Questions tagged [deep-learning]

For questions related to deep learning, which refers to a subset of machine learning methods based on artificial neural networks (ANNs) with multiple hidden layers. The adjective deep thus refers to the number of layers of the ANNs. The expression deep learning was apparently introduced (although not in the context of machine learning or ANNs) in 1986 by Rina Dechter in the paper "Learning while searching in constraint-satisfaction-problems".

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24 views

What is the difference between using a backbone architecture and transfer learning?

I'm super new to deep learning and computer vision, so this question may sound dumb. In this link (https://github.com/GeorgeSeif/Semantic-Segmentation-Suite), there are pre-trained models (e.g., ...
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1answer
45 views

Can a neural network learn to predict a number given a binarized image of a rectangle?

Let's assume that we have a regression problem. Our input is just binarized image that contains a single rectangle and we want to predict just a float number. Actually, this floating-point number ...
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62 views

Why does reinforcement learning using a non-linear function approximator diverge when using strongly correlated data as input?

While reading the DQN paper, I found that randomly selecting and learning samples reduced divergence in RL using a non-linear function approximator (e.g a neural network). So why does Reinforcement ...
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1answer
81 views

How many layers exists in my neural network?

I have a neural network model defined as below. How many layers exist there? Not sure which ones to count when we are asked about the number. ...
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0answers
35 views

How can I implement derivative of softmax function for matrices in Python?

I have trouble understanding how to implement derivative of softmax function. Here is what I tried: ...
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1answer
23 views

How to process data in a data stream for a LSTM

How can a data stream for a RNN (LSTM) be handled, when the stream contains data sets belonging to different prediction classes? Training phase: I have trained a LSTM to predict a class out of a ...
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17 views

How can we combine different deep learning models?

I know that ensembles can be made by combining sklearn models with a VotingClassifier, but is it possible to combine different deep learning models? Will I have to make something similar to Voting ...
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0answers
19 views

Efficient implementation of seperable convolution in tensorflow [closed]

It seems like the native implementation of separable convolution in tensorflow is not efficient. https://github.com/tensorflow/tensorflow/issues/12940 Is anyone aware how can we get an efficient ...
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1answer
31 views

Where can I upload a large photo database for public access? [closed]

I am applying for a grant, and one of the tasks we are seeking funding for is to make a large image database publicly available for users to train artificial intelligence (convolutional neural network)...
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14 views

Getting started with creating a general AI based on textual and then image based data?

I have a pool of knowledge that I want to mine for information and allow an AI to deduce likely conclusions from this information. My goal is to give the AI a set of textual data that is rated on a ...
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1answer
33 views

In deep learning, is it possible to use discontinuous activation functions?

In deep learning, is it possible to use discontinuous activation functions (e.g. one with jump discontinuity)? (My guess : for example, ReLU is non-differentiable at a single point, but it still has ...
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13 views

Feeding a neural network with single slices of a 3D matrix

I'm working on a neural network wich "slices" a 1080p image in many layers. It takes a 1080p image as an input and produces a 1080*1920*n matrix: basically I add a z value to each pixel rapresenting ...
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2answers
48 views

Why does the bias need to be a vector in a neural network?

I am learning to use tensorflow.js. I am also using the tfvis library to print information about the neural net to the web browser. When I create a create a dense neural net with a layer with 5 ...
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22 views

How to use Before / After images to train a model

I am trying to create a model that can clean pictures of noise, blur, high luminosity etc, but I do not know how to do that. I have tried to search for it a lot, and I couldn't find anything that ...
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31 views

Can Bert be used to extract embedding for large categorical features?

I've lot of training data points (i.e in millions) and I've around few features but the issue with that is all the features are categorical data with 1 million+ categories in each. So, I couldn't use ...
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26 views

How can I train a Deep Learning model using degraded photos and their clean version to correct photos

I have 5000 degraded pictures ( pixelated, blurry, too much luminosity ... ) and their clean versions, and I would like to train a model so that it can predict how to correct future pictures. I've ...
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2answers
148 views

Can we get the inverse of the function that a neural network represents?

I was wondering if it's possible to get the inverse of a neural network. If we view a NN as a function, can we obtain its inverse? I tried to build a simple MNIST architecture, with the input of (784,...
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1answer
49 views

How is back-propagation useful in neural networks?

I am reading about backpropagation and I wonder why I have to backpropagate. For example, I would update the network by randomly choosing a weight to change, $w$. I would have $X$ and $y$. Then, I ...
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1answer
52 views

How does the generator in GAN's work?

After reading a lot of articles (for instance, this one - https://developers.google.com/machine-learning/gan/generator), I've been wondering: how does the generator in GAN's work? What is the input ...
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1answer
28 views

Why is this deep Q agent constantly learning just one action?

I'm trying to implement deep q learning in the OpenAI's gym "Taxi-v3" environment. But my agent only learns to do one action in every state. What am I doning wrong? Here is the Github repository with ...
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24 views

What activation functions are better for what problems?

I’ve been reading about neural network architectures. In certain cases, people say that the sigmoid "more accurately reflects real-life" and, in other cases, functions like hard limits reflect "the ...
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35 views

How can I compare EEG data with accelerometer data in 1 algorithm?

I have frequency EEG data from fall and non-fall events and I am trying to incorporate it with accelerometer data that was collected at the same time. One approach is, of course, to use two separate ...
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18 views

Is there any paper that uses truncated neural networks?

Recently, I've found good success in truncated neural networks ie functions of the form $$ g=f1_{[-M,M]^d}, $$ where $f:\mathbb{R}^d\to\mathbb{R}^n$ is a feed-forward neural network and $1_{[-M,M]^d}$ ...
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1answer
21 views

What is the difference between batches in deep Q learning and supervised learning?

How is the batch loss calculated in both DQNs and simple classifiers? From what I understood, in a classifier, a common method is that you sample a mini-batch, calculate the loss for every example, ...
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1answer
34 views

Why does PyTorch use a different formula for the cross-entropy?

In my understanding, the formula to calculate the cross-entropy is $$ H(p,q) = - \sum p_i \log(q_i) $$ But in PyTorch nn.CrossEntropyLoss is calculated using this ...
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3answers
127 views

What's the function that SGD takes to calculate the gradient?

I'm struggling to fully understand the stochastic gradient descent algorithm. I know that gradient descent allows you to find the local minimum of a function. What I don't know is what exactly that ...
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0answers
18 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 ...
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1answer
38 views

How can a DQN backpropagate its loss?

I'm currently trying to take the next step in deep learning. I managed so far to write my own basic feed-forward network in python without any frameworks (just numpy and pandas), so I think I ...
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2answers
90 views

Why are traditional ML models still used over deep neural networks?

I'm still on my first steps in the Data Science field. I played with some DL frameworks, like TensorFlow (pure) and Keras (on top) before, and know a little bit of some "classic machine learning" ...
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0answers
42 views

Why don't the neural networks inside LSTM cells contain hidden layers?

I watched a video explaining how LSTM cells have very rudimentary feed-forward neural networks, basically a 2 layer input-output with no hidden layers. Why don't LSTM cells have more complex neural ...
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9 views

Can a trained Vid2Vid model be run on AMDs Ryzen 2700x with 32GB of RAM?

I know that training deep neural networks (DNNs) takes a lot of computational resources. This is, of course, just a generalized statement. Different networks require different resources. One that I ...
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0answers
48 views

Why isn't there a model playing FPS like CoD or Battlefield already existing?

Assuming we had an unlimited time to train a model and a very powerful machine to use our model in real-time (hello quantum computer), I'd like to know why no one could achieve to build an AI able to ...
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32 views

How to Layer based Feature extraction?

I have read that in deep networks you can engineer each layer for a particular purpose with regards to feature learning. I'm wondering how that is actually done and how it is trained? In addition ...
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28 views

What's the mathematical relationship between number of trainable parameters and size of training set?

Let's say that I have a pre-trained model where the training set used to pretrain the model is very different from my training set. Let's say I unfreeze layers that have X trainable parameters. What ...
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0answers
19 views

What's the difference between semi-supervised VAEs and conditional VAEs?

Can someone explain the difference? I'm assuming the difference is just that the neural nets representing the encoder and decoder are trained in a semi-supervised manner in semi-supervised VAE, which ...
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1answer
215 views

What is the mathematical definition of an activation function?

What is the mathematical definition of an activation function to be used in a neural network? So far I did not find a precise one, summarizing which criterions (e.g. monotonicity, differentiability, ...
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22 views
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1answer
69 views

What is a cascaded convolutional neural network?

For a project I am doing, I found the paper Face Alignment in Full Pose Range: A 3D Total Solution. It is using a cascaded convolutional neural network, but I wasn't able to find the original paper ...
4
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1answer
39 views

Can training a model on a dataset composed by real images and drawings hurt the training process of a real-world application model?

I'm training a multi-label classifier that's supposed to be tested on underwater images. I'm wondering if feeding the model drawings of a certain class plus real images can affect the results badly. ...
4
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2answers
472 views

Effect of batch size and number of GPUs on model accuracy

I have a data set which was split using a fixed random seed and I am going to use 80% of data for training and rest on validation. Here are my GPU and batch size configurations use ...
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0answers
30 views

How can I do hyperparameter optimization for a CNN-LSTM neural network?

I have built a CNN-LSTM neural network with 2 inputs and 2 outputs in Keras. I trained the network with model.fit_generator() (and not ...
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0answers
32 views

How can I extract the reason of the legal compensation from a court report?

I'm working on a project (court-related). At a certain point, I have to extract the reason of the legal compensation. For instance, let's take these sentences (from a court report) Order mister X ...
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2answers
60 views

Does summing up word vectors destroy their meaning?

For example, I have a paragraph which I want to classify in a binary manner. But because the inputs have to have a fixed length, I need to ensure that every paragraph is represented by a uniform ...
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0answers
39 views

Is it a good idea to apply reinforcement learning to dots and boxes? [closed]

I am currently in college, and trying to learn reinforcement learning by myself. My primary goal is building an agent that play games such as dots and boxes. I have sufficient highschool maths ...
3
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1answer
88 views

How to formalize learning in terms of information theory?

Consider the following game on a MNIST dataset: There are 60000 images. You can pick any 1000 images and train your Neural Network without access to the rest of images. Your final result is ...
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1answer
57 views

Can we calculate mean recall and precision

I'm evaluating the accuracy in detecting objects for my image data set using three deep learning algorithms. I have selected a sample of 30 images. To measure the accuracy, I manually count the number ...
2
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1answer
25 views

How can a system recognize if two strings have the same or similar meaning?

How can a system recognize if two strings have the same or similar meaning? For example, consider the following two strings Wikipedia provides good information. Wikipedia is a good source of ...
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0answers
24 views

Rarely predict minority class imbalanced datasets

I have a dataset in which class A has 99.8%, class B 0.1% and class C 0.1%. If I train my model on this dataset, it predicts always class A. If I do oversampling, it predicts the classes evenly. I ...
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1answer
45 views

Are CNN, LSTM, GRU and transformer AGI or computational intelligence tools?

Will CNN, LSTM, GRU and transformer be better classified as Computational Intelligence (CI) tools or Artificial General Intelligence (AGI) tools? The term CI arose back when some codes like neural ...
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2answers
49 views

Is there any classifier that works best in general for NLP based projects?

I've written a program to analyse a given piece of text from a website and make conclusary classifications as to its validity. The code basically vectorizes the description (taken from the HTML of a ...

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