Questions tagged [image-recognition]

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

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70 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 ...
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1answer
31 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, ...
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1answer
104 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 ...
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2answers
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% ...
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0answers
19 views

Does adding new keypoints increase accuracy for foot keypoint detection?

I am trying to have better results for foot keypoint detection(or foot pose estimation). In foot keypoints dataset the images labeleld for 6 different keypoints(big,small toes and heel for each foot). ...
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1answer
50 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 ...
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2answers
153 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 ...
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1answer
81 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?
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1answer
23 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 ...
2
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1answer
131 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 ...
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0answers
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
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1answer
329 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 ...
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0answers
33 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
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1answer
85 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 ...
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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 ...
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1answer
216 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 ...
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1answer
42 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 ...
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1answer
38 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?
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0answers
48 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 ...
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0answers
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 ...
3
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1answer
39 views

Size of image input of neural networks while resizing may not be appropriate

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 ...
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0answers
24 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 ...
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0answers
30 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
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1answer
43 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 ...
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1answer
32 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 ...
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1answer
40 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 ...
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1answer
27 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 ...
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1answer
33 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 ...
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1answer
49 views

Denoising Images When Training a Classification Model

Suppose you have a binary outcome variable and have some training data (10,000 images in jpg format). Also you have a test set of say 11,000 images. If we want to train a classification model and want ...
2
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1answer
48 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 ...
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1answer
133 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. <...
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3answers
39k 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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1answer
91 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 ...
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0answers
30 views

What is the purpose of hard distillation?

In order to get a smaller model, one often uses larger model, that performs reasonably well on the data as a teacher, and uses the information from large model to train the smaller one. There are ...
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0answers
24 views

Without using data augmentation gives results better than using data augmentation

I am a beginner to deep learning, I'm doing the image classification problem on a small self plant disease imaging dataset (400 images). I am doing transfer learning (pre-trained ...
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1answer
69 views

Is there a way of automatically drawing bounding boxes around interested objects?

Given thousands of images, where some of the images contain target objects and others do not, is there an easy way of drawing bounding boxes on these target objects rather than relying on manual ...
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1answer
131 views

What algorithms are used for image segmentation of images where objects are not composed of pixels that are similar in value?

In the process of segmentation, pixels are assigned to regions based on features that distinguish them from the rest of the image. Value Similarity and Spatial Proximity, for example, are two ...
2
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1answer
370 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 ...
5
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1answer
2k views

How are the kernels initialized in a convolutional neural network?

I am currently learning about CNNs. I am confused about how filters (aka kernels) are initialized. Suppose that we have a $3 \times 3$ kernel. How are the values of this filter initialized before ...
4
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1answer
390 views

Get the position of an object, out of an image

I have some images with a fixed background and a single object on them which is placed, in each image, at a different position on that background. I want to find a way to extract, in an unsupervised ...
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0answers
37 views

How to increase accuracy of image orientation classification (Left, Right, Center)?

I am working on classifying images in "Left", "Right", "Center", "Back". Training and Validation images look like this: The images are "Left", "...
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0answers
41 views

Is having near-duplicates in a training dataset a bad thing?

I am making a labeled dataset of images from web streams for a CNN classification. Pictures from the same stream are quite similar as far as background, but slightly different as far as the main ...
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0answers
37 views

Image recognition neural network: scaling and rotation

Are there some effective and robust solutions for scaling and rotation for image recognition with the neural networks (NN)? I see tons of sources on the Web with explanation how neural network is used ...
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0answers
29 views

Machine Learning Algorithm for OCR on full pages of text

I would like to build an OCR application. In. particular, I want my algorithm to scan entire pages of text in a specific niche language. I was therefore wondering if there are some algorithms that ...
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0answers
26 views

Is soft labeling the same thing as label smoothing?

I have some data with soft labels and I am trying to figure out the best approach to solve the problem with Machine Learning (since regular classification is of the table, i.e. hard labels). However, ...
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0answers
11 views

How to localize and classify objects in video

What methods are used to localize an object in an video and classify that object? Example: I have a camera which detects an pickup truck driving into a garage of three (1,2,3). In need to know if the ...
4
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1answer
84 views

How to use Machine Learning to create a "Draw-A-Person Test"

The process revolves around a child's drawing. Each part of each drawing corresponds to a score as in the Draw a Person Test conceived by Dr. Florence Goodenough in 1926. The goal of the machine is to ...
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2answers
77 views

An approach on reading musical notes from photos

I was looking around, a promising approach was this: https://github.com/mpralat/notesRecognizer the problem is: it doesn't seem good enough. One should be able to read musical notes with lower ...
3
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1answer
53 views

Does anyone know of a model for comparing the eyes of people in two images to see if they match?

There’s a lot of talk of undercover cops intentionally starting violence in otherwise peaceful protests. The evidence, primarily, are images like this. https://images.app.goo.gl/4n3o2EXwFzMQfsKq6 ...
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1answer
30 views

Should I label static objects on video dataset?

I'm using nvidia Transfer Learning Toolkit to detect cars in some video frames. I found some dataset (for example https://www.jpjodoin.com/urbantracker/dataset.html and https://www.kaggle.com/...

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