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.

227 questions with no upvoted or accepted answers
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Image recognition of selfie images

I developed an Android app that lets anyone upload pictures of encyclopedic things (bridges, museums, dishes, landscapes, paintings, etc) to Wikimedia Commons. Unfortunately, 5% of the users find it ...
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69 views

What happens with activations?

I am playing with convolution network, assembling something between AlexNet and ResNet. Not very deep, about 10 conv. layers including 2 through residual connection, and 3 fully-connected layes at the ...
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3answers
106 views

Real purpose of pooling

Recently I had a doubt as to what is the real purpose of pooling layers in neural networks is? The most common answer is To select the most important feature To increase the receptive field of the ...
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1answer
135 views

Why is training and validation loss steadily rising (eventually to NaN) in this CNN of mine?

Dear ML and data scientists: I have 4 layers of gray scale images for every single biological specimen in my dataset. I am trying to train a 4-convolution CNN (see pytorch architecture below) to ...
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1answer
739 views

Pytorch - Loss is decreasing but Accuracy not improving

It seems loss is decreasing and the algorithm works fine. But accuracy doesn't improve and stuck. ...
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0answers
51 views

How to help neuronal network with an other model

I am working on an image classification problem, the input data normally is images to classify, but I thought latitude and longitude would play something on these satellite images. I sorted by ...
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5k views

Adding multilabel classifier to TensorFlow example

I am starting with the generic TensorFlow example. To classify my data I need to use multiple labels (ideally multiple softmax classifiers) on the final layer, ...
3
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1answer
1k views

Generate new images based on a dataset of images

Is it possible take a training set of one million 120 x 120 pixel tiles, feed these tiles into a machine learning algorithm. And then make it synthesize images that look like the original training set ...
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0answers
12 views

features to help distinguish between document images

we are trying to build a model to classify different types of documents as the first step in our pipeline (final goal is to read all the text). Currently we use ImageNet to extract the features and ...
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0answers
37 views

Understanding the significance of LeNet-5 w/ MNIST data set

I'm beginning to learn about conv nets and started with what I understand to be one of the seminal works: LeNet-5. However, my limited experimentation doesn't seem to show any advantage over a single ...
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0answers
24 views

Classifying satellite data

I have a large data set of RGB satellite data that classifies 64x64 pixel images with a spatial resolution of 10m per pixel into 10 classes (e.g. highway, industrial, river, forest). Now I want to ...
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0answers
8 views

Distinguish real building pictures from rendered ones

I need to train an algorithm to identify rendered building images from real pictures. Here's an example: A rendered picture A real picture The real pictures will vary from Good quality to Poor ...
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2answers
57 views

Detect malicious GIFs

I was reading this article talking about a form of targeted internet bullying which involves sending flashing images via Twitter to people with epilepsy. I was wondering whether there is a way to ...
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0answers
33 views

Did I do the right thing in my CNN Keras (class imbalance - augmentation)

To implement my Binary CNN in keras, I had a dataset of ~~35000 images but only 700 is from one class and all the others are from the other class, so what I did: I get the 700 unique images from class ...
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0answers
22 views

Does object detection do a better job at image classification than image classification

I read in an article that object segmentation can do object detection better than object detection algorithms. I assume this is because there is more detailed information in the annotation images. I ...
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2answers
175 views

after augmentation validation accuracy going down?

My main question is about augmentation. if I process the augmentation I believe it always better than less data but in my case the validation accuracy going down train : 7000 images , validation: ...
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2answers
3k views

Looking for animals dataset for deep learning classification

Do you know any datasets that contain animals and their accurate classifications? I am looking for any dataset that categorizes animals. For example: a dataset with insects, with an image of an ...
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0answers
339 views

Why is my Siamese network always predicting 1?

There is no change to loss and the accuracy stays the same. ...
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0answers
162 views

Audio files and their corresponding spectrograms for image classification process

Suppose I have a dataset of audio files that I have to use for whale sound classification. I am choosing the strategy of treating it as an image classification problem by using their corresponding ...
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0answers
16 views

Where should we release our video dataset for activity recognition?

We have an activity recognition dataset made of tens of thousands video clips. Which are the alternatives to release it to the research community? Is there any public website? I saw for instance ...
2
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2answers
236 views

Pre-processing on MRI images

I have MRI images of brain tumors collected from a hospital (not a benchmark dataset). And I am planning to use them to predict/classify tumour types using a typical machine learning approach: texture ...
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0answers
16 views

Neural Network for detecting/checking for requirements in diagrams

My question is more about what approach is a good/the best approach for my problem: THE PROBLEM - I'm an (mechanical/software) engineer and we take extensive amount of time to review technical ...
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0answers
36 views

How can I get the original pixels that lead to the decision in CNN?

I work on medical images and I want to locate the most relevant regions of the image based on deep learning spatially CNN. So I feed my data into VGG16 architecture and get the features maps. Now I ...
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0answers
62 views

it is possible to use features maps of CNN to localised important areas in image?

I'm new in deep learning and CNN, I understand how convolutional and pooling layers work, I understand how and why feature maps are created. How I can localize from the feature maps important area in ...
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0answers
39 views

CNN kernel location for input image

Given a CNN, say AlexNet: How could one relate kernel locations at the 3rd conv block, i.e 13x13 filter size to the input image. Would that give a meaningful representation in terms of the input ...
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3answers
55 views

Is it reliable to use TensorFlow (ML in general) to classify baggage bag tags based on the presence of a green stripe?

The images are identical except for the presence of the stripe on the side. I am trying to use a classify the images into 2 classes: greenStripe, noGreenStripe. I tried to use tensorflow retrain with ...
2
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2answers
143 views

Simple Object Detection

I want to create a simple object detection tool. So basically an image will be provided to the tool and from that, it has to detect the number of objects. For example An image of a dining table ...
2
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0answers
28 views

How does convolution operation perform in CNN?

I know that convolution operation has the property, associative law. if I need to use multiple filters in succession and to perform this operation on multiple images, it makes sense to convolve the ...
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0answers
154 views

Machine Learning & Image Recognition: How to start?

I've been a full stack web developer for 15 years now and would like to be involved in machine learning. There is already a specific scenario for this: We have a database with several million products ...
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0answers
239 views

Spatial Transformer Networks and Data Augmentation

We are all familiar with the famous Deep Mind paper STN. Upon implementation, such as https://pytorch.org/tutorials/intermediate/spatial_transformer_tutorial.html , did anyone still use input data ...
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1answer
90 views

calculation of average ROC in IMageNet paper?

The IMageNEt paper Image Net. presents the Average ROC curve for the 16 classes in the imagenet data, visit image figure. 8 in the paper. what is the known function to compute this ROC plot. As ROC ...
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0answers
102 views

What are natural (computed) pre-images useful for?

I've just been reading Zeiler, M.D. and Fergus, R., 2014, September. Visualizing and understanding convolutional networks. In European Conference on Computer Vision (pp. 818-833). Springer ...
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1answer
898 views

What preprocessing steps to be followed before image comparison?

1 down vote favorite For example I am trying to find the similarity between two images using skimage - SSIM. The code block will be as follows ...
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0answers
736 views

Test data from ImageNet

Here's the description about the data usage for ILSVRC 2016 of ImageNet. I've interpreted it with the table as follows, ...
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0answers
460 views

dynamic addition and variety of neural network outputs

After studying some academic papers about neural network recognition, plus trying some of them out myself, I do understand how you can train a network to give you a certain output on a defined set of ...
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0answers
17 views

Number of SURF features normally used?

I am interesting in knowing an approximate amount of SURF features used to do e.g. image-recognition on 224x224x3 images. Is there a standard amount of features used? Or perhaps a well-acclaimed ...
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0answers
1k views

Caffe net.predict() outputs random results (GoogleNet)

I used pretrained GoogleNet from https://github.com/BVLC/caffe/tree/master/models/bvlc_googlenet and finetuned it with my own data (~ 100k images, 101 classes). After one day training I achieved 62% ...
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24 views

Classification of moving pixels with convolutional neural networks

I have a data set with videos of moving pixels. Each video contains 32 frames, each frame is 32x32 with two pixels in white and the rest in black. I have binary labels for 800 of these obtained by ...
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1answer
19 views

Can I train a CNN to detect the number of objects without localizing them first?

So I was trying to search but couldn't find any answers. I was wondering if it possible to train a model to detect the number of items of interest in a photo without having bounding boxes or dots to ...
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1answer
24 views

Weighted loss functions vs weighted sampling?

For image classification tasks, is there a practical difference between using weighted loss functions vs. using weighted sampling? (I would appreciate theoretical arguments, experience or published ...
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27 views

List of undesirable faces?

An Australian sporting league simulated live crowds using cardboard cut-outs to fill empty stadiums during COVID-19. Fans were allowed to submit their own faces to be used on the cutouts, which ...
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0answers
15 views

what's the SOTA for medical imagery classification for diagnostic purposes?

Many medical image datasets - Ultrasound for example - have a time component that is quite powerful. But some of the papers I have read use ConvNets and seem to ignore temporality. Have there been ...
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0answers
24 views

class activation mapping when accuracy is 100%

I am a beginner to image classification and apologies beforehand if the question I am asking is dumb. I am currently using the following model: ...
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0answers
47 views

Gender Prediction from Offline Handwriting Using Convolutional Neural Networks

Starting from the fact that handwritten documents style are gender-dependent (male and female have different writing styles), I'm trying to predict writer's gender from its handwritten scripts using ...
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0answers
12 views

From Patch-based Classifier to Full Image classifier

I was wondering if it is feasible to train patch-based image classifier, due to small amount of data, and then use it in order to initialize training for full image classification, but this time on ...
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2answers
67 views

How to improve accuracy in the following code?

I have the about 43 different categories of traffic signs images data. If I am using the small data of 3 categories the maximum accuracy I am getting is around 65% and I have tried a lot of different ...
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1answer
24 views

Label A records B times or label A*B records

This question concerns pre-training data sourcing. Suppose you have a human workforce of B individuals and a potentially unlimited source of data. The task is ...
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0answers
17 views

Automated taxonomic identification of insects – where can I find some good enough software or code?

Short context: my colleagues study plant-pollinator networks. Insect (pollinator) identification is a task that requires a lot of effort. I would like to know if there are already trained or ...
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0answers
138 views

ValueError: could not convert string to float: 'Nor967.jpg'

Whenever I try to use the data augmentation ImageDataGenerator I'm getting an error like could not convert string to float. Here is my code. ...
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0answers
14 views

Fixing attention of CNNs for image classification

I'd like to fix attention of a CNN to a particular region of a given image. For example, given 28x28 image, I'd like my model to only consider only the top-left 5x5 region. What's the proper way of ...

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