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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17 views

How to improve the accuracy of the test set of LRCN-based video classification model

An existing LRCN-based video classification model consists of resnet152 provided by torchvision and an LSTM layer, and this model achieves 92% accuracy on the UCF-101 test set. The input range of this ...
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Best image recognition API to implement for eCommerce Lifestyle/Sculpture site

I'm planning an eCommerce site currently. We are likely running WooCommerce and looking to implement Algolia for our search features. We feel that for our particular purposes, a visual search would be ...
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12 views

Classifying visual environment in Tensorflow CNN (video analytics)

I am given a selection of videos of users exploring simulated 3D enviroments (kind of looks like the Sims video game) and I am tasked with being able to classify each room using a tensorflow framework....
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CNN application assessment

I would be glad if someone could give me some hints and assessment for the following project. (I'm relatively new to ML and DL and having only a little theoretical knowledge) My goal is to build a ...
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Predict saved model from live camera for multiclass recognition

I have developed a model with relative good accuracy. I am trying to predict new input image from live camera by detecting or set a bounding box where only hand region are capture. I used the code ...
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29 views

Classification report and confusion matrix problem

I am working on sign language recognition system using HOG and KNN. I have 26 classes of 180 images per class. The dataset was split into 1/3(67%) for tanning and 2/3(33%) testing after feature ...
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what is the best way to learn a mapping of images of the size (20x20) to [0,360]?

I have an algorithm which takes an image (20x20 pixels) of an optical shape of a rotating nanoparticle and maps it to an angle in [0,360]. currently the mapping is done by a time-consuming least ...
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25 views

Best approach to clustering images

I am new to unsupervised clustering and I wish to perform clustering on a dataset of 512 images. I want to output n clusters where each cluster holds images that are similar to each other. I do not ...
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Removing irrelevant faces from a photograph

I try to do clustering over a collection of photographs from parties/weddings/etc... (where each photograph would usually contain multiple faces and large background crowds). I use the ...
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1answer
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Dummy vectors and performance measurement for vector search Face Recognition

I have about thousands of person face (from celebrity dataset LFW), which each person represented by 512 x 1 vector. I stored it on vector DB to build face searching system using embedded feature (...
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What is the impact of changing image sources on an image recognition?

I have a fairly general question pertaining to an image recognition ML model. I’ve recently developed an image recognition model using a single camera collecting more than 5000 images and then trained/...
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Siamese Neural Network for massive class variation

I have case to check whether the person has been registered into a database,and if the images has high similiarity with one of the image in the db, i want to retrieve the image information (name, id, ...
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Using machine learning to find the most similar image that contains another image

As the title states I want to use ml (maybe some kind of CNN autoencoder?) to find the most similar image (I have a list of 10k+ images) within another image. I am currently just using opencv with ...
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Basic doubt regarding “training” of a YOLO model

So I have just recently started exploring machine learning, and for a project I was required to train the YOLO v5 model. I first tried it on the coco128 dataset:https://www.kaggle.com/ultralytics/...
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29 views

Count repeating “objects” in a picture

This is my first data-science project and I would love to get some guidance to know how to get started. My problem is the following: I want to count objects that are in a picture. This picture has a ...
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Can I get some advices on inferencing people from upwards using Yolov5?

I'm trying to inference people from upwards and count them using Yolov5. I know the controversy between yolov5 and yolov4, but for me, Yolov5 is more easier and reliable to use, also the setup. I have ...
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CNN regression. help to improve current model [closed]

I have time series grey scale images that show movement of fluid with different densities. I want to predict a pixel value for time t, with (t-3),(t-2),(t-1) 2D images as inputs. I am figuring out how ...
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Best practices for memory management in image processing

I'm relatively new to data science, and I'm trying to create a CNN model for the Kaggle melanoma competition. I've created the following two functions to transform a folder of JPEG images to a Numpy ...
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24 views

Pre-trained models for classifying images with more than 3 input channels

I am working on an image classification problem. My input images have 19 channels. I tried building a CNN model that can handle such inputs. Now I want to learn transfer learning along with this. But ...
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1answer
36 views

best similarity measure for images with different angles

I want to compare different images (where the images are of the same setup but the angles with which the images are taken are different). I want to obtain some sort of similarity score. I tried using ...
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Find starting point and stopping point of noisy pulse

I have noised pulse signal like these. I need to identify starting point and stopping point of each peak. First and third pictures have 2 pulses with noise. Second picture has single pulse with noise. ...
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Split npz Dataset into Train/Test using Sklearn [closed]

I have a dataset of faces stored in an NPZ file that I would like to train it on Siamese Network. To do that, the dataset must be split into train / test using Sklearn. However, when I run the code to ...
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What kind of approach should I apply for face validation with using deep learning? [closed]

My research task is face recognition in cars with using deep learning method. Actually, in example we set an driver randomly and then the question is: Is this person driver or not? So i created an ...
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Finding the position of an arbitrary object in a static image?

One common object detection scenario involves finding trained models in an arbitrary scene. For example, we can train a model to understand what a "bicycle" looks like, by providing various ...
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2answers
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ResourceExhaustedError when building Sequential model

i have a big problem when trying to build my model, ...
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predict multiple letters in pixels matrix

I have a multilayer perceptron model that is trained to recognize handwritten English letters from an image. In the training set each image matrix had 784 pixel values. The labels of these images ...
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1answer
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How to manage memory constraint and increase speed for 1 vs rest image similarity comparison for over 100k images for computer vision?

I'm looking for ideas on how to do things in a better way, efficiently when using Machine/Deep Learning. I am working on a search improvement problem using Computer vision where I am thinking about ...
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Keras model has a good validation accuracy but makes bad predictions

I have this model which takes 9000 images in a dataset containing 96 categories of traffic signs, each category has more or less the same number of images (about 50). This is the model I made but ...
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142 views

Difference in features generated by same filters for color and grayscale images?

Would there be ay difference between the features generated by CNNs if they are fed with same image in color and grayscale format. If I am performing classification with same network for let's say ...
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1answer
25 views

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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1answer
25 views

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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2answers
302 views

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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1answer
67 views

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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1answer
31 views

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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39 views

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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