Questions tagged [deep-network]

For questions about deep neural networks (DNNs), neural networks with multiple hidden layers between the input and output layer.

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69
votes
10answers
5k views

How is it possible that deep neural networks are so easily fooled?

The following page/study demonstrates that the deep neural networks are easily fooled by giving high confidence predictions for unrecognisable images, e.g. How this is possible? Can you please ...
39
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5answers
2k views

What is fuzzy logic?

I'm new to A.I. and I'd like to know in simple words, what is the fuzzy logic concept? How does it help, and when is it used?
29
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4answers
925 views

How to find the optimal number of neurons per layer?

When you're writing your algorithm, how do you know how many neurons you need per single layer? Are there any methods for finding the optimal number of them, or is it a rule of thumb?
25
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2answers
950 views

How is a deep neural network different from other neural networks?

How is a neural network having the "deep" adjective actually distinguished from other similar networks?
21
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4answers
335 views

Is the pattern recognition capability of CNNs limited to image processing?

Can a Convolutional Neural Network be used for pattern recognition in a problem domain where there are no pre-existing images, say by representing abstract data graphically? Would that always be less ...
14
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2answers
1k views

What's the main concept behind Capsule Networks? [duplicate]

As you might know, Capsule Networks have been recently introduced by Hinton. There also have been several heads up within his talks. As expected, the paper elaborates on the idea way theoretically! ...
12
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2answers
608 views

Should deep residual networks be viewed as an ensemble of networks?

The question is about the architecture of Deep Residual Networks (ResNets). The model that won the 1-st places at "Large Scale Visual Recognition Challenge 2015" (ILSVRC2015) in all five main tracks: ...
11
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5answers
2k views

Why are deep neural networks and deep learning insufficient to achieve general intelligence?

Everything related to Deep Learning (DL) and deep(er) networks seems "successful", at least progressing very fast, and cultivating the belief that AGI is at reach. This is popular imagination. DL is a ...
10
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4answers
1k views

What is the “dropout” technique?

What purpose does the "dropout" method serve and how does it improve the overall performance of the neural network?
10
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1answer
174 views

What kind of problems require more than 2 hidden layers?

I've read that the most of the problems can be solved with 1-2 hidden layers. How do you know you need more than 2? For what kind of problems you would need them (give me an example)?
9
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1answer
324 views

How much of a problem is white noise for the real-world usage of a DNN?

I read that deep neural networks can be relatively easily fooled (link) to give high confidence in recognition of synthetic/artificial images that are completely (or at least mostly) out of the ...
8
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3answers
180 views

What is a deep neural network?

What is the definition of a deep neural network? Why are they so popular or important?
8
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2answers
692 views

What's the difference between hyperbolic tangent and sigmoid neurons?

Two common activation functions used in deep learning are the hyperbolic tangent function and the sigmoid activation function. I understand that the hyperbolic tangent is just a rescaling and ...
6
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4answers
1k views

Which machine learning algorithm is used in self-driving cars?

Which deep neural network is used in Google's driverless cars to analyze the surroundings? Is this information open to the public?
6
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3answers
260 views

Has anybody tried unsupervised deep learning from youtube videos?

YouTube has a huge amount of videos, many of which also containing various spoken languages. This would presumably provide something like the data that a "challenged" baby would experience - "...
6
votes
1answer
145 views

Has any research been done on DNN Music?

DNNs are typically used to classify things (of course) but can we let them go wild with sounds and then tell them if we think it sounds good or not? I'd like to think after a training class has been ...
6
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2answers
176 views

Neural networks efficiently solve traveling salesmen problems?

I occasionally read papers that show neural networks solving traveling salesmen problems and multi traveling salesmen problems efficiently? 1) Is there any analysis of the meaning of efficiency of ...
5
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2answers
241 views

Is it possible to construct an ANN that is more efficient than the human brain?

Intelligence ... changes based on the environment and situation Human are now inventing machines exhibiting some features of their own Intelligence. There appears to be a possibility that, in the ...
5
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2answers
222 views

What do neural connection weights represent 'conceptually'?

I understand how Neural Networks work and have studied its theory well. My question is at the intricacies of Deep Neural networks and perhaps is a bit beyond common understanding (as I have been told (...
5
votes
1answer
671 views

Precise localization and characterization of rudimentary shapes with neural networks

I understand that there are flavors of (convolutional) neural networks that are useful for object localization and detection tasks of reasonable difficulty. In all of the examples I have seen so far, ...
5
votes
1answer
88 views

How can neural networks that extract many features be fooled by adversarial images?

I have been reading a bit about networks where deep layers able to deal with a bunch of features (be it edges, colours, whatever). I am wondering: how can possibly a network based on this '...
4
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2answers
323 views

Iteratively and adaptively increasing the network size during training

For an experiment that I'm working on, I want to train a deep network in a special way. I want to initialize and train a small network first, then, in a specific way, I want to increase network depth ...
4
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1answer
825 views

Suitable reward function for trading buy and sell orders

I am working to build an deep reinforcement learning agent which can place orders (i.e. limit buy and limit sell orders). The actions are ...
4
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1answer
51 views

How can I use one neural network for both players in Alpha Zero (Connect 4)?

First of all, it is great to have found this community! I am currently implementing my own Alpha Zero clone on Connect4. However, I have a mental barrier I cannot overcome. How can I use one neural ...
4
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1answer
140 views

Regression with more than one output, neural network

Currently in my country, there is a system in which certain groups of researchers upload information on products of scientific interest, such as research articles, books, patents, software, among ...
4
votes
1answer
624 views

Using crowdsourcing for deep learning

Most companies dealing with deep learning (automotive - Comma.ai, Mobileye, various automakers etc.) do collect large amounts of data to learn from and then use lots of computational power to train a ...
4
votes
1answer
179 views

What can be done to correct for sampling bias introduced from (noisy) training data while training a DNN?

The obvious solution is to ensure that the training data is balanced - but in my particular case that is impossible. What corrections can one perform in such a scenario? I know that my training data ...
4
votes
1answer
2k views

Does it make sense to use batch normalization in deep (stacked) or sparse auto-encoders?

Does it make sense to use batch normalization in deep (stacked) or sparse auto-encoders? I cannot find any resources for that. Is it safe to assume that, since it works for other DNNs, it will also ...
4
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3answers
228 views

What is the most time consuming part of training deep networks?

Deep networks notoriously take a long time to train. What is the most time consuming aspect of training them? Is it the matrix multiplications? Is it the forward pass? Is it some component of the ...
4
votes
2answers
34 views

What kind of output should be used for predicting angles in DNNs?

I am building a model which predicts angles as output. What are the different kinds of outputs that can be used to predict angles? For example, output the angle in radians cyclic nature of the ...
4
votes
0answers
420 views

Sparsity constraint in a deep autoencoder

Is there any way and any reason why one would introduce a sparsity constraint on a deep autoencoder? In particular, in deep autoencoders the first layer often has more units than the dimensionality ...
3
votes
2answers
213 views

Are there any learning algorithms as powerful as “deep” architectures?

This article suggests that deep learning is not designed to produce the universal algorithm and cannot be used to create such a complex systems. First of all it requires huge amounts of computing ...
3
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2answers
870 views

Is there any proof based literature out there on neural networks?

Is there any mathematical proof (like in proof of a theorem) based literature out there on neural networks ? Everything is empirically based but no math proof for instance on why certain parameters ...
3
votes
1answer
258 views

How can generalization error be estimated?

How would you estimate the generalisation error? What are the methods of achieving this?
3
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4answers
209 views

What could an oscillating training loss curve represent?

I tried to create a simple model that receives an $80 \times 130$ pixel image. I only had 35 images and 10 test images. I trained this model for a binary classification task. The architecture of the ...
3
votes
2answers
74 views

AI that knows when its being spoken to

I am trying to make a artificial intelligent agent that is kind of like jarvis from Iron man however much less complex. One thing I want to have is I want my AI to be able to determine if I am talking ...
3
votes
1answer
62 views

What are the methods of optimizing overfitted models?

I'm worrying that my network has become too complex. I don't want to end up with half of the network doing nothing but just take up space and resources. So, what are the techniques for detecting and ...
3
votes
1answer
106 views

Alpha zero before move 8

The Alpha zero paper says that the The first set of features are repeated for each position in a T = 8-step history. So what happens before the first 8 moves? Do they just repeat the starting position?...
3
votes
2answers
155 views

Should the actor or actor-target model be used to make predictions after training is complete (DDPG)?

The situation I am referring to the paper T. P. Lillicrap et al, "Continuous control with deep reinforcement learning" where they discuss deep learning in the context of continuous action spaces ("...
3
votes
1answer
61 views

Can Google's patented ML algorithms be used commercially?

I just find that Google patents some of the widely used machine learning algorithms. For example: System and method for addressing overfitting in a neural network (Dropout?) Processing images using ...
3
votes
1answer
145 views

Can you learn parameters in nonlinear function?

In the paper Nonlinear Interference Mitigation via Deep Neural Networks, the the following network is illustrated. The network structure is The network parameters are $\theta = \{W_1^{1},...,W_1^{l-...
3
votes
2answers
177 views

How to build my own dataset and model for an LSTM neural network

I have a sort of mathematical problem and I'm not sure which model I should choose to make an LSTM neural network. Currently in my country, there is a system in which certain groups of researchers ...
3
votes
1answer
654 views

Dataset containing images of varying dimensions and orientations

I am new to deep learning. I have a dataset of images of varying dimensions of a certain object. A few images of the object are also in varying orientations. The objective is to learn the features ...
3
votes
1answer
39 views

Is batch normalization not suitable for non-gaussian input?

I generate some non-Gaussian data, and use two kinds of DNN models, one with BN and the other without BN. I find that the model DNN with BN can't predict well. The codes is shown as follow: <...
3
votes
1answer
75 views

Is it possible to create a decompiler using AI?

I am trying to decode a compiled file to source code and I am failing. I want to know whether an AI based decompilation is possible for a compiled files? Is it possible to create a decompiler using a ...
2
votes
2answers
98 views

what will i be able to do in the end of AI: modern approach? [closed]

i just started the book and i was wondering , what will i be able to do in AI by the end of the book ? and more particularly, what is my position with Reinforcement Learning, deep neural networks and ...
2
votes
1answer
379 views

Deep Q-Learning poor convergence on Stochastic Environment

I'm trying to implement a Deep Q-network in Keras/TF that learns to play Minesweeper (our stochastic environment). I have noticed that the agent learns to play the game pretty well with both small and ...
2
votes
3answers
1k views

What activation function is not used at the final layer of super resolution neural models?

I'm trying to implement some Image super-resolution models on medical images. After reading a set of papers, I found that none of the existing models use any activation layer for the last layer. What'...
2
votes
1answer
303 views

How does deepmind's Atari game AI work?

I know that deepmind used deep Q learning (DQN) for its Atari game AI. It used a conv neural network (CNN) to approximate Q(s,a) from pixels instead of from a Q-...
2
votes
1answer
170 views

Elon musk's comment on “non-benign AI scenarios”

I watched a youtube clip of Elon Musk talking about his view on the future of AI. He gave two examples. One of the examples was a benign scenario and the other example was a non benign scenario where ...