes
1
answer
104
views
Use deep learning to rank video scenes
I'm new to machine learning and especially, deep learning. Given a video (and it's subtitle), I need to generate a 10-second summary out of this video. How can I use ML and DL to produce the most ...
- 983
5
votes
1
answer
2k
views
What parameters can be tweaked to avoid a generator or discriminator loss collapsing to zero when training a DC-GAN?
Sometimes when I am training a DC-GAN on an image dataset, similar to the DC-GAN PyTorch example (https://pytorch.org/tutorials/beginner/dcgan_faces_tutorial.html), either the Generator or ...
- 51
3
votes
1
answer
282
views
What is the purpose and benefit of applying CNN to a graph?
I'm new to the graph convolution network. I wonder what is the main purpose of applying data with graph structure to CNN?
- 179
2
votes
0
answers
401
views
Super Resolution on text documents
I want to implement super-resolution and deblurring on images from text documents. Which is the best approach? Are there any Git-hub links which will help me to start? I am new to the field. Any help ...
- 21
1
vote
1
answer
227
views
Does changing the order of the convolution layers in a CNN have any impact?
Could changing the order of convolution layers in a CNN improve accuracy or training time?
- 35
2
votes
1
answer
71
views
How to reduce over-fitting on training set?
Currently I'm feeding spectrogram of audio to the CNN with 3 convolution.
Each convolution is followed by a max pool of filter size 2.
First -> 5x5x4
Second - > 5x5x8
Third - > 5x5x16
and final ...
- 21
14
votes
1
answer
17k
views
How can the convolution operation be implemented as a matrix multiplication?
How can the convolution operation used by CNNs be implemented as a matrix-vector multiplication? We often think of the convolution operation in CNNs as a kernel that slides across the input. However, ...
- 41.4k
9
votes
2
answers
12k
views
What is the concept of channels in CNNs?
I am trying to understand what channels mean in convolutional neural networks. When working with grayscale and colored images, I understand that the number of channels is set to 1 and 3 (in the first ...
- 321
1
vote
2
answers
1k
views
How to get a binary output from a Siamese Neural Network
I'm trying to train a Siamese network to check if two images are similar. My implementation is based on this. I find the Euclidian distance of the feature vectors(the final flattened layer of my CNN) ...
