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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
53 views

How should I detect an object in a camera image?

I would like to create a model, that will tell me if one type of object is in an image or not. So, for example, I have a camera and I would like to see when one object gets into the shot. Object ...
4
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1answer
178 views

Can a vanilla neural network theoretically achieve the same performance as CNN?

I perfectly understand that CNN takes into account the local dependency of each pixel to the nearby pixels. In addition, CNNs are spatially invariant which means that they are able to detect the same ...
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0answers
39 views

Paper & code for “unsupervised domain adaptation” for regression task

Does anyone know a paper or code that does "unsupervised domain adaptation" for regression task? I saw most of the papers were benchmarked on classification tasks, not regression. I want to do ...
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0answers
34 views

Is it possible to use adversarial training to learn invariant features?

Given a set of time series data that are generated from different sites where all sites are investigating the same objective but with slightly different protocols. Is it possible to use adversarial ...
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0answers
20 views

How to implement Multiple Neural network architecture, connected in parallel and series in Keras or Pytorch

Hello Dear StackExchange members, I want to make a deep network as shown in the image. I want each 'network 1 to look at the specific part of the input and I don't want to divide my input beforehand ...
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0answers
10 views

Inverting intensity on images to enhance image dataset

i just tried to improve my image dataset by inverting the images with a probability of 50% (means white background, black features transforms to black background, white features) I thought this will ...
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0answers
183 views

Applying a 1D convolution for 4D input

i'm trying to implement this paper and I'm stuck for quite some time now. Here is the issue: I have a 3D tensor and has (180,200,20) as dimension and I'm trying ...
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0answers
12 views

Binary annotations on large, heterogenous images

I'm working on a deep learning project and have encountered a problem. The images that I'm using are very large and extremely detailed. They also contain a huge amount of necessary visual information, ...
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1answer
77 views

Is DDPG just for deterministic environments?

I want to develop an AI for continuous space. I reached to DDPG algorithm that takes actions deterministically. If DDPG takes actions deterministically, should the environment also be deterministic? ...
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1answer
61 views

Is there a neural network method for time-varying directed graphs?

I want to study NN for time-varying directed graphs. However, as this field has developed relatively recently, it is difficult to find new ways. So the question is, is there any NN that can handle ...
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1answer
66 views

Which is better to start deep learning and understand it in depth (and not just a simple overview) - pytorch or tensorflow 2.0?

I am beginning to learn deep learning. I recently spoke with an expert in the field. He suggested that I start with pytorch because of these reasons: Keras abstracts the stuff a lot that we will not ...
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1answer
60 views

How does the CTC loss work?

I am trying to implement CTC loss in Tensorflow, but their documentation is pretty limited. So I am not sure how to approach the problem. I found a good example in Theano: https://github.com/...
3
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1answer
65 views

DQN in stochastic environment

I'm trying to apply a DQN to a stochastic environment but i'm having trouble getting it to converge. I found some similar questions asked here, but no solutions yet. I can fairly easy get the DQN to ...
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0answers
22 views

How to voxelize multiple frames at the time and append them together?

I'm trying to implement this approach for object detection and tracking. In this approach, the first step is voxelize each frame to construct a 3D tensor, the second step is to append multiple voxels ...
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0answers
15 views

What are some neural network models that can use auxiliary info during training for image segmentation?

What are some deep learning models that can use supplementary information other than RGB channels for image segmentation? For example imagine a poorly shot image of a river (blue) that shows a gap, ...
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0answers
29 views

Which model to use when selecting objects of interest?

I have a set of polygons for each image. Those polygons consist of four $x$ and $y$ coordinates. For each image, I need to extract the ones of interest. This could be formulated as an Image ...
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0answers
18 views

Issues related to RoI Pooling in keras

I am trying to do RoI pooling of an image whose RoI bounding box coordinates are known to me. Can anyone provide me the code for doing the same? I have read many repositories but I didn't get any ...
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0answers
17 views

What parameters can be tweaked to avoid a generator or discriminator loss collapsing to zero when training a DC-GAN?

Sometimes when I am training a DC-GAN on an image dataset, similar to the DC-GAN PyTorch example (https://pytorch.org/tutorials/beginner/dcgan_faces_tutorial.html), either the Generator or ...
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0answers
33 views

What are the benefits of using the state information that maintains the graph structure?

When you applying a graph structured data to the graph convolution network, what are the benefits of using the state information that maintains the graph structure?
2
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1answer
50 views

What is the purpose and benefit of applying CNN to a graph?

I'm new to the graph convolution network. I wonder what is the main purpose of applying data with graph structure to CNN?
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1answer
47 views

Clarifications on “Prioritized Experience Replay” (Deepmind, 2015)

Paper link : Prioritized Experience Replay About the blind cliffwalk setup: Why is the number of possible action sequences equal to 2^N? I cant think of sequences more than (N + 1) where one ...
2
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1answer
42 views

How do I locate a specific object in an image?

Some pictures contain an elephant, others don't. I know which of the pictures contain the elephant, but I don't know where it is or how does it look like. How do I make a neural network which ...
2
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1answer
171 views

How do I find the distance?

I am looking for solving this problem with training a deep learning-based classifier or image processing techniques. ps. I exactly do not need to know how much is distance, I only need to know whether ...
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0answers
49 views

How High and Low frequency filters effect activation in the next layer?

Generally, we come across terms such as High Frequency and Low frequency filters in Convolutional Neural Networks (CNN). In regards to this highlighted statement, in 'S1' section of this paper by ...
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1answer
91 views

Reinforcement Learning State Definition

I am quite new to Deep Reinforcement Learning, and I'm trying to define states in a Reinforcement Learning problem. The environment consists of multiple identical elements, and each one of them is ...
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1answer
43 views

Analysis of Training Loss and Validation Loss Graph

Here I am Showing Two Loss graphs of an Artificial Neural Network. Model 1 Model 2 Blue -training loss Red -val training loss Can you help me to analyse these graphs? I read some articles and ...
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0answers
106 views

What is the difference between GAT and GaAN?

I was looking at two papers Graph Attention Networks (GAT) by Petar Veličković and GaAN: Gated Attention Networks for Learning on Large and Spatiotemporal Graphs by Jiani Zhang. I'm trying to ...
2
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1answer
982 views

Adding BERT embeddings in LSTM embedding layer

I am planning to use BERT embeddings in the LSTM embedding layer instead of the usual Word2vec/Glove Embeddings. What are the possible ways to do that?
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0answers
12 views

Questions regarding rrn-writer by Robin Sloane?

https://github.com/robinsloan/rnn-writer I preface this by saying I do not know much about this topic, only that I have an intense interest in it, so I'm hoping I can make my questions as clear as ...
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1answer
40 views

Decreasing Loss, Constant Accuracy

Problem Statement I've built a classifier to classify a dataset consisting of n samples and four classes of data. To this end, I've used pretrained VGG-19, pretrained Alexnet and even lenet (with ...
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0answers
24 views

Why such a big difference in number between training error and validation error?

Question Why such a big difference between my 'Train loss' and 'Validation loss' as shown in the picture below? Is it a signal that my codes are wrong and my trained network is wrong as well? Some ...
2
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1answer
41 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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2answers
76 views

How do I perform object detection if there is only one type of object?

How do I do object detection (or identify the location of an object) if there is only one kind of object, and they are more of less similar size, but the picture does not look like standard scenes (it ...
2
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1answer
51 views

How does ARKit's Facial Tracking work?

iPhone X allows you to look at the TrueDepth camera and reports 52 facial blendshapes like how much your eye is opened, how much your jaw is opened, etc. If I want to do something similar with other ...
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1answer
32 views

Why feeding the correct output as input during training of seq2seq models?

So, I've read about seq2seq for time-series and it seemed really promising, but when I went to implement it, all the tutorial I've found use the correct output as input to the decoder phase during ...
4
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1answer
92 views

How can I build an AI with NLP that read stories

I want to do an NLP project but I don't know if it's doable or not as I have no experience or knowledge in NLP or ML yet. The idea is as follows: Let's say we have a story (in the text) that has 10 ...
2
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1answer
60 views

How do I classify an image that contains only polygons?

I have two closed polygons, drawn as connected straight black lines on a white background. I need to classify such images in to three forms Two separate polygons One polygon encloses the other The ...
2
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0answers
18 views

Validation Loss Fluctuates then Decrease alongside Validation Accuracy Increases

I was working on CNN. I modified the training procedure on runtime. As we can see the validation loss and validation accuracy, The yellow curve does not fluctuate much. Green curve and Red curve ...
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0answers
43 views

How can I interpret the following error graph?

I am training a neural network which produces the following errors (epoch number on the x axis). I have some questions regrading interpreting it. When I say ...
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0answers
27 views

Deep Generative Networks Probability of “Success”

I have built various "successful" GANs or VAEs that can generate realistic images reliably, but in either case the generative step is sampling a latent feature vector from some distribution and ...
2
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1answer
37 views

Neural Nets: CNN confirming layer/filter arithmetic

I was hoping someone could just confirm some intuition about how convolutions work in convolutional neural networks. I have seen all of the tutorials on applying convolutional filters on an image, but ...
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0answers
56 views

Super Resolution on text documents

I want to implement super-resolution and deblurring on images from text documents. Which is the best approach? Are there any Git-hub links which will help me to start? I am new to the field. Any help ...
2
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1answer
45 views

Reward does not increase for a maze escaping problem with DQN

I am using deep reinforcement learning to solve a classic maze escaping task, similar to the implementation provided here, except the following three key differences: instead of using a ...
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1answer
122 views

How can I train a deep learning model to predict a matrix?

I am trying to train a deep learning model to predict an 8*2 matrix. The predicted matrix would have complex values and the input matrix would be real numbers. Can it be done? Thank you for your time.
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0answers
99 views

Catastrophic Forgetting on Pong Environment using DQN

I am running a basic DQN on the Pong environment. Not a CNN, just a 3 layer linear neural net with ReLUs. It seems to work for the most part, but at some point my model suffers from catastrophic ...
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2answers
161 views

Do VR, AR and MR use any machine learning or deep learning?

I wonder if Virtual Reality (VR), Augmented Reality (AR) and Mixed Reality (MR) use any machine learning or deep learning? For example in AR, the virtual objects are brought into the real world, does ...
2
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1answer
61 views

Other deep learning image generation techniques besides GANs?

Can you please point me to some resources about image genereation besides GANs? Are there any other techniques throughout history? How did idea of image generation evolved and how it started? I tried ...
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2answers
78 views

How can I implement a GAN network for text (review) generation?

How can I implement a GAN network for text (review) generation? Please, can someone guide me to resource (code) to help in text generation?
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1answer
50 views

Understanding the configuration of replay memory and epsilon in deep reinforcement learning

I am tentatively reusing a codebase of pacman to train my own deep reinforcement learning model. While most of the components seems reasonable and understandable to me, there are two things that seem ...
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0answers
57 views

How to define cost function for custom nonlinear functions?

For logistic regression, the Cost function is defined as: \begin{equation} Cost(h_{\theta}(x)-y) = -ylog(h_{\theta}(x))-(1-y)log(1-h_{\theta}(x)) \end{equation} I now have a nonlinear function \begin{...