Questions tagged [image-recognition]

For questions related to image recognition in the context of AI.

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1 answer
175 views

What is the difference between exhaustive nearest neighbor search and k-nearest neighbour search?

I have two lists of feature vectors calculated from pre-trained CNN for image retrieval task: Query: FV_Q and Reference FV_R. <...
-1 votes
0 answers
19 views

CNN image classification [closed]

While training CNN with a fully connected layer for image classification, isn't training everything at once the problem? For example, we want to classify dogs. Somehow in the first epoch feature ...
1 vote
1 answer
127 views

Can we identify only the objects in specific parts of an image with computer vision?

I am studying computer vision for the past 3 months. I have come across the object identification problem, where given an image, CV would identify various parts in the image. If I give an image, and a ...
0 votes
1 answer
67 views

How can I reduce the loss? Why do I have the high loss and why do I have the gradient?

I want to classify some images (there are about 200.000 images) with a CNN. But I get a very high loss, see figures: Loss over the hole training run Loss for each epoch It's confused me, that there ...
2 votes
1 answer
425 views

How to detect multiple playing cards of the same class with a neural network?

I want to train an AI to detect the class (i.e. suit and rank) of playing cards. Playing cards from different decks may use slightly different shapes or colors to represent these attributes, and I ...
0 votes
0 answers
18 views

How to optimize input image tensor, to best fit image classifier, for specific target class?

Assume that we got pretrained image classifier, and we want to then optimize some input image tensor for it, that for given class, the output of classifier will match. How to do this for example in ...
1 vote
1 answer
35 views

Validity of ImageNet for measurement of the model performance

ImageNet dataset is an established benchmark for the measurement of the performance of CV models. ImageNet involves 1000 categories and the goal of the classification model is to output the correct ...
0 votes
1 answer
39 views

What algorithm to use to classify data by spatial relations?

Let's assume I have dataset of image-like 2D samples where values can be divided into few discrete levels (for example 1, 2, 3 and 4) like in the image below, where each color maps different value, ...
5 votes
1 answer
117 views

How to classify human actions?

I'm quite new to machine learning (I followed the Coursera course of Andrew Ng and now starting deeplearning.ai courses). I want to classify human actions real-time like: Left-arm bended Arm above ...
0 votes
1 answer
50 views

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)...
4 votes
1 answer
57 views

How to deal with images of different sizes, which need to be passed to a model of fixed input size, without losing details and spatial information?

I have the following problem while using convolutional neural networks to detect forgeries: Resizing the image to fit the required input size may not be a good way because the forgery detection ...
0 votes
1 answer
127 views

Training a model to identify certain differences between images?

Newbie to CV here so sorry of this is basic. Here's the deal, I have a program that I run many times. and each run I produce a screenshot. I need to compare screenshots from N-1 and N runs and make ...
2 votes
2 answers
203 views

How can I use autoencoders to analyze patterns and classify them?

I generated a bunch of simulation data from a complex physical simulation that spits out patterns. I am trying to apply unsupervised learning to analyze the patterns and ideally classify them into ...
0 votes
1 answer
87 views

What is 3D face recognition? and how we can check liveness of a face image?

Actually what is mean by 3D face recognition? In normal cases we are extracting face encoding s from a 2D image,right? Is 3D face recognition is used for liveness detection? how its possible?
3 votes
1 answer
163 views

How should I define the loss function for a multi-object detection problem?

I'm trying to create a text recognition project using CNN. I need help regarding the text detection task. I have the training images and bounding box details for them. But I'm unable to figure out ...
0 votes
1 answer
59 views

Can I flip a video to generate more data for action recognition?

There are 8 distinct action classes and around 50+ videos per class. I was wondering if flipping videos from the training set can be a good option to generate additional data. Is it?
0 votes
0 answers
20 views

How would you fine tune the model on images of larger size?

Let's say you have trained a model for image classification, on images of a defined size (H x W x Ch). How would you fine tune the model on images of larger size?
1 vote
0 answers
28 views

How do I deal with a dataset of Images with variable sizes (width and height) when doing Image Classification?

I have a dataset in which the images which don't have the same width and height. How do I perform Image Classification with such images? I am trying as much as possible to steer away from image ...
0 votes
1 answer
27 views

Image Recognition Method, calculate deviation from rectangular grid

I have a set-up which creates pictures of a grid that is a bit bend towards the ends, and I need some kind of program that can calculate the deviation, resp. it just needs to be some kind of indicator,...
3 votes
1 answer
1k views

How do I recognize and find the orientation of the item where the triangle is?

Hypothetically, the symbol (triangle) is sticked to an item and I need to find and recognize that symbol and try to calculate the orientation (in degrees) of the item it is sticked into. How would you ...
0 votes
0 answers
28 views

How to convert prediction probabilities of 2D images (initially 3D image) to 3D image predictions?

Classification: binary Model: CNN (ResNet50V2) During our research we've had 91x109x91 images (3-dimensional). We've used 2D CNN to train and evaluate our images and make predictions on labelled cases,...
1 vote
1 answer
82 views

What sort of out-of-the-box technology could be used to create work similar to artist Refik Anadol?

Refik Anadol has machines view actual pictures and then has the machine create its own images. This video shows some of the stuff he does. What kind of out-of-the-box tools (e.g. a Python package) or ...
1 vote
1 answer
27 views

Does Using the Same Background for Binary Classification Improve Model Accuracy?

I am training a CNN that detects if a there is a pot of boiling water vs if there is a pot of boiling water with pasta inside. My hypothesis is that having the same background for both a positive and ...
5 votes
2 answers
124 views

How can we recognise musical notes in low-resolution or blurry images?

I was looking for an approach to recognise musical notes from photos. I found this repository https://github.com/mpralat/notesRecognizer. However, it doesn't seem good enough. If you look into the <...
1 vote
0 answers
27 views

Is AI able to detect major changes in pairs of images while ignoring minor changes (due to tree crown growth, color and perspectiv disstortions)?

I'm starting to get involved into machine learning but still have some troubles to select the approriate tool or algorithm. My basic task is to compare remotly sensed images of individual trees at two ...
1 vote
2 answers
328 views

Musical notes interpretation [closed]

Musical notes Musical notes videos Piano Can AI, Machine learning, Data science, Computer vision, image processing technologies assist in interpreting musical notes ? Input dataset : Musical notes ...
1 vote
1 answer
37 views

Using convnet to classify language of text contained in images

I hope this question is not too broad or general. I have a very large set of images all of which contain text (some have more, some less). All of them have been tagged as containing, say, English text ...
0 votes
0 answers
16 views

Which is the best model for counting how many people are in an inside car image?

I'm new on AI... I've been given a mission of finding a model which detects how many people there are on a inside car/truck image. So far I worked only with YOLOv4 with OpenCV using yolov4 weights. ...
0 votes
1 answer
152 views

What's the best model to use for CNN(deep learning) regression task for small image dataset?

What are the best Deep learning models(with how many layers) to use in a regression task for a custom dataset containing around 100 images of only one object per image which is more or less ...
1 vote
1 answer
128 views

How to identify whether images contain driver's licenses or ID cards

Suppose I have a lot of scans of hardcopy documents, in the form of jpegs. Some of them are potentially scans of driver's licenses or identification cards. I wonder what would be a good way to ...
1 vote
0 answers
32 views

Detecting cheats visually using AI

I really like to play my favorite 3D shooter game online. Unfortunately, it is really old and cheat protection isn't really common there, but cheaters are! It is very frustrating, because it really ...
4 votes
2 answers
2k views

Is the QuickDraw with Google neural net a convolutional neural network?

Does anyone know, or can we deduce or infer with high probability from its characteristics, whether the neural network used on this site https://quickdraw.withgoogle.com/ is a type of convolutional ...
2 votes
2 answers
145 views

How to classify two very similar images using Deep Learning?

I am a newbie in Computer Vision. I have a scenario in which I have a stationary camera in a factory. I want to detect whether the technician is working on the machine or not. Images are like the ...
7 votes
2 answers
3k views

Does data skew matter in classification problem?

I'm working on an image classification problem using a neural network. In the training data set, 90% of the samples fall into 10% of all categories, while 10% of the sample fall into the other 90% ...
2 votes
0 answers
32 views

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 ...
3 votes
1 answer
359 views

Is color information only extracted in the first input layer of a convolutional neural network?

In a convolutional neural network (CNN), since the RGB values get multiplied in the first convolutional layer, does this mean that color is essentially only extracted in the very first layer? A ...
0 votes
0 answers
40 views

How to improve accuracy of CNN used for facial micro-expression analysis

From the paper (1) Facial expression analysis using CNN, the results using CNN show a 65% and 62% accuracy respectively, for emotion classification and state of mind identification. Proposed Method: ...
3 votes
1 answer
87 views

How can computers beat humans at image recognition, if humans may incorrectly label the images?

For supervised learning, humans have to label the images computers use to train in the first place, so the computers will probably get wrong the images that humans get wrong. If so can computers beat ...
0 votes
0 answers
41 views

Is it a good idea to train a neural network to classify images without base-hypothesis?

I'm a relative beginner in deep learning (understand by that, I'm doing my first Kaggle competition right now, and I have loads to learn still) and I was just wondering something. Let's say you have ...
1 vote
1 answer
259 views

What make a CNN suitable for image classification or semantic segmentation? [closed]

I've just started with CNN and there is something that I haven't understood yet: How do you "ask" a network: "classify me these images" or "do semantic segmentation"? I think it must be something on ...
1 vote
1 answer
43 views

In image classification, why do we usually minimize a cost function rather than maximizing it?

I was watching a video about policy gradients by Andrej Karpathy. At 10:00, it shows an equation for supervised learning for image classification. $$\max\sum _{i} \log p(y_i \mid x_i)$$ I have worked ...
1 vote
0 answers
98 views

What exactly do gradient-based saliency map tell us?

As far as I understand, gradients are supposed to tell us 1) the magnitude and 2) direction, to update a parameter such as to minimize the loss function. Regarding saliency maps, which use gradients ...
0 votes
0 answers
16 views

Comparing large numbers of images to find outliers

There are many methods you can use to compare two images in ML (Siamese NN, CNNs, Ect.) What I cannot figure out is comparing a large number of images (Without Retraining) to find images of a ...
0 votes
0 answers
31 views

Encoding Image Priors into CNN

There's a core problem with all of ML which I haven't really seen made explicit: the issue is every model needs to have an assumption on the structure of the data you learn and this assumption needs ...
0 votes
0 answers
33 views

Why am I getting a very small number as CNN prediction?

I created a CNN using Tensorflow to identify pneumonia and sometimes it returns a very small number as a prediction. why is this happening? I have attached the link for the dataset Here I how I ...
4 votes
1 answer
46 views

How do we perform object classification given images from a camera that captures images at 15 FPS?

I've been working with vanilla feedforward neural networks and have been researching the convolutional neural network literature. If a camera is capturing a video at a rate of 15 frames per second, is ...
0 votes
1 answer
45 views

For a task that searches for an image artifact within a picture, can existing tools can be used or do I need to design the process myself?

I am familiar only with basic AI/NN concepts but never worked with any libraries/tools as tensor flow. Currently, I have a task for which AI might be ideal: detection of a certain image artifact in a ...
0 votes
1 answer
34 views

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 ...
2 votes
1 answer
51 views

How do automatic high-beam headlights work on cars?

Modern cars can operate high-beam headlights automatically: They automatically switch from high-beam headlights to low-beam ones (less intense) when you enter a town or there is a car in front of you ...
25 votes
3 answers
42k views

How do I handle large images when training a CNN?

Suppose that I have 10K images of sizes $2400 \times 2400$ to train a CNN. How do I handle such large image sizes without downsampling? Here are a few more specific questions. Are there any ...

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