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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CNN Eliminate Wrong Results

I extracted images of human faces from the videos, but the model also recorded images without faces. I wrote CNN for emotion classification. In the obvious pictures, the probability is closer to a ...
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Graph Neural Networks for Segmented Images - Which Nodes do I connect?

I'm facing an interesting problem involving medical images. We are set out to test an hypothesis if certain objects in an image affect the diagnosis of a patient. I would love to hear any comments ...
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Exploratory data analysis (EDA) on large dataset

I am working with lots of data (we have a table that produces 30 million rows daily). What is the best way to explore it (do on EDA)? Take a frictional slicing of the data randomly (100000 rows) or ...
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Why Deep Learning / Neural Networs don't achieve state of the art results in tabular data problems?

Apparently, deep learning methods don't achieve state-of-the-art results on tabular data problems [1,2]. This claim appears to be known also by Kagglers. The SOTA method looks like it is the gradient ...
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How to solve MemoryError problem

I've created and normalized my colored image dataset of 3716 sample and size 493*491 as x_train, its type is list I'm tring to convert it into numpy array as follows ...
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Binary classification from local and global feature selection

I want to train a deep leaning model, consisting of images. My question is which scenariowas chosen to train the model? scenario 1 : I train images local context on Output 1, and I train images clobal ...
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Is it possible for the (Cross Entropy) test loss to increase for a few epochs while the test accuracy also increases?

I came across the question stated in the title: When training a model with the cross-entropy loss function, is it possible for the test loss to increase for a few epochs while the test accuracy also ...
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How to optimize hyperparameters in Bert?

I am using the BERT model in order to classify stereotypes in sentences. I wanted to know if there is a way to automate the optimization of hyperparameters such as 'epochs', 'batchs' or 'learning rate'...
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Which machine learning technique can be used for predictive log analysis

I have log data with 100k records. And These parameters. It looks like this. message types can be helpful for anomaly type detection. Out of total 15 message 5 ...
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Auto encoder network

Is there any rule that we should use only deconvolution operations in decoder block of auto encoder network or we can use convolution in such way that it up-samples or mirrors the corresponding ...
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Can i use Transformer-XL for text classification task?

I want to use transformer xl for text classification tasks. But I don't know the architect model for the text classification task. I use dense layers with activation softmax for logits output from the ...
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Dealing with near duplicates using NLP

I have a dataframe like as shown below ...
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What is Typical Variation Normalization?

I was reading this paper and came across a term "Typical Variation Normalization". What does that mean intuitively and formally? Any resources I can refer to know more about it?
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Why grad cam is not showing despite of no error?

I am applying grad-cam on 3d images and I see no errors, I only can see the Scan of my original images but not the grad cam. from skimage.transform import resize ...
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What to do if the model is not performing well on a validation dataset

I am trying to use different ML classifiers for binary classification (SVM, logistic regression,DNN). The dataset used for training contains 333 columns and about 2000 rows. The classes being slightly ...
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What should be the loss and accuracy value while training the input and output data in deep learning using jupyter notebook?

I am working on fault detection and fault classification in power system using deep learning, when I am training the input data (fault coefficients m, n, p, q) and output data (fault type A-G, B-G, C-...
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I am trying to establish a relationship b/n hcanopy & 18 predictors (vv_name & vh_name) using CNN but my model isn't learning. How can I resolve it?

Before building and running the model, I have rescaled and normalized the data. Here is my model - ...
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How to choose max layers and units to search over in hyper parameter tuning

When performing any hyper parameter tuning, let's say random search for simplicity, and I want to search over a minimum to max units/nodes in a layer, and a minimum to max number of layers, are there ...
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How to deal with one output for multiple inputs?

Hei! I want to train a model, that predicts the sentiment of news headlines. I've got multiple unordered news headlines per day, but one sentiment score. What is a convenient solution to overcome the ...
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Clarification on "predict the next character given the previous 100 characters"

I am studying Justin Johnson's lecture on RNNs Lecture recording: https://www.youtube.com/watch?v=dUzLD91Sj-o&list=PL5-TkQAfAZFbzxjBHtzdVCWE0Zbhomg7r&index=12&t=3177s One of the examples ...
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key generation from feature vectors in high dimentions

I welcome any suggestions to solve the following hard problem: I have a dataset of float feature vectors of size 512 where each feature vector is extracted from a face image. I want to generate a key ...
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LSTM for binary classification using multiple attributes

I haven't used neural networks for many years, so excuse my ignorance. I was wondering what is the most appropriate way to train a LSTM model based on my dataset. I have 3 attributes as follows: ...
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use pre-built model to predict audio file

i am using this code to build a model that recognizes emotions in speech, but i can't figure out how to use it after loading it in a new python file. this is what i have but the results are always the ...
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Is it right to argue that a testing dataset is not needed when evaluating the performance of a GAN?

For my degree final project I have been working on a GAN to solve a certain image enhancement task. The problem I’m currently working on has an extremely limited number of datasets due to the physical ...
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NameError: name 'librosa' is not defined [closed]

i'm working on Arabic Speech Recognition using Wav2Vec XLSR model. While fine-tuning the model it gives the error shown in the picture below. i can't understand what's the problem with librosa it's ...
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What kind of neural network am I using? How can I build a specific kind of network?

I'm going through a tutorial for tensorflow with keras and at one stage you build the neural network model using the code below. ...
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Erratic changes in validation accuracy

I am training the binary classification CNN model. It is part of the self-supervised pipeline and I use it to predict whether the transformation has been applied to an image. However, I am getting ...
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Which LSTM Training Strategy Performs better?

I would like to use LSTM for predicting multiple time series (Time series about sales per day in multiple countries. In parts, contradicting regional trends are present within the data. Sales is the '...
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Deep Learning accuracy vs Confusion Matrix accuracy

I am working on deep learning with fer2013 dataset. After training the model I got val_precision: 0.9168 (precision: 0.8492) ...
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Is Mask-RCNN a fully convolutional architecture?

Is Mask-RCNN a fully convolutional architecture (from what I see yes, because there are no dense layers but just wanted to make sure)? Thus can I feed differently sized images for inference without ...
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Genetic Algorithms (Specifically with Keras)

I can't get my deep genetic algorithm snake game to work and I can't figure out why. At this point, I think it must be either the crossover_rate/mutation_rate or the actual crossover code itself is ...
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Read all files from all the folders

I am using Windows, Jupyter Notebook, OpenCV, Mediapipe, Tensorflow. Hello. I have a video Dataset with 100 action folders and each folder has 100 videos(.avi). Frames Per Second is 25. I want to read ...
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Is Self-Supervised Learning a task of Representation Learning?

Maybe a weird question but: Currently, I'm writing a seminar paper about Self Supervised Learning for time series data. For this paper, I have to find methods to prepare unlabelled time series data ...
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At the first epochs, what will segmentation model get?

I am working at a semantic segmentation problem now, with 5-classes task. But when I running on validation function and output my probablities map. I found that with the background class (the extra ...
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Does eval loss decreasing slower than train loss indicate overfitting?

I am training a binary classifier using an efficientnetv2 model with a 1M image dataset where I do a 60/20/20 split. Does this graph mean that the model is over-fitting? I can see that the train loss ...
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NameError: name 'Patch' is not defined (cant use fastai-1.0.61 object-detection-fastai-0.0.10)after (! [ -e /content ] && pip install -Uqq fastai)

The problem still persists even after kernel restart. (cant use fastai-1.0.61 object-detection-fastai-0.0.10)after (! [ -e /content ] && pip install -Uqq fastai) I have tried downgrading the ...
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sentence type classification

I want to classify the sentences in my dataset as declarative, interrogative, imperative and ...
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Performance metrics for LSTM Autoencoder

I am building an LSTM Autoencoder (unsupervised model) to detect anomalies in a time series dataset. The input is telemetry data from routers and I want to detect anomalies in the throughout of router....
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Backpropagation in NN

During backward pass, which gradients are kept and which gradients are discarded? Why are some gradients discarded? I know that forward pass is computing the output of the network given the inputs and ...
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how to label 3d model for segmentation task

I'm working on 3d meshes dataset, i have to label it to train my deep learning model for a segmentation task like the picture shows. I spent days looking for a tool to label my 3d data but ...
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How to train deformable convolutions?

There is a concept in ML called deformable convolutions, instead of kernelling over rectangle filter, we use kernelling over learned shape. Whilst classic convolution is ...
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AttributeError: 'NoneType' object has no attribute 'landmark'

I am on windows, using jupyter notebook, Mediapipe:Holistic Solution, Python, tensorflow. I am using a Holistic solution and trying to get the left hand, right hand and pose landmarks. I am giving my ...
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Problem with timestamp

I have a data set with 2 timestamps (1 hour and then 15 minutes). how can I standardize the timestamps as 15 minutes? is it a practical practice to add other 3 rows (each one is 15 minutes) with the ...
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CycleGAN: Both losses from discriminator and generator drop fast, after 100 epochs outputs blurred original image

I'm trying to train a 3D Cycle-GAN on medical image synthesis, more specifically CT to MR. Currently I'm using a 3-Layer Discriminator and a 6 layer UNetGenerator borrowed from the official CycleGAN ...
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Splitting Subject Data in train, validation and test set for 3D Human Pose Estimation for better accuracy

This is a 3D Human Pose Estimation problem. There are totally 15 normal subjects in train set, 7 normal subjects in validation set and 7 normal subjects in test set. There are 7 impaired subjects ...
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Convolutional Neural network learning curve results

Working on a convolutional neural network with 6 classes and about 1500 image per class. The model that works best for me has given the results below, in previous models I have worked on has given ...
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Stride in time series classification/regression using neural networks

When dealing with time series in neural networks, we use windows with a size and a stride as input. Is it advantageous to train such a neural network with a stride that is smaller than the stride used ...
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How an lstm network classifies a time series

I am trying to understand how an LSTM model makes a decision to classify a time series into class A or B. I know that we can use the "TimeDistributed" parameter to access the intermediate ...
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Data Augmentation Keras length of data

I'm confused when I add data augmentation should I get more data or the same data I tested my x_train length to confirm but I got the same length before augmentation and after augmentation is that ...
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Splitting Subject Data in train, validation and test set for 3D Human Pose Estimation

This is a 3D Human Pose Estimation problem. There are totally 15 normal subjects in train set, 7 normal subjects in validation set and 7 normal subjects in test set. There are 7 impaired subjects ...
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