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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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1answer
94 views

How do the current input and the output of the previous time step get combined in an LSTM?

I am currently looking into LSTMs. I found this nice blog post, which is already very helpful, but still, there are things I don't understand, mostly because of the collapsed layers. The input $X_t$,...
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1answer
29 views

when should I create a custom loss function?

Hi I'm using neural network to solve a multi regression problem. I'm trying to predict continuous values, to be more specific I'm making a tracking algorithm to track the position of an Object, I'm ...
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0answers
30 views

Is there a deep learning-based architecture for digit localisation?

I'm new to object detectors and segmentation. I want to localize digits on a plate as fast as possible. All images of the dataset are normalized to $300 \times 60$. There are different approaches to ...
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1answer
40 views

When should I use a linear activation instead of ReLU?

I have read this post: How to choose an activation function?. There is enough literature about activation functions, but when should I use a linear activation instead of ReLU? What does the author ...
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1answer
63 views

Emotional Speech Synthesis

We are a team of computer science our graduation project about EmotionalSpeech Synthesis. We've found valuable information like research papers and WaveNet, Tacotron. A website (https://www.voicery....
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1answer
58 views

What would be the most effective self-learning algorithm for a 7 player social deduction game?

There's this 7 player social deduction game called Secret Hitler, and I have been trying to find a self-learning AI algorithm to learn how to play this game for a while. Basically, four players are ...
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0answers
24 views

What is the underlying model of IBM Watson Assistant and Microsoft LUIS?

As I stated in my question, I would like to know the underlying pipeline and machine learning models that are used to classify intents and identify entities in IBM Watson Assistant and Microsoft LUIS ...
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0answers
25 views

Reinforcement learning number of episodes per epoch not matching with paper

I am trying to reproduce results presented in this paper. On page 4, the authors state: ... we train for 50 epochs (one epoch consists of 19*2*50 = 1900 full episodes), which amounts to a total ...
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1answer
104 views

How does Hindsight Experience Replay learn from unsuccessful trajectories

I am confused by how HER learns from unsuccessful trajectories. I understand that from failed trajectories it creates 'fake' goals that it can learn from. Ignoring HER for now, if in the case where ...
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3answers
68 views

How can neural networks be used to generate rather than classify?

In my experience with Neural Nets, I have only used them to take input vectors and return binary output. But, here in a video, https://youtu.be/ajGgd9Ld-Wc?t=214, Kai Fu Lee, renowned AI Expert shows ...
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1answer
193 views

Training an AI to recognize my voice (or any voice)

I want to start a project for my artificial intelligence class about speaker recognition. Basically, I want to train my AI to detect if it's me who's speaking or somebody else. I would like some ...
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3answers
107 views

Extracting algebraic constraints from the input data

I would appreciate your help with this (naive) question of mine. Given the set of points located on a circle, $x_{i}, y_{i}$ as the input data, Can a deep/machine learning algorithm infer that radius ...
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2answers
101 views

How to fix time dimension in time varying data-sets using deep learning model for classification?

Dataset Description I am working on famous ABIDE Autism Datasets. The dataset is very big in a sense that it has more than 1000 subjects containing half of them as autisitic and other half as ...
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0answers
24 views

Assigning Weighting Factors

I have a hypothetical example that closes to my research problem: Assume you are a boss and you have different types of tasks that you need to assign to your employee. Sensitive task (very classified)...
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21answers
13k views

Can digital computers understand infinity?

As a human being, we can think infinity. In principle, if we have enough resources (time etc.), we can count infinitely many things (including abstract, like numbers, or real). For example, at least, ...
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0answers
157 views

Deep Learning Approaches for Color Enhancement Testing

I'm a student, and currently into image processing project and coding using OpenCV. Recently, I watched Sebastian Thrun from Udacity in TedTalks talked about AlphaGo and I'm totally interested in the ...
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2answers
70 views

How long it takes to train face recognition deep neural network? (rough estimation)

If I use a desktop PC with a GPU, how long it might take to train face recognition deep neural network on let's say dataset of 2.6 million images and 2600 identities? I guess it should depend on ...
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0answers
58 views

How to develop face recongiton program using CNN to obtain more than 95% accuracy? [closed]

I want to develop face recognition program using convolutional neural network. Can some one tell me steps to follow to do the same? I am new to deep learning. I want to develop it on windows using ...
2
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1answer
25 views

Doubt in Deep-Q learning with sparse rewards

I am working on a deep reinforcement learning problem, when I got stuck at the following questions. They are rather general and not specific to my specific problem. The solution uses a sparse reward ...
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2answers
109 views

Why do we need multiple LSTM units in a layer?

What is the point of having multiple LSTM units in a single layer? Surely if we have a single unit it should be able to capture (remember) all the data anyway and using more units in the same layer ...
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2answers
586 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: ...
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0answers
10 views

Which metrics of COCO API are suitable for object detection

These days I train a person detector and I use COCO API to evaluate my model. It uses Recall and Precision to evaluate a detection task. It's output is something like this: ...
2
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1answer
34 views

What are sim2sim, sim2real and real2real?

Recently, I always hear about the terms sim2sim, sim2real and real2real. Will anyone explain the meaning/motivation of these terms (in DL/RL research community)? What are the challenges in this ...
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1answer
30 views

Why is image classification tasks are dominated by minimizing cost function instead of maximizing ones?

I was watching a video of policy gradient by Andrej Karpathy at 10:00 there shows an equation for supervised learning for image classification. $max\sum _{i}log \:p(y_i|x_i)$ I have worked with ...
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3answers
90 views

How much can the addition of new features improve the performance?

How much can the addition of new features improve the performance of the model during the optimization process? Let's say I have a total of 10 features. Suppose I start the optimisation process using ...
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1answer
88 views

Applications of AI for creatives and artists

I have just watched a few videos on Tedtalks talking about how AI benefits creatives and artists but none of the videos I watched provided further resources for reference. So far, I have only came ...
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3answers
6k views

Can BERT be used for sentence generating tasks?

I am a new learner in NLP. I am interested in the sentence generating task. As far as I am concerned, one state-of-the-art method is the CharRNN, which uses RNN to generate a sequence of words. ...
34
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1answer
19k views

Which library would you recommend to begin with deep learning?

Which library (TensorFlow or Keras) would you recommend for a first approach to deep learning? I'm a neuroscience student trying for the first time computational approaches, if that matters.
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2answers
63 views

Running 2 NEAT nets on the same observations

So i have been playing around with neat-python. I made a program, applying neat, to play pinball on the Atari 2600. The code for that can be found in the file ...
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2answers
80 views

Why is MSE used over other quadratic loss functions?

So I was wondering, why I have only encountered square loss function also known as MSE. The only nice property of MSE I am so far aware of is its convex nature. But then all equations of the form $x^{...
2
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0answers
24 views

Are there methods that allow deep networks to learn object categorization in a self-supervised way?

When training a deep network to learn object classification from a set like ImageNet, we minimize the cross entropy between the ground truth and the predicted categories. This is done in a supervised ...
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0answers
19 views

Why hasn't deep learning been used for word level alignment?

I've been exploring word-level alignments tools such as MGIZA and it seems to me that there hasn't been any new tool for this problem. Are neural networks not suitable to solve this problem or simply ...
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1answer
23 views

Is this learning rate schedule increasing the learning rate?

I was reading a PyTorch code then I saw this learning rate scheduler: ...
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3answers
117 views

Is machine learning required for deep learning?

The answers to this Quora question say it's OK to ignore machine learning and start right away with deep learning. Is machine learning required or is useful for understanding (theoretically and ...
7
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1answer
185 views

What is “early stopping” in machine learning?

What is early stopping in machine learning and, in general, artificial intelligence? What are the advantages of using this method? How does it help exactly? I'd be interested in perspectives and ...
0
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1answer
77 views

Artifacts After pruning Unet CNN

Im trying to make a dark image brighter using CNN-UNet arcitecture. When I train the network I get the following results: When I cut the features in half for pruning, and do full train again, I get ...
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0answers
8 views

Can someone please explain the basics of a procedural reason system?

I’m a complete beginner so any help is appreciated
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2answers
50 views

Can multiple activation functions be replaced with a single activation function?

I'm just started to learn deep learning and I have a question about this neural network: I think $h_1$, $h_j$ and $h_n$ are perceptrons. So, if they are perceptrons, all of them will have an ...
1
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1answer
27 views

How to use a deep learning network on new data-set?

I am trying to use a network for classification. This network works very well on the author's example data, but doesn't work on new data. Currently, I am using the popular EEG Motor Movement/Imagery ...
2
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0answers
13 views

How to choose the suitable Neural Network Architecture for Regression Tasks

so I'm working on a Project where I want to predict the Vehicle Position from the Vehicle Data like speed, acceleration etc.. now the data that I have comes also with a timestamp for each sample ( I ...
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0answers
9 views

How does keras `train_on_batch` return value work?

From the doc, train_on_batch() will return a scalar representing the loss and the metric. I want to know whether the loss/metric is evaluated before the weight is ...
7
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3answers
248 views

Can some one help me understand this paragraph from Nvidia's progressive gan paper?

Furthermore, we observe that mode collapses traditionally plaguing GANs tend to happen very quickly, over the course of a dozen minibatches. Commonly they start when the discriminator overshoots, ...
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1answer
31 views

Can A.I/Deep Learning use one image as content for another image?

Is it possible for A.I to redraw an image in a new context? More specifically, suppose I take a photo of a notebook. I get the angle, lighting and perspective perfect. Now I copy an image I found ...
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2answers
64 views

What is the benefit of using identity mapping layers in deep neural networks like ResNet?

As I understand Resnet has some identity mapping layers that their task is to create the output as the same as the input of the layer. the resnet solved the problem of accuracy degrading. But what is ...
1
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1answer
41 views

“Outside-in” versus “Inside-out” machine learning

A little background... I’ve been on-and-off learning about data science for around a year or so, however, I started thinking about artificial intelligence a few years ago. I have a cursory ...
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0answers
12 views

Choosing best combinations from all possible combination expressions based few variables, unary operators, binary operators

I have a few financial variables of a stock universe like OHLC prices, volume, and other fundamentals with varying time-frequency. Using this set I'm creating an expression that gives the weights to ...
2
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1answer
33 views

How to make a distinction between item feature and environment feature?

My data is stock data with features such as stocks' closing prices.I am curious to know if I can put the economy feature such as 'national interest rate' or 'unemployment rate' besides each stocks' ...
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0answers
23 views

How to calculate covariance matrix of the mini-batch in the k-th layer using Python?

I am a beginner in Python. I want to calculate the covariance matrix of a mini-batch in a given hidden layer.
1
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1answer
16 views

What should load_mask() return if an image doesn't have any objects? (Mask RCNN)

I want to use Mask RCNN to do image segmentation. I need to override the load_mask function for the dataset class. I know this function should return mask tensors and class ids of objects in an image. ...
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0answers
7 views

Looking or the simplest framework to train keypoint detector

I currently use an object detector to detect an object and specific parts of it (a crop and its stem). Such detector is not the best choice for detecting parts that could be represented by a point (...