Questions tagged [neural-networks]

For questions about a artificial networks, such as MLPs, CNNs, RNNs, LSTM, and GRU networks, their variants or any other AI system components that qualify as a neural networks in that they are, in part, inspired by biological neural networks.

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What are some good alternatives to U-Net for biomedical image segmentation?

Soon I will be working on biomedical image segmentation (microscopy images). There will be a small amount of data (a few dozens at best). Is there a neural network, that can compete with U-Net, in ...
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52 views

What are examples of commonly used feature and readout maps?

It is well-known that deep feedforward networks can approximate any continuous function from $\mathbb{R}^k$ to $\mathbb{R}^l$, (uniformly on compacts). However, in practice feature maps are ...
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60 views

Are No Free Lunch theorem and Universal Approximation theorem contradictory in the context of neural networks?

To my understanding NFL states that, we cannot have an hypothesis (let's assume it is an approximator like NN in this case) class that can't achieve certain accuracy parameters $\leq \epsilon$ with ...
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67 views

Why is the loss associated with my neural network increasing?

I am currently learning neural networks. Using data from http://www.mariofrank.net/touchalytics/index.html, I am trying to predict "User ID" by training the neural network model shown below. However, ...
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40 views

How can I get to a final output of shape $224 \times 224$, without FC layers, from a tensor of specific shape, in OpenPose?

I am approaching the implementation of the OpenPose algorithm for realtime human body pose estimation. According to the official paper OpenPose: Realtime Multi-Person 2D Pose Estimation using Part ...
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36 views

Why does model complexity increase my validation score by a lot?

I learned that when creating neural networks the go to was to overfit and then to regularize. However I am now in a situation where, when I make the model more complex (more layers, more filters, ...) ...
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30 views

Can the addition of low-quality images to the training dataset increase the network performance?

I already trained a deep neural network called YOLO (You Only Look Once) with high-quality images (1920 by 1080 pixels) for a detection task. The result for mAP and IOU were 93% and 89% respectively. ...
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65 views

Neural network to extract correlated columns

I want to use a neural network to find correlated columns in a .csv file and give them as a output. The input .csv file has ...
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44 views

Recent algorithms for correcting mislabeled data using multilayer perceptrons

I am doing literature research on algorithms for correcting mislabeled data using multilayer perceptrons. Found an "old" paper An algorithm for correcting mislabeled data (2001) by Xinchuan Zeng et al....
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29 views

Suitable algorithms for classifying terrain condition (asphalt, dirt etc) for motor vehicles

I am required to obtain data through a sensor located on the vehicle reading speed, vibration, roll and tilt, within a sample time, to classify the current road condition using machine learning for a ...
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29 views

Impact or applications of introducing attention in deep networks modelling multi-agent systems

I have been reading quite a lot about the research progress in the domain of self attention-based neural networks that were introduced by Google Inc. in their paper titled "Attention is all you ...
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34 views

Using ML for Enemy Generation in Video Games

I am attempting to make a 2-D platformer game where the player traverses through an evil factory that is producing killer robots. The robots spawn at multiple specific locations in each level and ...
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56 views

How is the receptive field of a CNN affected by transposed convolution?

When computing receptive field recursively through a CNN, does a transposed convolution affect the receptive field the same way that a convolution does if the kernel and stride is the same?
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1answer
180 views

Why am I getting a difference between training accuracy and accuracy calculated with Keras' predict_classes on a subset of the training data?

I'm trying to solve a binary classification problem with AlexNet. I split the original dataset into training and validation datasets using a 70/30 ratio. I have trained my neural network with a ...
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2answers
76 views

Does a fully convolutional network share the same translation invariance properties we get from networks that use max-pooling?

Does a fully convolutional network share the same translation invariance properties we get from networks that use max-pooling? If not, why do they perform as well as networks which use max-pooling?
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Sign Language to Speech conversion

Is there any solution about sign language to speech conversion for mobiles? Can anyone suggest me the flow and tools so that I may implement the solution for mobiles?
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104 views

Can we use GPT-2 to smooth out / correct text?

Are we able to use models like GPT-2 to smooth out/correct text? For instance if I have two paragraphs that need some text to make the transition easier to read, could this text be generated? And, ...
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20 views

How to handle set-like size agnostic input format

Let's set up some hypothetical simplified scenario: Each instance $i$ of my imaginary dataset $D=\{i_{1}, \ldots, i_{MAX}\}$ has different number $k_{i}$ of $n$-dimensional vectors as input into my ...
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117 views

How I can predict the next number in a sequence with a neural network?

I've been dabbling with machine learning and neural networks (namely, resnet50) for a few months now, mostly doing image recognition. I am currently trying to make a program that, given a string of ...
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59 views

Neural nets not learning mnist dataset

I tried training a 2 hidden layer network using the mnist dataset, but I am not getting any results. I have tried tuning the learning rate(tried 0.1 and 0.0001) and the number of epochs(tried 10 and ...
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41 views

What is the expected value of an IOU in this case?

I have a detection problem. An object with a probability of 0.5 is in a box with coordinates ((0,0), (2, 2)) and with a probability of 0.5 a box with coordinates ((2,0), (4,2)). What is the maximum ...
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15 views

Regional specialization in neural networks (especially for language processing)?

What is the status of the research on regional specialization of the artificial neural networks? Biology knows that such specialization exists in the brain and it is very important for the functioning ...
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31 views

What activation functions are better for what problems?

I’ve been reading about neural network architectures. In certain cases, people say that the sigmoid "more accurately reflects real-life" and, in other cases, functions like hard limits reflect "the ...
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33 views

Generating 5 numbers with 1 input before loss function

I am trying make an ANN model that takes a constant m (will be changed later but now it is just a constant, let's say 0) as an input and generate 5 non-integer numbers (a1,a2..a5) after some layers ...
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42 views

How to Layer based Feature extraction?

I have read that in deep networks you can engineer each layer for a particular purpose with regards to feature learning. I'm wondering how that is actually done and how it is trained? In addition ...
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37 views

What's the difference between semi-supervised VAEs and conditional VAEs?

Can someone explain the difference? I'm assuming the difference is just that the neural nets representing the encoder and decoder are trained in a semi-supervised manner in semi-supervised VAE, which ...
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38 views

How can I extract the reason of the legal compensation from a court report?

I'm working on a project (court-related). At a certain point, I have to extract the reason of the legal compensation. For instance, let's take these sentences (from a court report) Order mister X ...
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27 views

Determine Frequency from Noisy Signal With Neural Networks (With Adeline Model)

I'm trying to determine the frequency from a signal with NN. I'm using the Adeline model for my project and I'm taking a few samples in each 0.1-volt step in a true signal and a noisy one. First ...
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40 views

How to understand my CNN's training results?

I created a multi-label classification CNN to classify chest X-ray images into zero or more possible lung diseases. I've been doing some configuration tests on it and analyzing its results and I'm ...
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1answer
321 views

How does a batch normalization layer work?

I understood that we normalize to input features in order to bring them on the same scale so that weights won't be learned in arbitrary fashion and training would be faster. Then I studied about ...
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53 views

Why are the current means and the old ones the same in this implementation of Elastic Weight Consolidation?

I'm trying to re-implement Elastic Weight Consolidation (EWC) as outlined in this paper. As a reference, I am also using this Github repository (another implementation). My model/idea is pretty ...
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38 views

How can I prevent a Recursive Neural Network from performing extremely poorly after a few cycles?

I've trained a neural network that can predict the $(n+1)^{th}$ element in a sequence, given the $n^{th}$ element. It does a pretty good job doing this, with very little error. The problem emerges ...
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106 views

Should I use deep learning to solve my task?

I need to predict the performance (CPI cycles-per-instruction) of 90 machines for the next hour (or day). Each machine has a thousand records (e.g. CPU and memory usage). Currently, I am using a ...
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41 views

FasterRCNN's RPN network training

I would like to know if my understanding of RPN training is correct, and if never training the RPN on some specific anchor box is bad (i.e if the anchor never sees good nor bad examples). To make my ...
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43 views

Can learned feature vectors be considered a good encryption?

Considering I have some neural network that, using supervised learning, transforms a string into a learned feature vector where "close" strings will result into more close vectors. I know that since ...
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41 views

How can I feed any word into a neural network?

I am working on an Intent detection problem for a chatbot in Java. So I need to convert words from String to a double[] format. I tried using wordToVec(deeplearning4j), but it does not return a vector ...
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131 views

What is a location-based addressing in a neural Turing machine?

In the neural Turing machine (NTM), the content-based addressing and location-based addressing is used for memory addressing. Content-based addressing is similar to the attention-based model, ...
2
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1answer
42 views

Unsupervised learning to optimize a function of the input

I am looking to build a neural network that takes an input vector $\mathbf{X}$ and outputs a vector $\mathbf{Y}$ such at $f(\mathbf{X}, \mathbf{Y})$ is minimized, where $f$ is some function. The ...
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0answers
25 views

Calculation of Neural network biases in backpropagation

While learning neural networks I've found a basic Python working example to play with. It has 3 input nodes, 4 nodes in a hidden layer, 1 output node. 5 data sets for training. The initial code is ...
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0answers
14 views

Loss function for increasing the quality of the image when labels are not perfectly alligned

I am trying to increse the quality of the images that I gather from the microscope. That is a acoustic microscope and there are lots of technical details but in a nutshell the low quality images and ...
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0answers
30 views

Same implementation, but agent is not learning in Retro Pong Environment

I tried to implement the exact same python coding by Andrej Karpathy to train RL agent to play Pong, except that I migrated the environment from Gym to Retro. Everything is the same except the action ...
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0answers
26 views

Choosing neural network output for prediction (regression) of a dynamical system

I’m trying to train a neural network to approximate the output of a dynamical system $dy/dt=f\left(y(t), u(t) \right)$, namely, given $y(0)$ and $u(t_i), i=1,2...N$ I want the network to predict $y(...
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0answers
30 views

Is there a detailed description or implementation of an end-to-end speech recognition system?

I am currently trying to implement an end-to-end speech recognition system from scratch, that is, without using any of the existing frameworks (like TensorFlow, Keras, etc.). I am building my own ...
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0answers
38 views

What is the complexity of policy gradient algorithms compared to discrete action space algorithms?

I am using a policy gradient algorithm (actor-critic) for wireless networks. The policy gradient-based algorithm helps because it considers continuous action space. But how much does a policy ...
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38 views

Can a Video Game Characters Behavior be directed by a NN?

So, I’m looking into some dynamic ways in which one can drive the behavior of a video game character. Specifically an NPC (Non playable character) that will be observable from the players point of ...
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0answers
25 views

Which neural network algorithms can be used to map motion vectors in image processing?

I'm working on finding out the motion vectors of objects in images. The inputs are the images of objects in motion. The outputs of neural network are the object name, direction of object vector and ...
2
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1answer
77 views

Unable to achieve expected outputs using NEAT for the snake game

I am trying to implement NEAT for the snake game. My game logic is ready, which is working properly and NEAT configured. But even after 100 generations with 200 genomes per generation, the snakes ...
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2answers
43 views

Maximize loss on non-target variable

I have a neural network that should be able to classify documents to target label A. The problem is that the network is actually classifying label B, which is an easier task. To make the problem more ...
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0answers
19 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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