Unanswered 'architecture' Questions

6

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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, ...

asked Sep 23 '19 at 14:05

user2316602

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3

votes

1answer

103 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 ...

neural-networks machine-learning deep-neural-networks architecture

asked May 1 at 20:57

user3489173

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3

votes

1answer

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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 ...

deep-learning convolutional-neural-networks comparison terminology architecture

asked Dec 18 '20 at 13:57

codinggirl123

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votes

0answers

36 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 ...

neural-networks convolutional-neural-networks computer-vision architecture

asked May 11 '20 at 13:08

Nautatava Navlakha

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votes

1answer

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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 ...

neural-networks deep-learning convolutional-neural-networks architecture

asked May 10 '20 at 13:01

SanMu

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votes

2answers

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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 ...

deep-learning convolutional-neural-networks architecture inception image-net

asked Jul 29 '19 at 11:25

magicww

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votes

0answers

44 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 ...

natural-language-processing long-short-term-memory hidden-layers architecture

asked Apr 1 '19 at 3:39

Derek Hans

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votes

0answers

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 ...

machine-learning architecture biology

asked Nov 19 '18 at 14:37

Amna Rajpoot

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vote

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28 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, ...

machine-learning deep-learning unsupervised-learning architecture

asked Jun 6 at 18:30

Cactuser

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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 ...

architecture facial-recognition principal-component-analysis content-based-image-retrieval

asked May 10 at 15:28

Alexander Soare

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vote

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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 ...

neural-networks deep-learning convolutional-neural-networks architecture regularization

asked Mar 15 at 19:01

Makintosz

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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 ...

deep-learning architecture

asked Nov 5 '20 at 15:47

Frank

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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" ...

convolutional-neural-networks ai-design recurrent-neural-networks deep-neural-networks architecture

asked Jul 20 '20 at 7:36

Naveen Reddy Marthala

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vote

1answer

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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 ...

neural-networks deep-learning architecture

asked Apr 27 '20 at 11:02

Gilad Deutsch

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1

vote

2answers

50 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 ...

convolutional-neural-networks keras architecture

asked Apr 17 '20 at 0:58

Mecho Engineer

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vote

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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 ...

convolutional-neural-networks objective-functions architecture image-segmentation u-net

asked Dec 11 '19 at 15:39

VansFannel

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vote

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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 ...

convolutional-neural-networks computer-vision gradient-descent architecture pytorch

asked Nov 28 '19 at 13:12

Amy

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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 ...

neural-networks deep-learning architecture overfitting

asked Sep 16 '19 at 11:51

Leviathan

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vote

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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 ...

neural-networks research architecture multilayer-perceptron

asked Sep 6 '19 at 5:37

SandMan

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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 ...

neural-networks ai-design alphazero architecture

asked Sep 1 '19 at 20:30

Leviathan

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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 ...

machine-learning architecture model-based-methods

asked Apr 5 '19 at 3:26

Invic18

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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 ...

neural-networks machine-learning architecture

asked Dec 31 '17 at 19:14

benbyford

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How to select dimensions of kernel and stride for pooling?

Consider a tensor of size $512 \times 512$. I need to reduce it to $32 \times 32$. There are several ways to do it. There are a lot of possibilities. Each possibility has its own kernel dimensions and ...

architecture filters pooling dimensionality downsampling

asked Oct 15 at 0:51

hanugm

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25 views

Rebirth Architecture for Deep Learning

Intro: Lots of Machine Learning methods are inspired Biology, Nature, Physics, Neurology... I just thought of a Deep Learning approach inspired on religion: Rebirth Network Some eastern religions ...

deep-learning philosophy deep-neural-networks architecture

asked Aug 27 at 6:51

Andre Goulart

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10 views

How to get Attention Maps from Attention Gates in Attention UNET?

Contex I have Attention UNET for image segmentation. I use it for humans segmentation. Question Everything works fine. I want to get attention maps from my network, so I could see what my UNET is ...

machine-learning attention architecture u-net

asked Aug 22 at 18:34

MASTER OF CODE

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19 views

Which Neural Network Topology to choose, are Transformers suitable?

I have a regression problem and I am not quite sure which architecture to choose. I never worked with transformers before, but I generally understand how they work and I think they might be suitable. ...

convolutional-neural-networks python datasets transformer architecture

asked Aug 19 at 7:20

Patrick Lehnen

1

0

votes

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24 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 ...

research architecture data-visualization

asked Jul 30 at 8:14

hanugm

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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 ...

machine-learning architecture

asked Jun 26 at 18:31

Tiago Chamba

1

0

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32 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 ...

machine-learning training image-recognition architecture

asked May 4 at 13:40

MASTER OF CODE

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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 ...

deep-learning generative-adversarial-networks pytorch architecture dc-gan

asked Apr 29 at 0:05

borodor

11 bronze badge

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109 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 ...

recurrent-neural-networks long-short-term-memory architecture

asked Dec 15 '20 at 20:47

HELP

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1answer

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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 ...

machine-learning deep-learning prediction pattern-recognition architecture

asked Sep 11 '20 at 12:39

neel g

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Questions tagged [architecture]

How do neural network topologies affect GPU/TPU acceleration?

Which ANN structure to use?

What's the difference between architectures and backbones?

Merge two different CNN models into one

Can you explain me this CNN architecture?

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

Multi-field text input for LSTM

Is Hebbian learning the progenitor of AI?

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

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

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

What exactly are deep learning primitives?

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

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

Heavily mixing signal differentiation from Open Set of backgrounds via CNN

Using U-NET for image semantic segmentation

Can Grad CAM feature maps be used for Training?

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

Is there data available about successful neural network architectures?

AlphaZero value at root node not being affected by training

Architecture and Use of Different Algorithms for Health Goal Feedback

Algorithms that connect neurons to previous layers as well as next

How to select dimensions of kernel and stride for pooling?

Rebirth Architecture for Deep Learning

How to get Attention Maps from Attention Gates in Attention UNET?

Which Neural Network Topology to choose, are Transformers suitable?

Do deep learning researchers generally visualize intermediate steps?

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

How to train feedforward network to recognize images?

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

Understanding Stable Baselines Custom Policies

How to use a NN for seq2seq tasks?

Hot Network Questions

Questions tagged [architecture]

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