Questions tagged [image-recognition]

A form of signal processing where the input is an image. Usually treating the digital image as a two-dimensional signal (or multidimensional). This processing may include image restoration and enhancement (in particular, pattern recognition and projection).

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11 views

create annotation of large images dataset

I have a dataset related to plant disease. the dataset has 70k images and I want to annotate images with a bounding box. I try for annotation LabelImg but it so time-consuming. is there any other ...
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Sneakers representation learning

I am trying to make a model which would take an image of shoes as an input and output a meaningful N-dimensional embedding of the shoes, so that they could be searchable/comparable/clustered and used ...
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Image requirements for face recognition [closed]

I am trying to make a tensorflow lite model for recognizing celebrity faces. I have 3 classes each having around 100 images. The input files are cropped and contain just the face and little area ...
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Is there a way to increase the validation accuracy for this model of image recognition?

I'm really new to machine learning, and this model is supposed to differentiate between rock, paper, and scissors. ...
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How to correctly label images with multiple objects

I have 3 types of images: A: Images of apples B: Images of bananas, however some of these banana images also contain apples in the observable background Is it enough to just label the bounding boxes ...
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Does resizing the image size, reduce the quality of the images in CNN?

I am doing a project for cancer recognition. My data set has hunderds of images but not of equal size. I wanna resize them to the size of the smallest image. But I am wondering do you think using the <...
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Understanding arcface, sphereface, and their differences

I'm a beginner in ml and I want to make a facial recognition system. While going through the research paper I realized that I'm losing the intuitive sense of the computations. I'm not from a ...
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Create a model that can extract only specific data out of receipts or invoices?

I'm trying to build a model that is capable of identifying only some of the information on receipts and invoices. All the documents having different structure in image format. Sample Data : Click here ...
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Machine learning algorithms for identification and classification of Microorganisms

https://www.google.com/search?q=Viruses+images&tbm=isch&ved=2ahUKEwiB9-fsoL3sAhUJyHMBHWRZB-sQ2-cCegQIABAC&oq=Viruses+images&gs_lcp=...
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Would descriptors of the last hidden layer of two different CNN be the same?

I am given a dataset of 2D medical images. I am asked to extract image descriptors from the hidden layer of the neural network pre-trained on the ImageNet dataset. I consider to use two networks: ...
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With one pretrained CNN model do I get only one vector of descriptors for an image?

I am given a dataset of 2D medical images. I am asked to extract image descriptors from the hidden layer of the neural network pre-trained on the ImageNet dataset. I consider to use two networks: ...
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Is it possible to guess a pretrained CNN accuracy beforehand?

I am given a dataset of 2D medical images. I am asked to extract image descriptors from the hidden layer of the neural network pre-trained on the ImageNet dataset. I consider to use two networks: ...
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Can I tune a model after training it? (Convolutional Neural Network & Classification)

I am relatively new to Data Science and I've recently embarked on a project. Long story short, I've trained a CNN model to distinguish between Male and Female genders. However, I wish to tune my model....
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Retrieve symbol outline from image

We have a pet-project for generation of words out of symbols found on the image. Currently, we are processing symbols on the image using Photoshop, convert those to .png files and then they are ready ...
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Machine learning algorithms for Geometrical objects shapes identification

Are there Machine learning algorithms which will take input dataset of all geometrical objects shapes as images in gif,jpg,tiff formats & output the geometrical shapes names? i.e. Geometrical ...
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Why does my CNN validation loss increase immediately, even with lots of data?

The Issue I've been working on a regression CNN implementation to predict time series data and have run into an issue where my validation loss and training loss diverge immediately during training, as ...
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Machine learning algorithms for interpreting Companies brand/s logo/s

https://www.google.com/search?q=Company+brand+logos&client=ms-android-lava&prmd=isnv&sxsrf=ALeKk0218I-1fMd-hNXX_fAF8_fu6EOotA:1600348128111&source=lnms&tbm=isch&sa=X&ved=...
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Differentiate twins, triplets images in Computer vision field

https://en.wikipedia.org/wiki/Computer_vision https://en.wikipedia.org/wiki/Twin https://en.wikipedia.org/wiki/List_of_triplets Will there be challenges in Computer vision field to differentiate ...
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Best object detection model where inference speed is not a factor?

As in the question I’m wondering what is the current best model for object detection in images where inference time doesn’t matter? Thank you in advance.
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How to recognize plaid / tartan?

I have an idea for a side-project: I'd like to be able to start with an image of a Scottish kilt, and automatically determine what tartan is used. For example, this is my (MacGill) tartan. Ideally, I'...
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Tagged dataset with photos for race detection

Looking for the tagged dataset, because I would like to identify race by photo. I tried using the UTKFace dataset from Kaggle, but it outputs hispanic and Arab people on images as ...
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Why it is reshaped the last layers of VGG_UNet segmentation model?

I want to do a multiclass segmentation task using deep learning (in python). Here, is a summary of vgg_unet model that is mainly collected from GitHub. So, in my dataset 8 labels are available. So, at ...
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Image classification tool for detection of small features

I have a dataset of images of damaged cars. Each image has an associated mask of overall damage and severity index of each type of damage. Unet successfully predicts the overall mask of damaged area ...
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Training images for gender and and age detection from face

Can someone please tell me if it is feasible to train my own set of facial images to detect gender and age without using any cloud architecture or paying some amount of money ? And , on an average how ...
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Ship detection on high resolution unlabeled image dataset

I have been given a dataset of 4000 high resolution photos of different size of ships entering a port, that need to be clustered in order to execute the following tasks 1)Ship detection 2)Count the ...
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What is the difference between HLC (Histogram of local features) , CSS ( color self-similarity) ans MDST (Max DisSimilarity of Different Templates)

I'm new to computer vision and have been researching for Master thesis purposes in Detection algorithms and the techniques used in each. As I arrived to the point where alot of papers showed the ...
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Unrelated output by pytesseract image_to_string function

I'm trying to extract text from an image but pytesseract is giving a totally different output, the image attached below output is "Werle" (complete different word and characters), I tried ...
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Best NN for image pattern recognition without classifier

For images like this I'm trying to split up the cells (the different rectangles). The cells, can vary in size, brightness and so forth. I tried multiple ways using OpenCV for about 5 days, I almost ...
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Varying Image sizes in Tensorflow Malaria dataset | Dealing with unclean tensorflow data

I am trying to build a CNN based image recognition system for the Tensorflow malaria dataset. I loaded the dataset (~27k RGB images) using conventional tensorflow_datasets syntax. After some data ...
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Image classification using cnn [closed]

I did image classification using CNN and it successfully classified the images but How to save predicted images to separate folder for example i have two classes cat and dog after prediction how to ...
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Siamese network do not compare pictures correctly

I have a siamese network trained for recognizing products. Some of these products are recognized properly but some of theme not. Images in each class are similar (For testing this architecture I had ...
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Why siamese network using ResNet50 architecture has worse results than network trained from beginning?

I am trying to build product recognition tool based on ResNet50 architecture as below ...
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24 views

What kind of images/objects are the most easy for neural networks to detect?

I need to design a marker image that should be detected by the neural network. I am aware that it is not a complex task just to detect an image and this can be done with OpenCV alone. However the ...
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How to deal with images with textual noise?

I have a dataset of images collected from google and bing images (scraped). basically I want to classify these images into binary classes (positive, negative). Images that contain a text originally ...
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Can I plug models like Linear Regression into a CNN feature map result?

I was learning about image recognition on the Orange Software and I saw that I can feed my image database into a CNN(they call image embedding) that has as output a feature map of the image and then I ...
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What pre-processing of the image is needed before feeding it into the convolutional neural network?

I can't figure out what preprocessing of the image is needed before feeding it into the convolutional neural network. For example, I want to recognize circles on a 1000 by 1000 px photo. The learning ...
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CNN + LSTM dimension error

I am building a model to predict if a video images are describing a sleepy person or awake person. I have trained a CNN custom model to classify blink eyes or not. Now it's time to join these Conv2D ...
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Annotating images for CNN; how to label partially obscured images

I am annotating images to train a CNN classifier, some images are partially obscured, generally speaking what is the intuition and advice in these situations, should a partially obscured image be ...
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how to compare two images and show the difference in a new image?

I want to compare two web pages images using computer vision techniques. show what are non-unique portions comparing both images. which part image1 not exist in image2 vice versa.
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52 views

What is the origin of YOLO/darknet coordinates

I am aware of that darknet/yolov3 outputs relative coordinates, would the coordinate (0,0) be at the bottom left, or at the top left? I am confused as opencv2 seems to have the ...
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the size of training data set in the context of computer vision

Generally speaking, for training a machine learning model, the size of training data set should be bigger than the number of predictors. For a neural network, or even a deep learning model, the number ...
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How to train a Model which can check whether image is from existing classes or not

I have given with a image dataset of 1000 classes , each class has 100 images. Now My requirement is to train a model which will take a image as input, and it should answer whether the image is ...
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1answer
44 views

Binary Classification of a ship Dataset

What are the best options for a big dataset classification? I am thinking of 2 solutions- 1.Autoencoders 2.PCA(Principal Component Analysis) I think the first approach is better.Does it works for ...
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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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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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133 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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17 views

Image-to-Image Regression for GO territory classification

I'm trying to implement a neural network that is able to generate an image indicating territory occupation given a board state for GO (a strategy board game). Input images are 19x19x1 grayscale images,...
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35 views

How to recognize overlapping digits?

I've got a set of images with overlapping digits which need to be recognized. The task seems a good fit for neural networks but the issue is that they are used to have inputs as single digits but in ...
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How do I get started with machine learning and image recognition?

I'd like to get started with machine learning, specifically image recognition. I know that Python is the most popular language for ML since it's easy to pick up and there's tons of libraries for it. I ...
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Keypoint detection from an image using a neural network

I am trying to design and train a neural network, which would be able to give me coordinates of certain key points in the image. Dataset I've got a dataset containing 1800 images similar to these: ...

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