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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AutoEncoders feature extraction

Is it a good idea to extract features from pre-trained, the last 1x1 convolution removed U-NET/Convolutional Autoencoder? Data will be similar and the model will be trained for image segmentation. I ...
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Image recognition of specific animal drawings with body parts (tiny dataset)

I have an assignment for a class where I need to visualy detect specific animal drawing models, and extract the colors from such model after identifying the different body parts. My problem is that my ...
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Same layer for different purposes

We are using convolution for different purposes, image reconstruction for output of transposed convolution in the decoder part of U-NET, as FCN at the last layer of U-NET, and feature extractor in the ...
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CNN model with images - 100% accuracy on validation and test sets with limited data?

I have a binary classification problem (e.g. if there is a human in the room or not) with a small dataset of images from a thermal camera. Originally, those were 7 videos, which I have converted into ...
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euler number of image returns a double

I read that euler number is the Number of objects in the region minus the number of holes in those objects , it should then return an integer. why does it return values like 54.25
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CNN Eliminate Wrong Results

I extracted images of human faces from the videos, but the model also recorded images without faces. I wrote CNN for emotion classification. In the obvious pictures, the probability is closer to a ...
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How to find arbitrary object (toast) using image detection

I'm a beginner, I've done object detection using Haar Cascades on faces as well as ImageAI. So maybe not a complete beginner. I'm working on a simple regression project for my resume, predicting low ...
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Object Detection without annotations and labels

Problem Statement: I am given 2 sets of images. All the images in both sets are without annotations and labels. First set : a set of images of the grocery store shelves (captured in the grocery stores)...
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How to train a form recognizer

I'm working on a project in which I need to build a form recognizer that, given a form image, returns de key - values pairs. As I just got started, I wanted to hear some opinions about what should I ...
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Comparing two images for similarity

Comparing two images for similarity What are the best softwares available for comparing two images having similarity and differences? Example: Margaret Thatcher & Enid Blyton.
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Is there a Machine Learning/AI model for recipe ingredients?

Working on a project that uses a mobile device camera to add ingredients to a users database, and im wondering if there exists a way/MLmodel that classifies ingredients into simple classifications or ...
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Floor plan analysis

Given an image of a floor plan, is there a known algorithm I can use to understand measurements of all apartments present ? (for example, that means in the attached picture understanding there are 4 ...
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Where can I find a good image repair model?

Where can I find a powerful learning-based algorithm for image inpainting so that I can, say, remove certain pixels from an image, have the model fill in those pixels, and return the new image all in ...
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What computer vision task does describing the features of images comes under?

I have a very noob question - Is there a computer vision task category for the task when you describe the objective feature of the images like - brightness, focus, artefacts and hence classify the ...
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Can you use a Confusion Matrix for a image detection problem?

I have read the classic examples of using a Confusion Matrix for a classification problem. ("Does a patient have cancer, or not?) The ML system I am working with is for detecting objects in an ...
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Determine postion of dart in dartboard

I'm new to machine learning and I want to built my first project. I decided to write an application which determines the postion of a dart in a dartboard. The neural network would have the following ...
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Image size for training transfer learning model for object detection purposes

I am trying to build transfer learning model to detect objects from video streams. There will be at least two or three different objects (classes) which are quite different from each other. The ...
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Algorithms to do a CTRL+F (find object) on an image

We all know the CTRL+F "Find text..." feature in text editors / browsers. I'd like to study the available algorithms to do something similar on an image. Example of UI/UX: let's say you have ...
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How can I correctly identify an item within a larger image, but also detect if the item is the correct orientation?

I have some machinery at work with a small sticker I am trying to detect within a larger image. I am familiar with object detection techniques based on a trained classification model, but to further ...
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Using Object Detection or Image Segmentation without labelled input data to build a dataset to then be manually labelled?

I'm looking to build an object detection model or image segmentation model, ideally the latter, which will identify and label objects from satellite imagery but I don't currently have any labelled ...
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Is there any difference between classifying images by their type and by the objects they represent?

Let us suppose that I would like to train a machine learning model for classifying images according to their types (for example, photographs and drawings). The techniques that I can use for this would ...
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Trouble with anomaly/novelty detection (on microscale) - need easy practical guide with Keras

I am relatively new to the field of machine learning. However, I already have solved simple image classification tasks with Keras (for example building CNNs and classifying MNIST...). The rough deep ...
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Reducing Validation loss for Triplet Loss Embeddings

I'm trying to create a facial recognition detector using triplet loss followed by a kNN algorithm. I have roughly 10000 input images with 3 different classes, input size is 80x80. Model structure uses ...
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Can i segment/crop out image using image processing?

I have a large dataset of bottles. I want to train a model with this dataset. But before feeding the input images to the model I want to crop out the bottle from the background. Is there a way to do ...
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How to estimate Coal Level in a Coal Train

I want to estimate coal level in each of the bogies in a moving coal Train. I want to get the percentage of how much it is filled. Can anyone please suggest me how should I proceed?
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Best smoothing image techniques for digit recognition

There are several ways to smooth an image like - Gaussian Blur Median Blurr etc. as mentioned on the page - https://docs.opencv.org/4.5.2/d4/d13/tutorial_py_filtering.html Suppose I have an image ...
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Digit recognition images for testing

I made a python program to solve the digit recognition problem that is mentioned here - https://www.kaggle.com/c/digit-recognizer The sample dataset that is given on this website is basically pixel ...
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How to create COCO format data out of list of boxes

I have $N$ images. I have a script that extracts boundary boxes of an object that I am interested in. For each image, I may get $m$ boxes. There is only one item that I am interested in which is cat. ...
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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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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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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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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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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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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 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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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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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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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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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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