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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8 views

Getting a bounding box mask given coordinates of an object in the image

In the paper See the Glass Half Full: Reasoning about Liquid Containers, their Volume and Content, one of the inputs to the model is "a bounding box mask smoothed by a Gaussian kernel". I'm not sure I ...
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Image classification model only predicting one class

I'm trying to build a deep learning model to predict image classes from the Kaggle competition. I'm using the Xception model as the top layers and then putting the last layer into a dense layer with ...
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26 views

Binary Classification of a ship Dataset

I want to create a ship detection classifier from a dataset that is formed by 4000 photos(3072*2048).Basically i want to classify the dataset to ship-image and no-ship. I am thinking of 2 solutions- ...
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1answer
13 views

Convolutional neural network block notation

The paper by He et al. "Deep Residual Learning for Image Recognition" illustrates their residual network in Figure 3 as follows: I am not a neural network expert, so could somebody please explain to ...
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Feature-to-parameter mapping in neural networks

For neural networks, can we tell which parameters are responsible for which features? For example, in an image classification task, each pixel of an image is a feature. Can I somehow find out which ...
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How can I detect the frame from video streaming that contains the clearest shot of a graffiti on city walls?

I am working on a graffiti detection project. I need to analyze data stream from a camera mounted sideways on a vehicle to identify graffiti on city walls and notify authorities with the single best ...
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Approximate evaluation for deep learning architecture

When train on big dataset for deep learning architecture, like imagenet, it takes long time to judge whether our new neural network architecture is good, say for image classification. Is there a way ...
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Age estimation task by face picture [closed]

I am new to data science and I need to solve a age estimation problem. I have some data ( 600 example people face images) and csv file ( id_image -> age ) as a result of my model work I should get csv ...
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21 views

How do I improve the accuracy of this classifier?

I have a dataset of 20000 x 3072 images for a homework assignment. This is just the training set, and the images are 32x32 and can depict one of four labels/classes, namely cars, trucks, boats and ...
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How to extract the reason behind a prediction using TensorFlow?

I created a CNN using TensorFlow2 and trained it as a binary classifier. Is there a way to extract the influence of each pixel upon the prediction? I am trying to obtain a mask similar to the ...
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22 views

Multiclassification problem [closed]

I was wondering what happens when an image not in the training set is provided to the model in a multiclassification problem? Does it just classify something which is close to this image?
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Are there any existing model weights for buildings segmentation from aerial images?

I'd like to test some deep learning techniques to extract buildings footprint from aerial imagery. I've found many references related to this problem (here, or here), but only providing the model ...
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1answer
31 views

Bald detection using Keras

I am new to machine learning and I was wondering if anyone can help by providing me with some guidelines for creating a bald-or-not image classifier, The main problem I can foresee is finding a ...
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1answer
25 views

DL model to assess quality of image

I have an idea but I am not certain that it can be modeled in a DL architecture. Let's say we have images of different qualities based on color patterns and their assessment as labels in a range from ...
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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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1answer
15 views

Active learning on image classification model

Say we have a trained image classification model. Theoretically, is it possible to update the model with only a sample without retraining? If not, is there any kinds of active image classification DL ...
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1answer
27 views

What is Image Annotation?

Why do we need to use Labelimg tool for object detection? After labeling the bunch of training images using labelimg tool which will give CSV file How that CSV file works with TensorFlow object ...
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1answer
19 views

Eigenfaces VS Deep neural network for classification

I just saw a video from Washington University where professor Steve Brunton explain how to use Eigenfaces for classfication e.g image recognition. Eigenfaces is really simple and does not require any ...
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Improve performance of my CNN model

I am working on an image classification problem. There are 876 images in the training and 600 in the test dataset. It is a multi class classification for plants. Since this is my first CNN problem, ...
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1answer
33 views

Retraining EfficientNet on only 2 classes out of 4

EfficientNet model was trained on ~3500 images for a 4-class classification: A, B, C and Neither – with accuracy of 0.985 – by someone else, not me. I'm quite new to ML. So we have this model, and it ...
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Are these images too 'noisy' to be correctly classified by a CNN?

I'm attempting to build an image classifier to identify between 2 types of images on property sites. I've split my dataset into 2 categories: [Property, Room]. I'm hoping to be able to differentiate ...
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Train building classifier for imagerial data

I am using the https://www.arcgis.com/ api for accessing imagery of aerial data. I would like to train a model that can caputure on the imagery if the provided ...
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14 views

Multimodal end-to-end deep learning

I'm thinking of working on a project that involves multiple models of data and wanted to share my thoughts to get some feedback. Think of problem of sentiment classification where the input contains ...
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1answer
33 views

What is the best way to store images in python for machine learning

I am currently working on a classification problem that requires me to classify whether an image contains cancerous tissue cells or not. Each image is 50x50x3 pixels, the 3 is for RGB values. So far ...
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Using Images uploaded in google drive in Colab

Does anyone know how to use already uploaded images in Google Drive to colaboratory for creating a trainloader? I'm creating the trainloader and model in Pytorch
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Unsupervised classification of satellite images sequences derived from time series with SOFM in python?

I have the following data: Up to 2 images per day (time series from 2015 - 2019 with gaps) for a specific region (AOI - Germany - Hesse) with 2 variables (soil moisture, precipitation). Out of this ...
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How can I make my own Neural Network model for Object Detection?

I'm using the ImageAI module in Python3 to do some object detection on some images I scraped from a video game. In testing, I am able to successfully detect normal world objects from a test photo of a ...
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Getting big losses and little accuracy on image classification model with cnn

i am currently working on image classification of artworks from this site https://www.kaggle.com/ikarus777/best-artworks-of-all-time and following the tutorial from this site https://...
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1answer
33 views

How to label images for CNN use as classifier

I have theorical question that I couldnt decide how to approach. I have tons of grayscaled shape pictures and my goal is seperate these images to good printed and bad printed. For this, I look at ...
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23 views

Real-time or offline Data Augmentation for segmenting microscopy images?

I'm doing semantic segmentation(for cells) using microscopy images. I'm exploring U-net and FCN DenseNets for the task. In the U-net paper the authors have trained their model only from 30 images but ...
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1answer
15 views

How to know the probability of correctness of a test data in a Binary Classifier

I have written a sequential classifier script using Keras, Tensorflow. Its a binary image classifier that predicts the class, given the directory path of a sample image. I want to implement a ...
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1answer
46 views

Binary image classifier always predicting one class

I am trying to design a model for binary image classification, this is my first classifier and I am following an online tutorial but the model always predicts class 0 My dataset contains 3620 and ...
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1answer
24 views

Patch wise training vs Full Convolutional Training in semantic segmentation

As mentioned in the title, what are those 2 methods? I already checked this question: Patchwise and Full training, (and the mentioned paper) but i can't really understand the meaning and the process ...
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42 views

How to understand the weights and biases for beginners?

I am newbie to deep learning, I was building my first model using MNIST dataset, I understood the full model, but one thing is a bit confusing to me. How can we get the weights and bias? Is it that, ...
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1answer
46 views

How YOLO training and prediction works for an object fall in multiple grid?

So far what I understood about YOLO, it expects training image should be divided in to fixed grid, where each grid has Label like P(object present or not), object bounding box, object classes. ...
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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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36 views

How to approach new project in Medical Image analysis?

I am working on a project in medical image analysis - Breast cancer detection. And since I am the one who has proposed this project I was wondering, what would be the (data science) steps its ...
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How to interpret training results

I am working on an image similarity network. I have around 90,000 pairs of images contain an equal number of positive and negative samples. For learning the similarity between image pairs, I used the ...
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37 views

Can anyone direct me on how to got to [closed]

I am a newbie to python. I have uploaded about 2000 images into my google drive, assigned a variable to all content in the folder and tried to split the folder's content into training and testing, ...
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How do i get to make colab read my images from my google drive?

I havee about 2000 images, I have uploaded them to my Google drive. How do I make colab see and read these images. All the images are in one folder.
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Generic object detection - unspecified list of classes and high accuracy

As a part of a small project, I would like to create tags for a set of pictures (posters). I know that if I want to recognize a lot of objects I need to have a model that was trained on a large ...
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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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Data Quality Assessment in Image Data

I'm working on a CNN model that classifies images. After scraping image files from the Internet, I found that many of them didn't look this way as described by the searching keyword (for example ...
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Is there a way to test out simple filters before committing to coding them?

Is there a way to test out simple filters before committing to coding them? Like if I want to estimate the feasibility of recognizing some features from images. Or to estimate the effort/...
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2answers
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Can colored images have more than 3 channel values?

I was reading this well-known paper and noticed something in figure 1 below: It says in the caption (The number of channels is denoted on top of the box). You can see that the number of channels is ...
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1answer
26 views

Pretraining a neural network to teach it general information

Let's say that I want to train a neural network to recognize symptoms of severe dehydration in distance runners visually. Runners tend to finish races either overhydrated (hyponatremic) or dehydrated, ...
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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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1answer
27 views

How do I get the values of y_true and y_pred in the confusion matrix?

I am using the weka program and i want to know the values of y_true and y_pred through confusion matrix that appeared in the classification results , because I want to calculate the balanced ...
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Using Orange3 to embed the image, the raw data need to upload to a remote server?

the official document talk about : Image Embedding reads images and uploads them to a remote server or evaluate them locally. Deep learning models are used to calculate a feature vector for each image....
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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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