All Questions
13 questions
0votes
0answers
464views
Is it possible to transform audio with neural networks to make it sound like 3d sound
so the idea is to feed neural network data like input: mono audio(extracted from existing 3d audio) output: 3d audio after training it should convert mono audio to 3d sound do you think it is possible?...
0votes
2answers
614views
Is there a neural network that accepts both the current input and previous output?
I am quite new to neural networks. I am trying to implement in Python a neural network having only one hidden layer with $N$ neurons and $1$ output layer. The point is that I am analyzing time series ...
2votes
1answer
1kviews
Do correlations matter when building neural networks?
I am new to working with neural networks. However, I have built some linear regression models in the past. My question is, is it worth looking for features with a correlation to my target variable as ...
2votes
0answers
214views
Inaccurate masks with Mask-RCNN: Stairs effect and sudden stops
I've been using matterport's Mask R-CNN to train on a custom dataset. However, there seem to be some parameters that i failed to correctly define because on practically all of the images, the bottom ...
- 43
3votes
1answer
278views
What is the fastest way to train a CNN with billions of examples?
I have a CNN model that I need to train for a large scale genomics application. It is working well with a subset of my training data. I have scaled up to a subset of about 130 million examples and ...
5votes
1answer
1kviews
How do I combine models trained on different data to increase classification accuracy?
I have two trained models. One is using a LinearSVC algorithm and is trained on numerical data from medical examination from patients with diabetic retinopathy. The second one is a neural network ...
4votes
2answers
180views
Using a neural network to identify a stable region within a set of data?
I am working on a problem in which I am attempting to find a stable region in a spiral galaxy. The PI I'm working with asked me to use machine learning as a tool to solve the problem. I have created ...
0votes
1answer
368views
Deep Q Learning Algorithm for Simple Python Game makes player stuck
I made a simple Python game. A screenshot is below: Basically, a paddle moves left and right catching particles. Some make you lose points while others make you gains points. This is my first Deep Q ...
- 131
2votes
0answers
219views
Understanding CNN+LSTM concept with attention and need help
I have a question about the context of CNN and LSTM. I have trained a CNN network for image classification. However, I would like to combine it with LSTM for visualizing the attention weights. So, I ...
- 21
2votes
1answer
1kviews
Reinforcement learning to play snake - network seems to not get trained at all
I am trying to build a network able to play snake game. This is my very first attempt to do such stuff. Unfortunately, I've stuck and even have no idea how to reason about the problem. I use ...
- 123
4votes
1answer
686views
Convolutional Layers on a hexagonal grid in Keras [closed]
Keras' convolutional and deconvolutional layers are designed for square grids. Is there was a way to adapt them for use in hexagonal grids? For example, if we were using axial coordinates, the input ...
0votes
2answers
2kviews
How to decrease accuracy from 99% to 80%~85% using keras for training a model
How do I decrease the accuracy value when training a model using Keras; which parameters can I change to decrease the value? My objective is not to actually decrease it, but just to know which ...
- 19
5votes
1answer
1kviews
Over- and underestimations of the lowest and highest values in LSTM network
I'm training an LSTM network with multiple inputs and several LSTM layers in order to set up a time series gap filling procedure. The LSTM is trained bidirectionally with "tanh" activation ...
- 61
