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Questions tagged [image-classification]

The tag has no usage guidance.

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Detect presence of text in image

I want a simple image classifier to detect (No need to recognize) whether an image contains text or not. Some of the approaches I thought of: Single class image classifier with a Threshold Fast/...
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Deep learning performance on classifying simple geometric figures

I'm trying to find papers or just performance data on classifying simple geometric shapes, e.g. the first six convex regular polygons. The input data is computer graphics generated, producing high ...
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Creating an image data set from a set of 2D points?

I have N sets of x and their corresponding y coordinates. e.g. x_i = [1.1, 2.3, 3.5] & y_i = [-1.1, -3.2, -5.2]. These coordinates represent an image, which may belong to one of two classes. I ...
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1answer
20 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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Recognition of objects in almost plain background

I want to recognize climbing holds in a climbing wall. I thought about implementing my own heuristic algorithm for background detection because it's almost plain, but I was wondering if this kind of ...
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Make image label prediction from Chainer CNN model

I have train dataset of 8000 images and labels. Validation set consists of 1957 images and labels. The test set contains 2487 images. Each image contains White Blood Cell images. WBC is divided innto ...
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Using deep learning to classify similar images

I'm currently using Keras to build a deep learning network (CNN for now) in attempts to classify images which are similar-ish, produced through simulation. The images in question are generated as ...
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“10-year-challenge” data for age algorithms? [closed]

Both on FB and IG, I see people posting themselves before 10y and now. I have no idea how this challenge started. Could it be a way to collect a colossal amount of data, that could be used to train ...
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1answer
19 views

Generated training set on convnet

I have a dataset with roughly 800 images that are classified in 18 classes. The classes are spread unevenly, with some classes having 30 images and others having 5. In order to increase my dataset,...
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1answer
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Does it make sense to train a convolutional neural network on lo-res, use on hi-res pictures?

this is my first machine learning project and actually also my first question here. I am a novice to machine learning with a background in theoretical physics. I want to use a CNN to detect scratches ...
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1answer
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Training a floor detection model: use full room images or only the cropped floor?

I'm trying to build a floor type image classification model.There's an open dataset called OpenSurfaces containing images segmented by the material type of every item appearing on a room. Something ...
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CNN architecture design guidelines when doing multilabel classification of 1K possible “easy” classes

in my problem I am given a website screenshot and I need to detect which logos appear on it (nike, youtube, pepsi etc.). From what I have read, this is usually tackled with template matching. However ...
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1answer
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Overfit from the loss curve

I have a binary classification task. I have shown the loss curve here. I have decreased the learning rate by 1/10 every 15 epochs. There is also dropout put in the model. As you can see, I am trying ...
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1answer
24 views

Mask RCNN: Random predictions during inference for the same image

I recently trained the Mask RCNN (matterport's implementation) on some satellite images, but during inference mode, I'm getting random predictions for the same set of weights for the same image. That ...
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30 views

Cannot interpret feed_dict key as Tensor: Tensor Tensor(“Placeholder:0”, shape=(3, 3, 3, 32), dtype=float32) is not an element of this graph

I have a working Keras model that makes predictions great in the repl but fails to load in a Flask app on accessing multiple times.. K.clear_session() and graph = tf.get_default_graph() did not work ...
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1answer
15 views

Performance of CNN based deep models with number of classes

How does a given deep cnn model performance vary with number of classes in tasks such as classification, object detection segmentation? For example mobilenet v2 gives around 90% accuracy on ...
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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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32 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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33 views

How to approach training a machine to read a form

After many rewrites I'm still not entirely thrilled with how I've presented this.... please delete if inappropriate. Background As part of my job, we record observations on underwater paper and then ...
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1answer
27 views

Can Reinforcement learning be applied in image classification?

So my question is can Reinforcement learning be applied in image classification?
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2answers
25 views

Tattoo Image Recognition - Should I Crop Training Data Background

I am trying to train a neural network to detect objects within a tattoo. I couldn't find any existing labeled dataset so I need to manually create and label my own. I only understand the basics of ...
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1answer
49 views

How to benefit Data augmentation when it yields to different classes

I'm trying to classify rooftop sky images orientations, whether it is horizontal or vertical. Knowing that the most obvious feature here is known: orientation. I can simply augment each class by ...
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Which model for Kaggle Diabetic Retinopathy Image Dataset?

What model is the best to use on this Kaggle dataset, such that there is about a >70% accuracy but is not too resource intensive for say a desktop? Is this even possible? Should I go for a deep ...
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1answer
23 views

Signature verification - machine learning

I have to do a project on signature verification. My goal is having a program with two images as inupt (one is a genuine signature of a selected subject and the other one is the one that I want to ...
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1answer
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Feature selection/reduction techinique for combination of features in image processing

I have a combination of features extracted from 3 descriptors, namely GLCM based feaures(correlation, homogeneity,energy and contrast ), Local binary patterns (256) and discrete wavelet transform ...
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segmentation of brain tumor in MRI images

I have a dataset of brain tumours images. and I have to build a model to classify the malignancy grade of these tumours. The size of the tumours varies from small to large. The ROI are already ...
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1answer
29 views

RGB Image Segmentation using Clustering

I want to apply some segmentation on a dataset for preprocessing purposes. I have tried the "otsu thresholding" approach in order to segment the image. It's a good method, however, I think a ...
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1answer
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Is it possible to train this image classifier?

I'm writing a mobile app that will enable a user to scan a Craft Beer Label from a bottle, tap, six pack, etc. The scan will only work for my customers who are the Brewers themselves, so I will have ...
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2answers
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Classifier not predicting real data

I'm trying to train a classifier to recognize my own signature. This is how I built my classifier How did I collect data? Signed on a piece of paper for 50 times and created 50 images out of it. for ...
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0answers
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Any consideration for image classification when one class has generally one particular color

I am trying to predict rooftop orientations among: horizontal, vertical, flat, unknown. The particularity of horizontal and vertical rooftops, is that it's color generally is reddish, the reason of ...
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2answers
47 views

How to transform a folder of images in a csv file

I have a folder with a lot of images that I want to use to bild a classificator using a SVM model in python with sklearn. I've always used csv file as train/test set with sklearn, how can I make it? (...
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2answers
33 views

Counting non-overlapping objects in a semantic segmentation prediction mask

What is a good way to count the number of roofs detected by a CNN in the following output on the right (produced using keras/tensorflow): I need to count the discrete shaded areas and estimate their ...
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1answer
46 views

Best way to deal with realistically imbalanced dataset for Regression problem

I have a dataset where each object has a label between 0-1. Objects with label = 1 are very common but those with label = 0 are very rare. I am interested in predicting the label in unseen data. NOTE:...
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2answers
44 views

When using Data augmentation is it ok to validate only with the original images?

I'm working on a multi-classification deep learning algorithm and I was getting big over-fitting: My model is supposed to classify sunglasses on 17 different brands, but I only had around 400 images ...
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how can I get the original pixels that lead to the decision in CNN ? is that possible?

I work on medical images, 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, I get the features maps, now I want ...
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2answers
60 views

How can I augment my image data?

What are the correct and common ways to normalize image for CNN? I used to work with text and it was pretty straightforward. Removing stop words, clean text from noise, tokenization, stemming etc. ...
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1answer
35 views

Does image resizing lower the prediction accuracy of MLP?

I am implementing a vanilla neural network (MLP) to do image classification in python using tensorflow on images of honey bees to detect their health status. The images in my dataset are of different ...
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1answer
22 views

Higher dimension data visualization in Matlab/Octave

I am working on sparse recovery for a classification task. I use Pine hyperspectral dataset which is a freely available dataset and this image contains 200 Dimension (Depth/channels/bands). In ...
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Multi-inputs Convolutional Neural Network for images from the same class

I want to create a multi- input one output CNN model using Keras. The model inputs are images (pair of images in different dataset) from the same class, and the output is the class. The model ...
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129 views

Examples for multi-input Convolutional Neural Network

I want to create a multi inputs Convolutional Neural Network (cnn) that takes two inputs and produces one output of the inputs class by using Keras. I searched for resources that explain multi inputs ...
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Framework to build object detection model to predict identical or closely identical images

I am looking for an approach to build Image classification and Object detection model for a large category of items (About 200K) but with the very smaller number(4 images on each) of subject input on ...
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76 views

Regularization in Python Code

I tried to understand the code provided below. This code is for Regularization using python. ...
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1answer
40 views

Does CNN take care of zoom in images?

Suppose a convolution neural network is trained on small images of an object, say flower, as in following 3 training images: Will this CNN correctly classify if the same object is present in zoomed ...
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1answer
166 views

Keras ImageDataGenerator.flow_from_directory doesn't find images

I'm working on a deep learning (CNN) problem. I have structured my images into folders correctly (I think), like this: ...
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0answers
35 views

Dataset Creation for Images

I am creating an image dataset of objects. We have 15 classes of objects and need to provide a color to the objects also. What ...
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10 views

How is it that Compute the features by the CNN without targets of train data

Excuse my ignorance, but I am a newbie when it comes to deep learning in general. I am trying to run a training algorithm on train data which is images using VGG16 network part of trained models on ...
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1answer
33 views

How can we use machine learning to distnguish between similarly looking images

How can I build a model which can distinguish between Milk and Phenyl? I want to predict whether a given item is edible to eat or not. If I train a model with thousands of photos of Milk and Phenyl ...
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2answers
189 views

How to use Autoencoders for outlier detection on images

I have a bunch of images taken from a camera showing a pipe and would like to detect if the pipe is leaking or not. There are very few examples of leaking pipe in the data set. So considering this ...
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15 views

Performance degradation from video compression

I have two datasets. The first are frames saved as pngs (lossless) from a live video feed, and the second are the same frames taken from an mp4 (H.264 compression). Training the same image classifier ...
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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 ...