Questions tagged [deep-learning]

a new area of Machine Learning research concerned with the technologies used for learning hierarchical representations of data, mainly done with deep neural networks (i.e. networks with two or more hidden layers), but also with some sort of Probabilistic Graphical Models.

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8 views

Image segmentation on poor quality images

Which neural network image segmentation architecture works well with poor quality images?
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Why YOLO algorithm predicts B boxes for each grid cell S?

In yolo each grid cell predicts multiple bounding boxes lets say in YOLOv1 it predicts B=2, what is the advantage as it only predicts class probabilities only once for each grid cell. If that so why ...
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What's the point with neural networks if you can only predict linear test data?

So, I have tried all the different activation functions listed on https://keras.io/api/layers/activations/. I can indeed approximate any nonlinear function in the training range perfectly well - but ...
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How to implement random cropping during training?

I'm developing a U-net like model which segments the damaged tissue of the brain between two time-points in Multiple Sclerosis patients. The model is given the baseline and follow-up images as x and ...
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Learning sequences consisting of single non-zero entry and remaining zeros

Pattern such as [1 0 0 0], [0 1 0 0], [0 0 1 0], [0 0 0 1] can easily be learned by using LSTM. We have created patterns where above mentioned vectors serve as the basis but we reveal one index ...
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UNet Pytorch Audio Super-Resolution - Upsampling block problems

I am trying to reproduce Audio super-resolution. At the bottom is architecture in PyTorch from this paper (https://github.com/dsgiitr/Audio-Super-Resolution). It is supposed to accept downsamples/...
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Keras Custom Layer call Method

I have implemented a Keras Custom Layer in which I call a custom function inside the call method, the issue is when Keras is constructing the model, it is calling my custom layers call function with ...
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Using vgg16 or inception with wights equals to None

When using pre-trained models like vgg16 or inception, it seems that one of the benfits of using pre-trained model, is to save ...
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Why don't I find a decision making problem and dataset [closed]

I am a master student trying to work on decision support systems and improving their accuracy with machine learning techniques, namely neural nets for now. For 2 months, I have been trying to start to ...
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Calculating confidence score in NER

I am working on a problem on Named Entity Recognition. Given a text, my model is detecting the Named Entities and extracting that info for the end user. Now the ask is end user needs a confidence ...
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Inverse Autoregressive Spline Flow Implementation

I have to implement an algorithm for a university project, however I can not seem to wrap my head around it. The algorithm should be an inverse autoregressive normalizing flow using splines. It should ...
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Criteria for saving best model during training neural network?

I am doing 4-class semantic segmentation with U-net using generalised dice loss as loss function. General approach to save best model during training is to monitor validation loss at each epoch and ...
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Is this a tried alternative to word embedding for NLP?

I'm searching for research related to my idea, but apparently cannot articulate it well enough to the search engines to show me what's been published on this. My idea: in a deep learning context (text ...
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when will the mlp give constant prediction?

I have a regression task.(to predict price for finanical market) I build a mlp to do the regression. I found mlp will stop at giving a constance prediction. which i think it's useless. Does this mean, ...
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Multi Input Network MNIST-CIFAR10

I have the following task of meta learning: We want that our neural network learns to sum weights. 1)Do the training on MNIST, and on CIFAR10 (as support dataset). We want that performance (accuracy) ...
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AB testing for Recommender models

Let's say that I have two recommendation system models built, Model A and Model B. Now I track the performance of both the models for 5 days from 1st Jan to 5th Jan. Each model has been assigned a ...
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How to resize image along with their mask?

I have original images of the size 1935x1481. I am using labelme to annotate the images. I am creating polygons on the original image. Is there a way to resize the image along with their mask? I am ...
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Currency Normalization for Salary Prediction

I have a dataset (350k data points) with data of employees across different regions over the last 10 years. The dataset consists of their skills, the region they are in, the industry, their current ...
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DQL for detecting next move in games

I am trying to understand using DQL for playing board games and how we can do function approximation of the q-learning Bellman equation in order to detect the best next move , if anyone can give the ...
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If we only have the rating scores of items provided by the users, how do we use matrix factorization to build a recommender system model?

If we only have the rating scores of items provided by the users, how do we use matrix factorization (MF), factorization machine (FM), and deep learning (DL) to build a recommender system model?
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Keras: apply multiple filters to each feature map in CNN

I am new to Keras, and I want to do the following: take a 2D image, and apply four 2D convolution kernels to it, giving four 2D feature maps. I could accomplish this. But then I want to apply two ...
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LSTM input layer shape in Keras using functional API

0 I am trying to implement LSTMs on drug data the shape of the data is given below also the model but it throws an error which is "Input 0 is incompatible with layer lstm_1: expected ndim=3, ...
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multivariate biLSTM text classification

I have made a model that takes vacancy data and classifies it with (bi)LSTM. The variables of the initial dataset are: positiontitle ...
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Deep q learning from scratch weights diverge to NaN

I'm trying to make a deep q learning algorithm with neural network from scratch, minbatch gradient descent, replay memory, and target network. But weights diverge to NaN after a around 40 episodes ...
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In DQN, why not use target network to predict current state Q values?

In DQN, why not use target network to predict current state Q values, and not only next state q values? In doing a basic dq learning algorithm with nn from scratch, with replay memory, and minibatch ...
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Zero Padding in Convolutional neural network

We use Convolutional neural network because it by design learns features that generalize over spatial location , so when using conv operation it reduce image size and that what we hope to have so we ...
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Convolutional neural network with Deep Q learning in games

What does "the average magnitude of maximal action value output by the network" tell us? I mean if we plot this graph, is it good to start as low value and then increase until it goes in a ...
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Understanding outputs from ANN and how to improve validation loss

I apologise if this is a bit long winded, but it was suggested by another user that I post. I will start by saying that I am very new to the world of machine learning and deep learning. As such, the ...
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Is there any TF implementation of the Original BERT other than Google and HuggingFace

Trying to find any Tensorflow/Keras implementation of the original BERT model trained using MLM/NSP. The official google and ...
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Negative log-likelihood not the same as cross-entropy?

The negative log-likelihood $$ \sum_{i=1}^{m}\log p_{model}(\mathbf{y} | \mathbf{x} ; \boldsymbol{\theta}) $$ can be multiplied by $\frac{1}{m}$ after which the law of large numbers can be used to get ...
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1answer
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Keras: ValueError: Input 0 is incompatible with layer lstm_1: expected ndim=3, found ndim=2

I am using Keras functional API to write an LSTM model but It throwing an error can somebody please help below is the code for the model the output shape is 65. I am using Keras 2.2.4 and TensorFlow 1....
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22 views

Is this a task of meta-learning or transfer learning?

I have a task that I am not able to identify if it is of transfer or meta learning. I want to know this, in order to ask help in solving it, because there are some parts that I have not understood. ...
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Why does Adam optimizer work slower than Adagrad, Adadelta, and SGD for Neural Collaborative Filtering (NCF)?

I've been working on Neural Collaborative Filtering (NCF) recently to build a recommender system using Tensorflow Recommenders. Doing some hyperparameter tuning with different optimizers available in ...
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Choosing the size of the network for Neural Collaborative Filtering (NCF)?

I've been working on Neural Collaborative Filtering (NCF) recently to build a recommender system. After doing some hyperparameter tuning with various sizes for embedding and dense layers sizes, from ...
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Automated tools to generate synthetic training images out of synthetic 3D models and 2D backgrounds

I have 3D meshes and textures for a dozen of objects, which have to be detected in synthetic images. I have 2D textures of backgrounds these objects will be visible in front of. Object detection will ...
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How to force a NN to ouput the same output given a reverse input?

I want to choose an architecture that can deal with an input symmetry. As input, I have a sequence of zeros and ones, like [1, 1, 1, 0, 1, 0] and at the output layer I have N neurons that outputs a ...
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What type of ANN architecture to choose?

I have N number of teachers each of which has an input feature vector (25 dimensional) consisting of positive numerical values for different quality of aspects (for example, lecturing ability, ...
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AI to play games [closed]

Early, I had done usual AI (I created neural network for solving some tasks, ex:translation, object detection, etc.). I also had to deal with cool researches such as DeBERTa-v2(https://huggingface.co/...
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One Year Ahead Forecasting with Unevenly Spaced Time Series

I have many products in my warehouses which can be "demanded" any day by my different clients. I want to forecast how many of each item will be demanded for the whole next year. Naturally, ...
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How to annotate the object more efficiently

I want to perform object detection and object counting on the given below image using neural networks. My first step will be to annotate and label each object present in the training set of images. In ...
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what does one Shot learning mean? do they only need one image to train for some new class detection?

Being new to deep learning I am somewhat struggling to grasp the idea of one shot learning. Let us say I have a class to detect which didn't exist in training dataset such as COCO or Image NET. Can I ...
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1answer
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CNN model accuracy

I have trained my CNN model on CIFAR 10 and I got val_accuracy of 87% which is not a low value but when it comes to detection of pictures my model detected most of the pictures wrong. anyone knows why ...
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1answer
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CNN model low accuracy

I have 1299 images in 4 classes (374/269/284/372). I want to use the VGG19 model, add a dense layer at the top and fine-tune it with my images. As I only have 1299 images, I also want to use data ...
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Can I get some advices on inferencing people from upwards using Yolov5?

I'm trying to inference people from upwards and count them using Yolov5. I know the controversy between yolov5 and yolov4, but for me, Yolov5 is more easier and reliable to use, also the setup. I have ...
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How to add more weight to certain features?

I have extracted features from two types of signals. Prior to merging them to create one feature vector, I have computed an importance score of every feature within that type of signal. I would like ...
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Why is the kernel of a Convolutional layer a 4D-tensor and not a 3D one?

I am doing my final degree project on Convolutional Networks and trying to understand the explanation shown in Deep Learning book by Ian Goodfellow et al. When defining convolution for 2D images, the ...
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1answer
26 views

How to implement sequence to sequence models?

I have a dataset with patient demographics, diagnosis history, hospital visit dates, drugs consumed etc. All these events have time stamp information (except static info like demographics such gender, ...
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How does attention for feature fusion works

I am struggling to understand how would a self-attention layer be used for features of different modalities fusion. What I understand until now is that : Every unique modality is fed into a self-...
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1answer
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Can you choose a binary feature matrix for a binary classification model

This may be a stupid, but, I am new to deep learning (and machine learning for that matter) and I can't seem to find any literature to help with my question. All I can see when Googling many different ...
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22 views

class weights formula for imbalanced dataset

I am trying to make some semantic segmentation. I have 7 imbalanced classes in my case. I found several methods for handling Class Imbalance in a dataset is to perform Undersampling for the Majority ...

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