Questions tagged [image-recognition]

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

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11 views

Sound in opencv [closed]

I have written opencv code using python, the code is fueled with a deep learning model that detects hand gesture and extracts meaning "sign language" I was able to extract the meaning of the ...
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15 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 creates its own images. This video shows some of the stuff he does: https://www.youtube.com/watch?v=I-EIVlHvHRM What kind of ...
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12 views

pytorch TypeError: forward() takes 1 positional argument but 2 were given

I have been trying to implement a small VGG network but run into this error. Here is the error message I am getting: ...
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17 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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16 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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15 views

Multi-Modal Vs Multi-View learning

What is the difference between Multi-modal & Multi-view in the context of visual data analysis(images) knowing that Multi-view learning deals with Multi descriptors of image.
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33 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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34 views

How does bipartite matching work in DETR?

I was going through the DETR paper to understand this end-to-end detection transformer used for object detection, and I came across this bipartite matching thing.
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38 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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34 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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26 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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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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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 ...
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1answer
54 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
85 views

What is the difference between a vision transformer and image based relational learning

I am trying to figure out the difference between the architecture used in this and this paper. It looks like both used multi-headed self-attention and therefore should be the same in principle.
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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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What does the lambda parameter in the paper "Interpretable Explanations of Black Boxes by Meaningful Perturbation" do?

I do not understand the purpose of the $\lambda$ parameter in equation 3 of the paper Interpretable Explanations of Black Boxes by Meaningful Perturbation. $$m^{*}=\underset{m \in[0,1]^{\Lambda}}{\...
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when updating the bias matrix, do we get the total sum of dZ or the sum of the axis of dZ?

I'm currently studying how to implement a neural network from scratch to know how it works, I came across this article: https://www.samsonzhang.com/2020/11/24/understanding-the-math-behind-neural-...
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Image classification distributed inference (mobile/server)

I'd like to learn some stuff about distributed DNN inference and how it works in practice. So, let's consider the example of image classification and assume we have a mobile device which utilizes the ...
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Is it possible to create a simple face-tracking app that can monitor how much time one spends at their desk?

Context: I'm an experienced programmer with a graduate education in AI and previous CUDA programming experience. I'm versed in Machine Learning but am out of the loop -- I've not used any of the ...
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26 views

How to deal with images that do not contain any object of interest?

I'm currently working on an iOS App where I want to detect if there is a table, chair or bench in the current camera input. My idea was to take the MobileNetV2 model and get it to classify these three ...
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DeepLabV3: Why use global average pooling in the ASPP module?

I'm trying to understand the rationale of the various modifications the authors of the DeepLab models have made to their third version, DeepLabV3. In the paper, the following is written: ASPP with ...
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What is "fill" algorithm used for image resizing and cropping?

I was going through this documentation directed by Codelab-Developer-Google. In order to resize an image, the notebook is using the "fill" algorithm. See the below code ...
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Inconsistent Classification Accuracy between Classification Network & Object Detection

I have been working on an object detection and classification problem, and I am having understanding a discrepancy in my results. I am try to detect and classify 2 classes. These objects are ...
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27 views

Is it possible to train a perceptron to tell if a picture is a dog or cat?

I know perceptron is a linear classifier that tells linearly separable binary class data, such as iris setosa vs. iris versicolor via their sepal's length and width. I'd just like to know if I have 2 ...
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23 views

Document clustering from ordered pages list

I have a series of ordered pdf pages which own to different documents. Let me give you an example: Pages: 1 2 3 4 5 6 True Pages: 1 2 | 1 2 3 4 So I have like six ordered pages, two of which from ...
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New image-to-image translation algorithm for other type of tasks

I found this amazing new research paper "High-Resolution Photorealistic Image Translation in Real-Time: A Laplacian Pyramid Translation Network" and an associated video. It's about a new ...
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1answer
36 views

Number of classes vs number of parameters/layers?

How to estimate the number of parameters in CNN for object detection? I know that there are some well-known architectures that was trained on a lot of data (AlexNet, ResNet, VGG, GoogleLeNet). But ...
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How can my CNN produce an "unknown" label?

I have a dataset of 20k images of infected mango. I have built a web-based app using Flask, where a user can upload a picture, and my CNN model detects the disease. I have 6 classes in the model, ...
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Finding an object in a large image

I am looking for an algorithm to solve the following problem. There is a very large image (road map). A small distorted part of big image is fed into the input. I want to find the location of a small ...
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1answer
34 views

Cnn for Combination of both digits and letters(small and capital) [closed]

Hi I am new to machine learning can anyone suggest open dataset consists of both digits and letters(small,capital) I want images consisisting of both digits and letters to train my cnn model and make ...
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21 views

Is it possible to do object detection on an object classification dataset?

I'm new to computer vision, which I find fascinating. I wonder whether it is possible or if there has been any research into going from object recognition data to object detection. In other words, ...
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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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How to train feedforward network to recognize images?

Context I'm trying to create network for digits recognition. All digits are the same font and size of 40x40. I know that I can use feedforward network or CNN. I'd like to use the first one. Issue I ...
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1answer
46 views

How to properly use Flatten layer?

Context I'm trying to create net that will be able to recognize printed-like digits. Something like MNIST, but only for standard printing font. Images are of the size 40x40 and I'd like to put them ...
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1answer
23 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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How to make CNN to recognize whole picture, not just the details?

In my current project I use CNNs to analize plots (CNN autoencoders for feature extraction and KMeans for clusterization) and I get the feeling that these networks, can extract only features that are ...
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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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2answers
65 views

Accuracy Not Going Above 30%

I am trying to make a big classification model using the coco2017 dataset. Here is my code: ...
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1answer
61 views

Should one use an "other" category in image classification?

In image classification, there are sometimes images that do not fit in any category. For example, if I build a CNN in Keras to classify Dogs and Cats, does it help (in terms of training time and ...
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1answer
20 views

Why do popular object detecting models output heatmaps instead of coordinators of object directly?

I think heatmap outputs of architectures like CenterNet, OpenPose, etc. can be changed to coordinator outputs, and loss functions like focal loss can be modified so they can deal with coordinators ...
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1answer
54 views

Is there a full and precise formulation of Theorem 1 in the Integrated Gradients paper?

Theorem 1 (page 5) in the paper about Integrated Gradients states that Integrated gradients is the unique path method that is symmetry-preserving. What I miss is A precise formulation of the ...
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1answer
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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 ...
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Yolo from scratch dataset and output

Hi I coded a YOLO model from scratch and just came to realise that my dataset does not fit the models output. This is what I mean: The model outputs a ...
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2answers
88 views

How to recognize sequence of digits in an image

I am learning to program neural networks and others, and I would like to know how I can get the numbers that are in an image, for example, if I pass an image that has 123 written, get with my model ...
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1answer
70 views

Predicting continous value with CNN (prediction of fruit maturity)

I want to train some IA algorithm to be able to evaluate the maturity of a fruit (say, measured in numbers of days before rotten) based on an image of the fruit. My first instinct is to go with ...
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What's the best machine learning algorithm / neural network architecture to use for a task that maps between images and textual descriptions of them?

Title says it all really. I want to train a network to take images of diagrams and produce a standard textual definition of them. What ML architecture is best for this?
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1answer
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How is few-shot learning different from transfer learning?

To my understanding, transfer learning helps to incorporate data from other related datasets and achieve the task with less labelled data (maybe in 100s of images per category). Few-shot learning ...
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1answer
52 views

Training a classifier on different datasets with different image conditions for different labels causes the model to infer using the background

I have an interesting problem related to training the model on two different datasets for the target feature on images taken on different conditions, which might affect the model's ability to ...
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Considerations when doing image classification where the object is not the subject

I've come across two types of image classification tasks cat/dog classification the whole picture is either a cat or a dog. Simple. this image contains a cat classification. There's a whole chaotic ...

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