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Questions tagged [image-classification]

For questions about image classification: a decision problem where an algorithm must decide to which class ('cat', 'chair', 'tree') an input image belongs.

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My keras CNN model gives good predictions in 10/11 classes but missleads to the 11th class. What can I do to improve?

My project involves classifying printed numerical characters from real-life essays. My dataset includes 11 classes ('0' - '10'), with the label '10' representing the '/' symbol. The issue is that ...
Mai Khanh's user avatar
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How specific should I be with my region of interest in image data for training a CNN model for better accuracies?

I am trying to train a 3D CNN model for classification of cancer stages on a dataset that comprises of head to neck CT image series which is split into 5 classes corresponding to the stages of cancer....
Ashwin Singh's user avatar
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Validation accuracy can't increase above 70%

I am building a classifying model to predict images over 3 classes. The data is balanced, with 10.5k images for train ( 3.5k for each ), 3k validation images ( 1k each ). I increased my ...
Dragos123's user avatar
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lost "target value" role after merge data

Hello there, Currently i am trying to learn Orange how to classify the quality of products we produce b image analysis. I have a set of images which i analyse via image embedding. This gives 1 dataset....
bas domburg's user avatar
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How to work with SAR and optical images? Trying to do a Multimodal CNN

I´ve been trying to come up with a image classification algorithm that uses SAR and optical images, but I havent been able to write a code that works, where could I look for guides about multimodal ...
Belat's user avatar
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Validation accuracy stuck in tf keras

So I have a model to classify images into 3 classes. I have 10.5k train images ( 3.5 per each category ) and 3k ( 1k per each category ) validation images but I can't increase my val_acc no matter ...
Dragos123's user avatar
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Accuracy and test_accuracy gives a result =1

I've developed a code for classifying hyperspectral images using three different convolutional neural network (CNN) architectures: 1D, 2D, and 3D. The code has two main parts: Preprocessing and data ...
user162895's user avatar
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I want to create a system for classifying bone fractures What pre-processing steps can I use to process images?

I want to know where I should put the image preprocessing code in the decision tree code How to extract features from images and classify them
zxcvbnm zxcvbnm's user avatar
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Preparing image datasets for a CNN

I'm struggling to decide on how to setup my model. I'm learning by myself so hoping to get some advice. I am building an image classifier using a CNN with the aim to classify food images as healthy or ...
mintteaplease's user avatar
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Converting multiple binomial logits to multinomial

I am faced with a image classification problem with 3 classes. My existing network consists of 3 'branches' each corresponding to one of the classes. Each of these branch outputs a binomial logit ...
Farhan Ahmed Wasim's user avatar
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How can i retrieve incorrect labelled predictions on new unseen data on image classification when i want to retrain my model later on?

I've recently made a binary image classification model with transfer learning. The model is used on an api and the predictions gets saved into a database. The problem is that it predicts images ...
Enes Aygun's user avatar
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HCC-TACE-datase

Is anyone worked with CT images. I am having problem in dicom images. I want to make a similar slice for all my segmentation image and liver image. Is there any tutorial or suggestion for that? Thank ...
Sumaiya's user avatar
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Image Generation Models

I am looking for a list of different image generation models and how I can test them? For example: DALL-E (accessible via ChatGPT4) Stable Diffusion (open source) CLIP? - but idk how to access/test it....
x89's user avatar
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Resources for writing CNN for semantic segmentation

I am intermediate/advanced in Python and new to machine learning. Most of what I know about deep learning I learned through Deep Learning with Python by François Chollet. I am trying to do image ...
utx7563yu's user avatar
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While working on binary image classification, the class mode set to binary incorrectly labels the images, but does it correct on categorical

I am currently working on a binary image classification. My problem is that when i use data augmentation, it incorrectly labels the images when it is set to binary. The things i have tried: Looked ...
Enes Aygun's user avatar
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Applying dropout effectively in CNN

I am fairly new to deep learning and machine learning in general and have been trying to teach myself. I’m interested in understanding when and how to effectively use dropout in a CNN. While ...
Nile's user avatar
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Why is my 3D CNN stuck at constant accuracy?

I am writing a CNN for binary classification MedMNIST data: https://medmnist.com/, specifically the Lung Nodule 3D dataset (N=1633 and 7:1:2). Currently, my model is not training at all; it is either ...
Matthew H's user avatar
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Creating a custom loss function for an image classification model where the label matters

I have the following dataset of images, where we can see the image distribution of labels below. I want to construct a loss function that, on the one hand, outputs probabilities for a specific class ...
Tom's user avatar
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Is there any standard or heuristic for deciding on the dimensions and filters of a convolution layer for image processing?

I reposted this from StackOverflow since it does not meet StackOverflow's guideline to focus on programming and coding questions. Link to the original question. I want to find ways other than trial ...
Joachim Rives's user avatar
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Why do object detection model adversarial masks look different from those of image classifiers?

I was messing around to observe the behavior for adversarial attacks on image classifiers, and decided to try it with an object detector as well. I realize that inference time attacks are more complex ...
Soumil Datta's user avatar
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Image Classification when image is a plot of two functions

My goal is to perform a supervised classification of a number of objects. Each object is described by a plot of two functions, f(t) and g(t). The plot dimensions, (b - a) and T, are about the same ...
James's user avatar
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K means clustering of image with k=1 vs mean of all pixels

I have relatively uniformly colored images and I extracted colors using k-means. k means 1 showed the best results for my modeling purposes, k means 2 not so much, and with k-means 3 there ceased to ...
phil27's user avatar
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1 answer
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How to optimize my CNN classification architecture

I have this CNN based model architecture that takes an RGB image. Now I'm trying to change it for a color classification case on an object (10 color classes: white, black, yellow, etc). This current ...
Mary's user avatar
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How to detect abnormal fetal head size with image classification?

I'm writing Python code to predict fetal head circumference 10mm range using classification. The model will train to classify a fetal head image into a range (e.g., 50–60 mm) representing its ...
NiStack's user avatar
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Using AWS Sagemaker (Ground Truth) for Labeling Jobs + Rekognition. How best to approach my project?

I'm new to ML so bear with me. I want to create an object detection model that can detect anything from flags (e.g. Israel flag) to symbols (e.g. yin-yang sign) to a giving setting (e.g. war). I am ...
Noey's user avatar
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ML approach for quantifying building quality perception

I'm working on a project to model public perceptions of buildings in a tourism context, focusing on attributes like beauty and mystery. The data I have is a labeled dataset of building photos, each ...
Blerg's user avatar
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How to handle multiple training jobs in AWS Sagemaker Pipelines?

I am trying to create a pipeline for training an image dataset via Sagemaker Pipelines. Based on the examples I understood that for all distinct stages like data preparation, model training, ...
Mimansa Maheshwari's user avatar
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21 views

Using cropped background images as background class

I’m currently working on a binary image classification problem using high resolution (up to 6000x4000 pixels) images with complex backgrounds, and CNN transfer learning. In order to reduce Images size ...
Dot_Pixis's user avatar
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45 views

Competition test set performance much lower than validation set

We are a team of 3 participating in a university competition for a deep learning course. The competition involves a binary image classification task where we have to predict leaf diseases on a (5200, ...
Fiorenzo Fiorenzi's user avatar
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29 views

Test accuracy is very low, compare to Trian and validation accuracy for image classification for 400 class

I am working on image classification with 400 class , during training , I am getting good training and validation accuracy , but test accuracy is approximate 0-1% .My input image is 1 scale , with ...
NeelPatwa's user avatar
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Pretrained computer vision models that accept as input a segmented image and the original image

My data is a set of segmented images with extra details: there is 30 object classes each object is labeled with its state (very old, old-fashion, modern) and each object is also labeled with a second ...
Karim-53's user avatar
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1 answer
46 views

How to use additional features in image captioning?

I have the following question - is it possible to train a model based on Transformer architecture to use additional attributes to generate a caption for an image? For example, I have a dataset with ...
Jeremy Cuberian's user avatar
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17 views

Which image classification methods/models could suit my (product) image classification problem?

Say you are a potato chips company. The goal is to have consumers upload images of the product they are having issues with and be able to identify the product by brand/variant using machine learning. ...
Paul's user avatar
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1 answer
31 views

Binary Classification of Images- CNN

I am learning ML and am working on a CNN problem where I need to classify images of CATS and DOGS. The way I have setup the labels is that cats are 1 and dogs are 0. I have made the final output layer ...
Hussain Bhavnagarwala's user avatar
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Different generated patches from original image using vision transformer (ViT)

I am using ViT for image classification, I scaled images in range of [-1,1], and I also padded images. Then, I used the following code to see the original image and generated patches, but the output ...
Zara Nz's user avatar
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42 views

My VGG16 Model's training and validation accuracy scores are stuck

Im trying to create an image classification model that classifies plants from an image dataset made up of 33 classes, the total amount of images is 41,808, the images are unbalanced but that is ...
Therone Almadin's user avatar
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65 views

3D CNN accuracy is too low, how to improve it?

I have just started learning image processing and this is my first time working on video classification. I am trying to develop a model that recognizes hand gestures using the EgoGesture dataset(more ...
esyilmaz's user avatar
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30 views

Why does the first call to a TensorFlow function execute much slower than the second call?

I was doing an Image Classification problem using TensorFlow. I was generating the mean images for two image datasets having the same size. The dataset was generated using the tf.data API. Thereafter ...
Harsh Khare's user avatar
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43 views

How to remove augmented data from test data

I am working with this dataset https://data.mendeley.com/datasets/hxsnvwty3r/1 for object classification model like CNN. In the description of the dataset, I see in the description there are "...
usan's user avatar
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1 answer
26 views

Object Classification Dataset Creation

There is a problem I've faced recently which I'm not sure my approach is proper or not. There is bunch of field videos which I run a semi-supervised detection model to extract crops to train my ...
spawnfile's user avatar
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26 views

Image classification of centered objects with convolutional neural networks

Given that I have a set of images that contain multiple objects for which labels exist and the object the image label refers to is always in the center. The objects vary in size. I want to train a ...
fhllw's user avatar
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0 votes
1 answer
227 views

Histogram of Oriented Gradients (HOG) - Why normalize 16x16 blocks and not the whole picture?

I'm trying to learn Histogram of Oriented Gradients (HOG) I understand why we compute the gradient and the orientation and also map every gradient into a 9 binaries histogram that spans from 0 to 180. ...
euraad's user avatar
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1 answer
27 views

Detector vs Classification - Detecting a netted bag for fruit/vegetables in image

The application is detecting the presence of a netted bag in an image. The image can contain fruit and vegetables, either with or without a netted bag around them, or below them (no constraints about ...
ADHD Productions's user avatar
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1 answer
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How do I create an Image Dataset for a CNN?

I'm currently working on assembling a CNN for image classification with tensorflow.keras. I have all my images in a file which I already uploaded to my program. Also I have CSV-Files for training and ...
Martin Gerry's user avatar
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Is a csv file to store image path and class neccessary for image classification?

I just get my hand-on a basic deep-learning project. I am working on multi-class image classification project with e-commerce dataset. I am not sure whether by storing training images in sub-folder ...
RXT_ Z's user avatar
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1 answer
199 views

Combine two separate models created via Transfer Learning?

Suppose have two 'image classification' models created by transfer learning on the same base model[1], each producing a different set of labels/classes. Trained at different times, with different ...
barryhunter's user avatar
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0 answers
64 views

Create a TensorFlow Input pipeline from GCS Bucket?

I wish to generate a TensorFlow input pipeline (i.e. tf.data pipeline) for an image classification project. The images stored in a GCS bucket having access controls and is not publicly accessible. And ...
Harsh Khare's user avatar
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0 answers
19 views

Multilabel Image Classification - problem with probability at prediction

I'm building a multilabel image classification problem usinc MIMIC CXR dataset. I'm struggling with probability at prediction as for every image in test dataset the probability of an existance of ...
greg0001's user avatar
2 votes
1 answer
2k views

Input dimensions for the EfficientNetV2 family of models

I have a question regarding the EfficientNetV2 family of models. If my understanding is correct there are 6 models under this family - B0 to B1 & S are the comparatively smaller models while M &...
th2797's user avatar
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TensorFlow lite classification model;{1,1,1,3}

How can I initialize and insert images into this classification model; what is meant by {1,1,1,3} according to my parameters it should be {1,size,size,3} please help try { Firstclass model = ...
Mohammad Nabeel's user avatar

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