Questions tagged [cnn]

Question 1

Meta has recently published its new transcription model Omnilingual ASR: Open-Source Multilingual Speech Recognition for 1600+ Languages. However, I am somewhat sceptical about it, particularly given ...

Question 2

I am training a model using Keras python library to recognize images of drawings that belong to two artists. Here is a screenshot of the flactuations I am seeing: 587/587 ━━━━━━━━━━━━━━━━━━━━ 906s 2s/...

Question 3

I’m training a CNN (DenseNet169) for a medical imaging task with ~12,000 training samples using fine-tuning (pretrained on ImageNet). I monitor both training and validation loss/accuracy. What I see ...

Question 4

I'm using a CNN classification model that I trained to identify phytoplankton classes from png images. The images in the training set do not contain a scale bar. However, some of the datasets I want ...

Question 5

I'm trying to train a CNN model to identify phytoplankton species from a training set. During preprocessing, the images are resized to 224x224, which seems to be stretching or compressing the object ...

Question 6

To be clear, I shuffled my data when I trained it. It is only the testing data that I modified to be unshuffled, and found that accuracy tanks. (i also used the same data for training and for testing)

Question 7

I am working on a regression task to estimate glucose concentration from image data. The images are of reagent test strips, where a chemical reagent reacts with a blood sample and changes colour (...

Question 8

I’m working on a binary classification problem in a biomedical context, with ~15,000 instances. Each instance corresponds to a single biological sample (a cell), and for each sample I have three co-...

Question 9

For my Bachelor's thesis, I am working on a project named "Neural Networks for Matrix Inversion" where deep learning methods are used to compute the inverse of a matrix in comparison to ...

Question 10

So I've been working on this convolutional neural network but my accuracy is stuck at 62% without improving and I'm afraid I'm in rather severe situation with the overfitting issue. I've been trying ...

Question 11

I've been trying to aggregate a normal CNN loss with a loss that quantifies how well we can cluster the second-to-last layer embeddings (i.e. feed the embeddings to a 2D Self Organizing Map (SOM) and ...

Question 12

I have spatio-temporal data with PM2.5 concentration at a daily timestamp for 51 latitudes and 51 longitudes (51 x 51 grid). I converted the netCDF files to a pandas dataframe with timestamp as the ...

Question 13

I am currently using a CNN for face detection. I plan to use open datasets to pre-train one neural network and fine-tune the neural network using images captured by my camera. The open datasets are ...

Question 14

I have implemented a classic feedforward NN (by myself) and it works fine. However, I added conv layers and now learning behavior is very strange. On a simple task (classifying zeros and Xs on a 28x28 ...

Question 15

I've been interested lately in doing research about different neural networks and how to contribute to Autonomous Vehicles, I used a couple of images to train a model and the results were different ...

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Questions tagged [cnn]

What has Meta's "Ominlingual ASR" really learned?

Why training time alternates between 900s and 70s when training my keras sequential model?

How to determine the optimal number of training epochs when validation loss stabilizes but does not increase?

Using a CNN classification model on images that contain a scale bar

Effects of resizing training images during preprocessing CNN classification model

when testing with shuffled data, accuracy is high, but when testing with unshuffled data, accuracy is low

How to Select Effective Features from Color-Based Image Statistics for Glucose Prediction?

Best CNN architecture for multiple aligned grayscale images per instance

Neural Networks for Matrix Inversion

Overfitting problem of convolutional neural network; how to fix?

Using a differentiable Self-Organizing Map loss in a CNN

Time Series Forecasting Using Geospatial Data

Is one dataset with many images of the same person acceptable?

CNN strange learning behavior

I would like to build an open source Traffic Signs Dataset solely for research purposes

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