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".

Filter by
Sorted by
Tagged with
6
votes
4answers
435 views

What does deep learning offer with respect to standard machine learning?

I've been reading a lot about DL. I can understand to an extent how it works, in theory at least, and how it's technically different from conventional ML. But what I'm looking for is more of a "...
3
votes
1answer
543 views

Detect street and sidewalk surface in aerial imagery (neural network)

I would like to detect street and sidewalk surface in a very detailed (0.075m/pix) USGS High Resolution Orthoimagery which basically means image segmentation with two classes. Places in question are ...
2
votes
4answers
377 views

Training neural network for good taste in art

I'm a newbie in machine learning, so excuse me in advance). I have an idea to make NN that can estimate visual pleasantness of arbitrary image. Like you have a bunch of images that you like, you train ...
0
votes
2answers
7k views

Concatenate convolution layers with different strides in tensorflow.

I am trying to do an inception layer, but it only works if the convolution strides, pool strides and pool size are the same, otherwise I get an error in tf.concat that Dimesion 1 is not the same. ...
6
votes
3answers
646 views

Machine Learning hardware usage in embedded applications

I've been reading a lot about hardware development and implementation for AI/ML, mainly about Deep Learning, and I have a question about its usage. From what I understand, there are 2 stages for DL: ...
2
votes
1answer
111 views

Recognition of abbreviated text

I want to write a program that looks at abbreviated words, then figures out what the words are. For example, the abbreviation is "blk comp", and the translation is "black computer". In order to give ...
0
votes
1answer
140 views

Tensorboard problems

When trying to run tensorboard locally to show my logs with tensorboard --logdir logs/ it always shows nothing but the regular tensorboard menu options, such as ...
0
votes
3answers
3k views

SSD or YOLO on arm

Is it possible to run SSD or YOLO object detection on raspberry pi 3 for live object detection (2/4frames x second)? I've tried this SSD implementation but it takes 14 s per frame. Is there anything I ...
10
votes
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 ...
1
vote
1answer
403 views

Why do action recognition algorithms perform better on ucf101dataset than HMDB51 dataset?

If we look at state of the art accuracy on the UCF101 data set, it is around 93% whereas for the HMDB51 data set it is around 66%. I looked at both the data sets and both contain videos of similar ...
10
votes
1answer
345 views

AI that can generate programs

I have been looking into Viv an artificial intelligent agent in development. Based on what I understand, this AI can generate new code and execute it based on a query from the user. What I am curious ...
1
vote
0answers
95 views

Infer dependent variables to produce output aligned to trained data

Hypothetical example, say I wanted: P(gender,ethnicity|age,hair); so that the input would aligned to a trained dataset of: ...
2
votes
1answer
91 views

Can silicon based computers create A.I. per definition?

Can silicon based computers create A.I. per definition of what intelligence is? Or does silicon based computers only create human mimic? If silicon based computers only create human mimic, are human ...
3
votes
5answers
2k views

Is it a good idea to pay for an deep learning course? [closed]

I'm an artificial intelligence enthusiastic and I want to learn about it. I want to ask you what do you think about the Udacity nanodegree Deep Learning Nanodegree Foundation. I don't know if it is ...
4
votes
1answer
605 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 ...
3
votes
2answers
73 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 ...
5
votes
5answers
342 views

How would AI be able to self-examine?

As I see some cases of machine-learning based artificial intelligence, I often see they make critical mistakes when they face inexperienced situations. In our case, when we encounter totally new ...
5
votes
2answers
308 views

Feasibility of generating large images with a convnet

I've spent the past couple of months learning about neural networks, and am thinking of projects that would be fun to work on to cement my understanding of this tech. One thing that came to mind last ...
2
votes
0answers
102 views

Conversational agent,query [closed]

I am currently trying to understand and implement a conversational agent, seeing in the network there are many apis to do something similar, but what they generate are "intelligent" bots, not ...
2
votes
1answer
1k views

Making a simple ai like Jarvis

So I am looking to make an AI like jarvis. A perfect real life example of this type of system is the simple AI that Mark Zuckerberg has recently built. Here is a description on how his AI works. From ...
4
votes
4answers
374 views

Which methods or algorithms to develop a learning application?

I am creating a game application that will generate a new level based on the performance of the user in the previous level. The application is regarding language improvement, to be precise. Suppose ...
0
votes
2answers
201 views

Is it possible to train deep learning agent to pass a multiple-choice exam?

Is it possible to train an agent to take and pass a multiple-choice exam based on a digital version of a textbook for some area of study or curriculum? What would be involved in implementing this and ...
3
votes
1answer
601 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
0answers
85 views

boltzmann machine; from logistic function to boltzmann distribution [closed]

I'm trying to understand Boltzmann machines. Tutorials explain it with two formulas. Logistic function for the probability of single units: ...
2
votes
1answer
132 views

Network representation for Q-Learning in carrom

I am trying to build an agent to play carrom. The problem statement is roughly to estimate three parameters (normalized) : force angle of striker position of strike Since the state and action ...
2
votes
0answers
115 views

What resources are good for learning to program AI? [closed]

I know how to program. I've familiar with C++, Python, and Java, and I've known how to program for years now. I've experimented with genetic algorithms, but I want to go further. What resources should ...
29
votes
3answers
17k views

Why is Lisp such a good language for AI?

I've heard before from computer scientists and from researchers in the area of AI that that Lisp is a good language for research and development in artificial intelligence. Does this still apply, with ...
6
votes
3answers
762 views

Board/Card Game AI - Questions concerning state/action space - Deep Reinforcement Learning

Ok, I now know how a machine can learn to play to play Atari games (Breakout): Playing Atari with Reinforcement Learning With the same technique it is even possible to play FPS games (Doom): Playing ...
12
votes
2answers
1k views

How do generative adversarial networks work?

I am reading about generative adversarial networks (GANs) and I have some doubts regarding it. So far, I understand that in a GAN there are two different types of neural networks: one is generative ($...
9
votes
2answers
462 views

Was DeepMind's DQN Atari game learning simultaneous?

DeepMind state that their deep Q-network (DQN) was able to continually adapt its behavior while learning to play 49 Atari games. After learning all games with the same neural net, was the agent ...
12
votes
1answer
2k views

How would Deepmind's new “differentiable neural computer” scale?

Deepmind just published a paper about a "differentiable neural computer", which basically combines a neural network with a memory. The idea is to teach the neural network to create and recall useful ...
3
votes
3answers
472 views

AI becoming sentient plausibility?

In lots of sci-fi, it seems that AI becomes sentient (Terminator, Peter F Hamilton's SI (commonwealth saga), etc.) However, I'm interested in whether this is actually plausible, whether an AI could ...
5
votes
1answer
345 views

What is the most abstract concept learned by a deep neural network?

It seems that deep neural networks are making improvements largely because as we add nodes and connections, they are able to put together more and more abstract concepts. We know that, starting from ...
2
votes
3answers
3k views

When using neural networks to detect features in an image, how can locate that specific feature in the original image?

I understand how a neural network can be trained to recognise certain features in an image (faces, cars, ...), where the inputs are the image's pixels, and the output is a set of boolean values ...
41
votes
3answers
27k views

How can neural networks deal with varying input sizes?

As far as I can tell, neural networks have a fixed number of neurons in the input layer. If neural networks are used in a context like NLP, sentences or blocks of text of varying sizes are fed to a ...
11
votes
2answers
569 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: ...
8
votes
3answers
1k views

Do deep learning algorithms represent ensemble-based methods?

Shortly about deep learning (for reference): Deep learning is a branch of machine learning based on a set of algorithms that attempt to model high-level abstractions in data by using a deep ...
14
votes
3answers
948 views

Has anyone thought about making a neural network ask questions, instead of only answering them?

Most of the people is trying to answer question with a neural network. However, has anyone came up with some thoughts about how to make neural network ask questions, instead of answer questions? For ...
2
votes
1answer
296 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
86 views

Using feature learning for a medical text classification problem [closed]

I'm currently working with the CHILDES corpus trying to create a classifier that distinguishes children whom suffer from specific language impairment (SLI) from those who are typically developing (TD)....
14
votes
5answers
2k views

What is the difference between machine learning and deep learning?

Can someone explain to me the difference between machine learning and deep learning? Is it possible to learn deep learning without knowing machine learning?
0
votes
1answer
161 views

How does Wolfram's Image Identification Project work?

Wolfram Language Image Identification Project launched an Image Identify site demo which returns the top predicted tags for the photos. How does it work, briefly? I mean what type of learning vision ...
4
votes
1answer
86 views

How can artificial intelligence (including deep learning algorithms) find suspicious patterns in the body’s biochemistry?

It has been suggested that machine learning algorithms (also Watson) can help with finding disease in patient images and optimize scans. Also that deep learning algorithms show promise for every type ...
0
votes
2answers
377 views

Training network to detect spelling mistakes

I would like to know what kind of dataset I need (to prepare) for training the network to recognize the spelling mistakes in individual words for English text. Given the large database of words, ...
-2
votes
1answer
223 views

How many neurons would a network have after a training of 100k small images?

Is there any way to estimate how big the neural network would be after training session of 100,000 unlabeled images for unsupervised learning (like in STL-10 dataset: 96x96 pixels and color)? Not the ...
69
votes
8answers
11k views

Do scientists know what is happening inside artificial neural networks?

Do scientists or research experts know from the kitchen what is happening inside complex "deep" neural network with at least millions of connections firing at an instant? Do they understand the ...
3
votes
1answer
253 views

How do Google cars recognize the traffic signs?

The paper Multi-column Deep Neural Networks for Image Classification (pages 7-8) shows an attempt at recognizing the traffic signs, with lower error rates, by using multi-column deep neural networks. ...
1
vote
1answer
72 views

What are the most challenging tasks aiming to achieve the lowest error rate?

For example there is the MNIST database which is used to test artificial neural network (ANN), however it's not so challenging, because some hierarchical systems of convolutional neural networks ...
3
votes
2answers
818 views

Predicting chemical reactions using AI

Is there any research which study application of AI into chemistry which can predict the output of certain chemical reactions. So for example, you train the AI about current compounds, substances, ...
9
votes
2answers
779 views

How much of Deep Mind's work is actually reproducible?

Deep Mind has published a lot of works on deep learning in the last years, most of them state-of-the-art on their respective tasks. But how much of this work has actually been reproduced by the AI ...