Questions tagged [object-recognition]
For questions related to object recognition, which is the problem of determining the type/class/category of an object in the image, so object recognition could also be called object classification. This is different from object detection, which is either used to refer to object localization (i.e. find the coordinates of the object in the image) + object classification, or just object localization.
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NN Architecture for the detection of "sparse" Objects
I have a document digitalization task where I want to detect technical drawings from images. These Images mostly consist of objects made up of combination of shapes like lines, circles and rectangles. ...
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YOLOv7 fine tuning with unbalanced dataset
I have a question about training object detection models especially using the YOLOv7 algorithm.
I use a Soccer Players Dataset from the Roboflow. The dataset is very unbalanced.
I trained the model ...
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Object recognition based on its movement [closed]
Models like YOLO, Detectron2, etc. classify objects based on their appearance.
This is great when we have single images, and we want to classify objects within those images. However, video contains a ...
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Can NotA (none of the above) class be combined with object detection / segmentation models?
So there's this way of classifying an object as NotA (none of the above) class as described in https://arxiv.org/abs/1910.02830
So mostly this uses a sort of confidence thresholding with different ...
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Mapping an image to a well defined object using OpenCV
I am completely new to computer vision and I am working on a small hobby project.
The goal is to use camera footage of a foosball table to map the image to already well defined object geometry with ...
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What is single object localization?
Object detection is said to be combination of object localization and image classification. However, when reviewing localization, I often come across the term "single-object" localization, ...
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Is there a way to improve the low-quality data?
I'm on a robotics team and we've been tasked to write a program to differentiate between a live and dead fish. We've been given ~15 minutes of training footage and it's absolutely terrible. It's low ...
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For an image (of any object), how to find its location in the other image(s) which contains it, given there are no labels or annotations for any image
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 does the classification head of EfficientDet work?
EfficientDet outputs classes and bounding boxes. My question is about both but specifically I am interested in the class prediction net part. In the paper's diagram it shows 2 conv layers. I don't ...
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Multiple labels for the same rectbox?
My goal is to identify the horse in a photo. I'm dealing with about 500 unique horses.
My feeling is that the best way to distinguish one horse from another is by its face. So I trained Yolov5 ...
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In anchor based object detection, why don't the anchors share the same weights?
After reading about YOLO V3 and Faster R-CNN, I don't understand why the weights for the regression head aren't the same across all boxes of the same size. Given that the backbone of these systems is ...
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Why object detection algorithms are poor in optical character recognition?
OCR is still a very hard problem. We don't have universal powerful solutions. We use the CTC loss function
An Intuitive Explanation of Connectionist Temporal Classification | Towards Data Science
...
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How can I train a model to recognize object with zoomed-in image?
Humans are good at guessing animals with zoomed-in images from patterns of fur/skin.
(For example, if we saw a black-white pattern fur, it must be a zebra)
I have some experience guessing a car model ...
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How are Ground truth provided to each Pyramid map in RetinaNet or YOLOv3 Paper? How is the mapping of Feature Pyramids done to Ground Truth
SO the YOLO V3 and RetinaNet both uses the Feature pyramids which look something like this:
(except b and e which have one ...
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Can object detection approaches be used to solve text/detection problems?
I have been working on text detection and recognition for almost two months and new on this field. So far, I have fine-tuned, tested, and trained several text detection/recognition methods, such as ...
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Image classification - Need method to classify "unknown" objects as "trash" (3D objects)
We have an image classifier that was built using CNN with faster R-CNN and Yolov5.
It is designated to run on 3D objects.
All of those objects have similar "features" structure, but the ...
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Can the (sparse) categorical cross-entropy be greater than one?
I am using AlexNet CNN to classify my dataset which contains 10 classes and 1000 data for each class, with 60-30-10, splits for train, validation, and test. I used different batch sizes, learning ...
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If random rotations are included in the data augmentation process, how are the new bounding boxes calculated?
When studying bounding box-based detectors, it's not clear to me if data augmentation includes adding random rotations.
If random rotations are added, how is the new bounding box calculated?
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Single-Shot Learning for Object Re-Identification
I am looking for a way to re-identify/classify/recognize x real life objects (x < 50) with a camera. Each object should be presented to the AI only once for learning and there's always only one of ...
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Find object's location in an area using computer vision
I'm trying to see how to detect the location of a soccer ball in the field using the live camera. What are some ways to achieve this?
1- Assuming we have a fixed camera with a wide shot. How to find ...
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Get object's orientation or angle after object detection
I'm trying to get a detected car's orientation when object detection is applied. For instance, when we apply object detection on a car and get a bounding box, is there any ways or methods to calculate ...
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How can I train a CNN to detect when a person is smoking outside of shop given images from a video camera?
My friend is working at a pizza shop. He takes cigarette breaks in an area that is covered by the public webcam of our town.
I now want to train a convolutional neural network to be able to detect ...
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Is it ok to perform transfer learning with a base model for face recognition to perform one-shot learning for object classification?
I am trying to create a model that is using a one-shot learning approach for a classification task. We do this because we do not have a lot of data and it also seems like a good way to learn this ...
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Why isn't medical imaging improving faster with AI?
Researcher here. I just read this piece about medical imaging ai with object recognition and it left me wondering why there are still 100,000+ deaths a year in the US due to misdiagnosis - anyone out ...
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Can I resize my images after labeling them?
Is it okay if I label my images with their original size and then resize them, or should I first resize them and then label them?
I mean do I need to recalibrate my labels if I resized my images?
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How to quickly change hand-drawn shapes to symmetrical polished shapes?
Given a hand-drawn shape, I'd like to generate the corresponding symmetrical polished shapes such as circle, rectangle, triangle, trapezoid, square, parallelogram, etc.
A short video demonstration
...
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Video recognition (specifically video, not individual frames)
There are libraries for recognizing individual video frames, but I need to recognize an object in motion. I can recognize a person in every single frame, but I need to know if the person is running or ...
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Detect object in video and augment another video on top of it
I'm trying to detect an object in a video (with slight camera movement), and then augment another video on top of it. What is the simplest approach to do that?
For instance, let's assume I have this ...
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Is the choice of the optimiser relevant when doing object detection?
Suppose that we have 4 types of dogs that we want to detect (Golden Retriever, Black Labrador, Cocker Spaniel, and Pit Bull). The training data consists of png images of a data set of dogs along with ...
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What is the best way to detect and recognize traffic signs in a picture?
I'm working on a project for my college to recognize traffic signs in pictures. I searched a lot but can't find the best method to do it.
Can someone recommend me a paper, article, or even GitHub link ...
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Recognize carp and give them a unique id
For my internship assignment I have to implement a proof of concept for an application that is supposed to scan a picture with a carp on it and identify which carp this is. All of the carps that are ...
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Small size datasets for object detection, segmentation and localization [closed]
I am looking for a small size dataset on which I can implement object detection, object segmentation and object localization.
Can anyone suggest me a dataset less than 5GB? Or do I need to know ...
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YOLOv3 Synthetic Data Training
Suppose we want to train a model to detect various objects. Let's say we have training data of those objects in various backgrounds along with their bounding boxes. Basically these objects have been ...
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YOLO 9000 about Better Stronger
In this paper, YOLO has three features compared to YOLO v1. This question is about Better and Faster.
In the Better section, there are many techniques such as Batch Norm, Anchor Box and so on. In the ...
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How can I recognise the name of a molecule given an image of its structure?
I want to recognize the name of the chemical structure from the image of the chemical structure. For example, in the image below, it is a benzene structure, and I want to recognize that it is benzene ...
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FasterRCNN's RPN network training
I would like to know if my understanding of RPN training is correct, and if never training the RPN on some specific anchor box is bad (i.e if the anchor never sees good nor bad examples).
To make my ...
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Is it possible to use AI for detecting the volume of a cup
I was just wondering if it's possible to use Machine Learning to train a model from a dataset of images of cups with a given volume in the image and then use object detection to detect other cups and ...
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learning object recognition of primitive shapes through transfer learning problem
Question on transfer learning object classification (MobileNet_v2 with 75% number of parameters) with my own synthetic data:
I made my own dataset of three shapes: triangles, rectangles and spheres. ...
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Is it possible to train a CNN to predict the dimensions of primitive objects from point clouds?
Is it possible to train a convolutional neural network (CNN) to predict the dimensions of primitive objects such as (spheres, cylinders, cuboids, etc.) from point clouds?
The input to the CNN will be ...
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Pose estimation using CNNs on Point clouds
In the case of single shot detection of point clouds, that is the point cloud of an object is taken only from one camera view without any registration. Can a Convolutional Network estimate the 6d pose ...
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Are there deep networks that can differentiate object class from individual object?
We usually categorize objects in a hierarchy of classes. Let us say crow vs bird. In addition, classes can be "messy", for instance a crow can be also a predator, but not all birds are predators.
My ...
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Are there methods that allow deep networks to learn object categorization in a self-supervised way?
When training a deep network to learn object classification from a set like ImageNet, we minimize the cross entropy between the ground truth and the predicted categories. This is done in a supervised ...
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Is Mask R-CNN suited to solve a multi-class classification problem where the classes are related?
I want to create a model to solve a multi-class classification problem.
Here are more details about my problem.
Every picture contains only one object
The background is very simple
All objects ...
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Is there any computer vision technology that can detect any type of object?
Is there any computer vision technology that can detect any type of object? For example, there is a camera fixed, looking in one direction always looking at a similar background. If there is an object,...
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Extending FaceNet’s triplet loss to object recognition
FaceNet uses a novel loss metric (triplet loss) to train a model to output embeddings (128-D from the paper), such that any two faces of the same identity will have a small Euclidean distance, and ...
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What could an oscillating training loss curve represent?
I tried to create a simple model that receives an $80 \times 130$ pixel image. I only had 35 images and 10 test images. I trained this model for a binary classification task. The architecture of the ...
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Can Microsoft's cognitive service find similar person in a set of images without using the face service?
I need to create an application that can detect if a person X entered as an input exists in an image set and return as output all the images in which the person X exists. The problem is that the ...
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Where to find pre-trained models for multi-camera people tracking?
I need to build a multi-camera people tracking system and I have no idea how to start. I read ML for Dummies and I've watched a lot of youtube classes/conferences and read a lot of articles about ML/...
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How do I identify the number and type of objects in the same picture?
I need to identify the number and type of all objects in a picture, so there can be multiple objects of the same type.
For example, I have a picture with $10$ animals, and I want my program to tell ...
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How should I build an AI that quickly detects falling game assets on screen?
I want to build an AI that plays a simple android game.
The game is just a one at a time object falling, some times at an angle. The AI needs to recognize the object and to decide whether to swipe ...
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