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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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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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Video / image recognition: Featurize movement

How would it be best to featurize movement of objects between video frames? Let's say I have a footage of a wolf pack and I am trying to understand where the Alpha is there. The best is actually not ...
Tagar'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
2 votes
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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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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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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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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
1 vote
1 answer
44 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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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. ...
dataengineer22's user avatar
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1 answer
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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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34 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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51 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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27 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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37 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
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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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24 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
186 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
  • 115
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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
32 views

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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18 views

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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0 votes
1 answer
160 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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55 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
18 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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0 answers
16 views

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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0 answers
29 views

Overfitting on implemented Dense-Net architecture

I have been playing with different architectures and see how they would perform on the quick draw dataset. Even though the accuracy is significantly higher, I can't reduce overfitting no matter what I ...
Marcuss's user avatar
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0 answers
89 views

Object detection on largest number of classes

Does anyone know any pretrained object detection models to run with python with highest number of objects to be recognised? Yolo finds 80 objects, it is good if I can find a larger number. It would be ...
Jean's user avatar
  • 37
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0 answers
31 views

How do I test with custom images for a model that was trained on quick draw npy dataset

I have been trying to test my CNN model on a custom doodle of an apple that I drew. But even when I preprocess the image to have the same shape with the training data, the model gives wrong prediction ...
Marcuss's user avatar
1 vote
1 answer
55 views

Different validation sets give very different results. What can be the reason?

I have ~78k microscopy images of single cells, where the task is to classify for cancer (binary classifier). The images are labeled according to which patient the data came from. I do the train-val ...
Emil Edvardsson's user avatar
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0 answers
16 views

Validation Loss not decreasing for RESNet model

I have been trying to train a Resnet model to classify Diabetic Retinopathy images into binary classes. The dataset consists of around 35k images. The val loss and accuracy does seem to behave weirdly ...
SarveshSC's user avatar
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0 answers
67 views

Why does my validation loss go so high after few epochs?

I am facing an issue with my pretrained mobilenetv3 model, it is quite strange how the validation loss is behaving, it starts low but then goes up ridiculously high. I have normalized my images as ...
NevMthw's user avatar
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0 answers
79 views

How can I prevent mobilenetv3 from overfitting with less data?

So I have around 462 images and I can't really get more images. I am using a pretrained model of MobileNetV3 with the respective weights. I am facing a huge problem of overfitting and no real solution ...
NevMthw's user avatar
  • 57
1 vote
0 answers
75 views

MobileNet validation loss not decreasing over time

I am trying to train a MobileNetV2 on a custom dataset, to image Classification task. Cardinality is 864 images, split in 70%/20%/10%, balanced between the 3 different classes. Weights are pre-loaded ...
elbarto's user avatar
  • 11
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1 answer
48 views

Improve image classification model with trained generator

Is it possible to improve an image classification model with a generator (trained class conditionally). (so this is same source/target distribution and same source/target task, so not domain ...
InKodeWeTrust's user avatar

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