All Questions
28 questions
2
votes
0
answers
111
views
How to Create a Neural Network Model to Generate Dance Movements Based on Music in MMD Format
I am working on a project where I need to create a neural network model to generate dance movements based on music. My goal is to achieve results similar to this video: https://youtu.be/FrA7f5F9TsI
...
- 21
0
votes
1
answer
122
views
How do I input multi-channel Numpy array to U-net for semantic segmentation
I had lidar 3D point cloud data from semantckitti. I want to perform Semantic Segmentation on the data using U-Net. I converted the 3d point cloud data into 2D using spherical conversion and saved the ...
0
votes
1
answer
33
views
How to convert my test data in the same dimensionality as my train data
I have trained a VAE with jpg images. My latent space dimension has 768 features and when plotting the latent space it looks like this:
However, when I use the scikit learn tool LDA (Linear ...
- 3
2
votes
1
answer
215
views
How does the memory augmented neural network work, and how to make a simple implementation?
How does the memory augmented neural network (MANN) work? How can I make a simple MANN with a vanilla neural network especially without a recurrent network?
- 1,096
0
votes
3
answers
702
views
What is loss function in Neural Networks?
I've been studying NNs with tensorflow and decided to code a simple NN from scratch to get a better idea on hwo they work.
It my understanding that the cost is used in backpropagation, so basically ...
- 13
0
votes
1
answer
385
views
Validation Accuracy remains constant while training VGG?
I posted this question on stackoverflow and got downvoted for unmentioned reason, so I'll repost it here, hoping to get some insights
This is the plot
This is the code:
...
- 218
6
votes
1
answer
118
views
It is possible to use deep learning to give approximate solutions to NP-hard graph theory problems?
It is possible to use deep learning to give approximate solutions to NP-hard graph theory problems?
If we take, for example, the travelling salesman problem (or the dominating set problem). Let's say ...
- 181
0
votes
1
answer
893
views
Why won't my model train with CTC loss?
I am trying to train an LSTM using CTC loss, but the loss does not decrease when I train it. I have created a minimal example of my issue by creating training data where the network simply has to copy ...
- 101
2
votes
2
answers
890
views
Extract features with CNN and pass as sequence to RNN
I read an article about captioning videos and I want to use solution number 4 (extract features with a CNN, pass the sequence to a separate RNN) in my own project.
But for me, it seems really strange ...
user40943
0
votes
0
answers
184
views
How GAN generator produce integer RGB colored picture?
For traditional neural networks, I know that we can't constraint the output to be strict integers. My question is what technique does GANs use to produce integer outputs, that can be then converted to ...
- 197
2
votes
2
answers
840
views
Finding patterns in binary files using deep learning
I am a newbie in deep learning and wanted to know if the problem I have at hand is a suitable fit for deep learning algorithms. I have thousands of fragments each of about 1000 bytes size (i.e. ...
- 121
0
votes
1
answer
42
views
Is it possible to use deeplearning with spark (with a distributed databases as HDFS or Cassandra)? [closed]
If it is possible, will it be really useful or the model will end up converging very early(with a typical optimum learning rate) ? Any content on this topic will be helpful for me.
- 47
4
votes
2
answers
3k
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 ...
2
votes
2
answers
136
views
Are there ensemble methods for regression?
I have heard of ensemble methods, such as XGBoost, for binary or categorical machine learning models. However, does this exist for regression? If so, how are the weights for each model in the process ...
- 211
1
vote
0
answers
25
views
What are examples of models for traffic sign detection that can be easily implemented?
I'm working on a college project about traffic sign detection and I have to choose a paper to implement it, but I have basic knowledge of TensorFlow and I'm afraid of choosing a paper that I can't ...
- 11
4
votes
2
answers
236
views
What could be the problem when a neural network with four hidden layers with the sigmoid activation function is not learning?
I have a large set of data points describing mappings of binary vectors to real-valued outputs. I am using TensorFlow, and would like to train a model to predict these relationships. I used four ...
- 63
2
votes
0
answers
74
views
How should I make output layer of my neural network so that I can get outputs ranging from [-20,-1]
I am trying to make a neural network which takes in 0 and 1 as it's input and should give me output ranging from [-20,-1].I am using three layers with sigmoid as the activation function .How should I ...
- 63
1
vote
0
answers
49
views
How could I locate certain words or numbers in a financial statement?
I would like to code a script that could locate a specific word or number in a financial statement. Financial statements roughly contain the same information, they are however not identical and ...
- 11
1
vote
2
answers
323
views
TensorFlow 2.0 - Normalizing input to DNN (on structured data) [closed]
I have a structured dataset of around 100 gigs, and I am using DNN for classification in TF 2.0. Because of this huge dataset, I cannot load entire data in memory for training. So, I'll be reading ...
- 111
0
votes
1
answer
2k
views
Should the biases be zero or randomly initialised?
I'm initialising DNN of shape [2 inputs, 2 hiddens, 1 output] with these weights and biases:
...
- 1,318
2
votes
0
answers
307
views
Suggestions for Deep Learning for regression on huge 3D volumes
I have a dataset of 3D images (volumes) with dimensions 400x250x400. For each input image I have an output of the same dimensions. I would like to train a machine learning (or deep learning) model on ...
- 53
1
vote
0
answers
181
views
DQN not able to learn in a game where other agents perform random walks
I am making a school project where I should develop any kind of game where I can have one reactive agent and one agent based on machine learning competing with each other.
My game consists of a ...
- 205
2
votes
1
answer
508
views
Should I apply ReLU to non negative output?
Suppose I want to predict the position of a sensor based on its reading.
I can first predict the unit vector and predict the distance to be multiplied to this vector.
And I know that distance will ...
- 325
4
votes
0
answers
1k
views
Can we combine multiple different neural networks in one?
I want to make a kind of robotic brain, i.e. a big neural network, which includes an NLP model (for understanding human voice), real-time object recognition system (so that it can identify particular ...
- 41
1
vote
0
answers
56
views
How to create a task-graph based neural network?
I'm trying to design a neural network with a task hierarchy. This is my idea so far:
...
- 2,246
3
votes
0
answers
731
views
Getting worse performance when training a pre-trained model with the existing class
I am training pre-trained SSD-InceptionV2-Coco to detect the "car",
which is one of the classes in mscoco label.
I train the model with ~50k sample from KITTI, 500k iteration with batch size 2.
I ...
- 131
5
votes
2
answers
2k
views
What layers to use in a Neural Network for card game
I am currently writing an engine to play a card game and I would like for an ANN to learn how to play the game. The game is currently playable, and I believe for this game a deep-recurrent-Q-network ...
- 59
30
votes
2
answers
37k
views
What are "bottlenecks" in neural networks?
What are "bottlenecks" in the context of neural networks?
This term is mentioned, for example, in this TensorFlow article, which also uses the term "bottleneck values". How does ...
- 411