Questions tagged [architecture]

For questions related to the architecture of AI models, e.g. the architecture of neural networks.

30 questions with no upvoted or accepted answers
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How do neural network topologies affect GPU/TPU acceleration?

I was thinking about different neural network topologies for some applications. However, I am not sure how this would affect the efficiency of hardware acceleration using GPU/TPU/some other chip. If, ...
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301 views

Get the position of an object, out of an image

I have some images with a fixed background and a single object on them which is placed, in each image, at a different position on that background. I want to find a way to extract, in an unsupervised ...
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1answer
96 views

Which ANN structure to use?

Let $\mathcal{S}$ be the training input data set where each input $u^i \in \mathcal{S}$ has $d$ features. I want to design a ANN so that the cost function below is minimized (the sum of square of ...
3
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1answer
100 views

What's the difference between architectures and backbones?

In the paper "ForestNet: Classifying Drivers of Deforestation in Indonesia using Deep Learning on Satellite Imagery", the authors talk about using: Feature Pyramid Networks (as the ...
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0answers
32 views

Merge two different CNN models into one

I have 2 different models with each model doing a separate function and have been trained with different weights. Is there any way I can merge these two models to get a single model. If it can be ...
2
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1answer
98 views

Can you explain me this CNN architecture?

I am starting to get my head around convolutional neural networks, and I have been working with the CIFAR-10 dataset and some research papers that used it. In one of these papers, they mention a ...
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2answers
2k views

What is the exact output of the Inception ResNet V2's feature extraction layer?

I am working with the Inception ResNet V2 model, pre-trained with ImageNet, for face recognition. However, I'm so confused about what the exact output of the feature extraction layer (i.e. the layer ...
2
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0answers
39 views

Multi-field text input for LSTM

I'm using LSTM to categorize medium-sized pieces of text. Each item to be categorized has several free-form text fields, in addition to several categorical fields. What is the best approach to using ...
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24 views

Is Hebbian learning the progenitor of AI?

Hebb's postulate attempts to explain associative learning via the processes of sampling (using sensors), emitting responses and receiving feedback. This is a form of control orientated architecture ...
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27 views

How to learn transition type in a 1-hour extended DJ Mix?

How would you design a model which learns the transitions in a given 1-hour DJ Mix? To be specific, the model should be able to learn transitions, specify the occurring time and the type (Crossfade, ...
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0answers
29 views

Under what circumstances is a fully connected layer similar to PCA?

I am reading this paper on image retrieval where the goal is to train a network that produces highly discriminative descriptors (aka embeddings) for input images. If you are familiar with facial ...
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40 views

Are there regularisation methods related only to architecture of the CNNs?

Are there any methods of regularisation of deep neural networks, particularly CNNs (or generally ANN but that will also work on CNNs) that are related only to the network's architecture and not the ...
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25 views

What exactly are deep learning primitives?

I came across the concept of "deep learning primitives" from the Nvidia talk Jetson AGX Xavier New Era Autonomous Machines (on slide 44). There doesn't seem to be a lot of articles in the ...
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41 views

How can one be sure that a particular neural network architecture would work?

Traditionally, when working with tabular data, one can be sure(or at least know) that a model works because the included features could explain a target variable, say "Price of a ticket" ...
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1answer
95 views

Should batch-normalization/dropout/activation-function layers be used after the last fully connected layer?

I am using the following architechture: 3*(fully connected -> batch normalization -> relu -> dropout) -> fully connected Should I add the ...
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2answers
47 views

Heavily mixing signal differentiation from Open Set of backgrounds via CNN

To whomever can help out, I appreciate it. I am currently attempting to detect a signal from background noise. The signal is pretty well known but the background has a lotttt of variability. I've ...
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0answers
44 views

Using U-NET for image semantic segmentation

I'm getting literally crazy trying to understand how U-NET works. Maybe it is very easy, but I'm stuck (and I have a terrible headache). So, I need your help. I'm going to segment MRI to find white ...
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0answers
14 views

Can Grad CAM feature maps be used for Training?

I am trying to recreate the architecture of the following paper: https://arxiv.org/pdf/1807.03058.pdf Can someone help me in explaining how are the feature maps coming out of the output of GradCam ...
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32 views

Neural Network training on one example to try overfitting leads to strange predictions

tldr; if I train the network on 1 training example, the outcome sometimes makes no sense at all, sometimes is as expected. If I train it on more examples and higher iterations, the network, which ...
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0answers
46 views

Is there data available about successful neural network architectures?

I am curious to if there is data available for MLP architectures in use today, their initial architecture, the steps that were taken to improve the architecture to an acceptable state and what the ...
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0answers
28 views

AlphaZero value at root node not being affected by training

I have written my own AlphaZero implementation and started training it recently. Problem is, I am 99% sure there is a mistake and I do not know how to tackle this, since I cannot explain it. I am new ...
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24 views

Architecture and Use of Different Algorithms for Health Goal Feedback

I wanted to get some opinions from the community for a certain problem that I will be approaching. The problem is to provide feedback to a user based on a image of the upper male torso. The image ...
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0answers
79 views

Algorithms that connect neurons to previous layers as well as next

Are there any algorithms, or any evidence to decide or to suggest it would be better to connect a neuron node in a layer l, in a neural network to particular nodes ...
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22 views

Do deep learning researchers generally visualize intermediate steps?

Many researchers in deep learning research come up with new architectures. The architectures are (just) combinations of few existing layers. Along with their mathematical intuition, in general, do ...
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14 views

Are there resources to learn what architectures are suited to which tasks?

I am very new to ANN, and haven't built the intuition yet. The problem I'm working on needs to process ~405 integers. The output should be a single number. Where can I find reading material about ...
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31 views

How to train feedforward network to recognize images?

Context I'm trying to create network for digits recognition. All digits are the same font and size of 40x40. I know that I can use feedforward network or CNN. I'd like to use the first one. Issue I ...
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12 views

Things to consider while adding custom function to generator output in GAN

I am training a GAN model (DCGAN) to generate 128x128 images. Now, I wish to add a function which will take the generator output, perform some pre-defined operations on it, and return the modified ...
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94 views

Understanding Stable Baselines Custom Policies

I'm trying to understand the structure of the custom recurrent policy introduced in the documentation of the Stable Baselines: How exactly is the Lstm NN constructed? (check code below) From what I ...
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1answer
44 views

How to use a NN for seq2seq tasks?

I am trying to make a NN(probably with dense layers) to map a specific input to a specific output (or basically sequence2sequence). I want the model to learn the relation between the sequences and ...
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21 views

The convolutional network architectures with enhanced invariance

It is well known, that CNN have advantage with respect to the Dense neural networks in the image classification and other pattern recognition tasks, because they have a translationall invariance built ...