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Questions tagged [image-classification]

The tag has no usage guidance.

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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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14 views

New cluster or classification methods for medical image processing

I'm looking for a topic for my thesis, which deals with either clustering or classification of medicial image data (Ct images or MRI images) of the human brain. Particularly interesting would be ...
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20 views

Which clustering algorithms are used in medical image processing? [on hold]

I'm looking for a topic for my thesis, which deals with either clustering or classification of medicial image data (Ct images or MRI images) of the human brain. Particularly interesting would be ...
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0answers
20 views

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
40 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
21 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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0answers
15 views

Clustering of Images - my own set of images [closed]

I am taking images of a few lamination boards used in house furniture. With the given set of lamination images (JPG/PNG), I want to cluster them into different groups based on different attributes ...
0
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1answer
14 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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Don't know how to start building a floor and wall material classificator

I need to, given an indoor image of a room, to detect the materials of the floor and the wall (and maybe the roof too). I've started looking for open source repositories similar to this and found ...
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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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0answers
28 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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25 views

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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0answers
35 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
31 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
38 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
28 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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0answers
8 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
28 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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0answers
10 views

Clustering images of same group

I have 3 groups of images (different domains) like let's say for example (1K images in night, 1K images in day, 1K images in rainy weather). I am looking for a way to do clustering for these 3 groups,...
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2answers
60 views

How to use Autoencoders for outlier detection on images

I have a bunch of images takes 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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0answers
14 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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0answers
21 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
11 views

Why is it possible to train a semantic segmentation neural network like U-net/Tiramisu from scratch using small data-set like few hundreds

Why is it possible to train a semantic segmentation neural network like U-net/Tiramisu from scratch using small dataset like few hundreds. While for the classification task, it is not possible to ...
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2answers
41 views

How to build classifier if only 1 image per class available

If I have only 1 image for each of 10 classes, what is the best way to build an image classifier? The images themselves are large (1200x1600) and of good quality. For example: Or similar images from ...
2
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1answer
40 views

How to analyze CNN model summary and improve it?

I am using a CNN (adapted from a few links on the net) for an image classification task. There are about 8000 images of size 128x128 each. They are of 13 different classes. Following is output of <...
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0answers
13 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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0answers
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Image processing - How to store image list and its labels in one-hot encoded ndarray?

I got a folder with 1976 training images. Each image has a shape (118,128,1) (greyscaled images). I created an array with all the images like this: ...
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0answers
52 views

Combining 2 Neural Networks

2 images as input, x1 and x2 and try to use convolution as a similarity measure. The idea is that the learned weights substitute more traditional measure of similarity (cross correlation, NN, ...). ...
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0answers
22 views

target and logits in the Mask-RCNN

I tried to implement the loss function in the mask-RCNN model using the Tensorflow tool. I used the average sigmoid cross entropy loss function: ...
4
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1answer
49 views

What is difference between intersection over union (IoU) and intersection over bounding box (IoBB)?

Can someone give a detailed explanation IoU and IoBB along with that the differences between them.
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1answer
34 views

What methods can be used to detect duplicacy in image dataset?

I want to remove duplicate images from a dataset of 50Million images. What is the best method to detect all the duplicates? Do you think one shot learning is good for this?
2
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1answer
71 views

Overfitting in Siamese Network

I am trying to train a Siamese network for an application very similar to this and this. From what I have read about training Siamese networks dissimilar pairs of images outnumber the similar pairs ...
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0answers
34 views

For EEG analysis, why is it more efficient to use the raw data than images of the data?

Data Science publications for EEG analysis like EEGNet: A Compact Convolutional Network for EEG-based Brain-Computer Interfaces use the raw EEG data (see: github vlawhern/arl-eegmodels ) rather than ...
2
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3answers
271 views

Unbalanced training data for different classes

What precautions do I need to take while trying to develop a CNN for classification of images if there is much more training data for one label. For example: ...
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0answers
14 views

Magnification factor in image classification

If a CNN is trained on images focusing on an object, will it also recognize when multiple such objects are present in the image? For example can a network trained on single flower images also ...
2
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1answer
34 views

Data augmentation for the inputs of CNNs to identify flowers

I want to make a neural network to identify flowers from images like this: or similar images e.g as on https://www.pexels.com/search/flowers/ I want to use a CNN for this as in https://...
0
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1answer
14 views

What does the co-ordinate output in the yolo algorithm represent?

My question is similar to this topic. I was watching this lecture on bounding box prediction by Andrew Ng when I started thinking about output of yolo algorithm. Let's consider this example, We use ...
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0answers
30 views

how to load label data presented in raster format into Keras/Tensorflow

I want to use CNN network to segment 2 objects (binary: "0: object not present 1: object present") into shapes but I have an issue with data. The train data is 150 images and in "jpg" format and the ...
2
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1answer
48 views

Neural Network for classifying humans

I am currently searching a neural network that can classify if there is a human in an image or not. I checked the ImageNet dataset, but the 1000 classes there contain nothing like human or person or ...
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2answers
29 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 ...
0
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1answer
22 views

Orange3 Image Classification

Is the attached workflow correct in case of training and testing with different data sets? Is the attached workflow considered "transfer learning" since my images are not related to the images that ...
2
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1answer
24 views

Conceptual question on CNN and any multi layer neural network (Part 2)

I have read a number of tutorials and online lectures (https://ujjwalkarn.me/2016/08/11/intuitive-explanation-convnets/) but none of them mention the rationale for selecting a particular design. How ...
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0answers
46 views

Neural Network Architecture for Identifying Image Copies

I have a large image collection and wish to identify the images within that collection that appear to copy other images from the collection. To give you a sense of the kinds of image pairs that I ...
2
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1answer
69 views

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 ...
3
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1answer
34 views

How to check two images(one is original image and other one captured by mobile) similarity using deep learning?

My problem statement is - In my project, original image of product is stored in database. Now whenever any person uploading that product's camera pic(for internal audit process) then I need to verify ...
5
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1answer
222 views

how to interpret predictions from model?

I'm working on a multi-classification problem - Recognizing flowers. I trained the mode and I achieved accuracy of 0.99. To predict, I did: ...
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1answer
44 views

resampling image takes a large amount of time

I am working on medical image exactly CT scan images, there is a method for reading these type of images, also another method for resampling, the code for two methods shown below: ...
1
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1answer
62 views

Image classification if rotated version same

I asked this question on stackoverflow but was advised to come here. I have some images to classify. I see that Convolutional neural network may be best for this, e.g. here. However, for my images, ...
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2answers
36 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 ...
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1answer
22 views

How to handle image classification network where output classes can be subsets of one another?

For instance, if I wanted a train network that can output van truck sedan vehicle pedestrian does it make sense to only train it on van, truck, sedan, and pedestrian and then make "vehicle" a ...