Questions tagged [computer-vision]

Computer Vision is a subfield of computer science which deals with analyzing and understanding images. This includes detection of objects like faces in images or segmenting images.

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Image segmentation network to extract questions from an image of a test paper?

This is the sample document -> I want to extract questions along with the options. There are other question papers as which have questions with diagrams in them. I want to be able to extract them ...
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What does the notation mAP@[.5:.95] mean?

For detection, a common way to determine if one object proposal was right is Intersection over Union (IoU, IU). This takes the set $A$ of proposed object pixels and the set of true object pixels $B$ ...
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Data preprocessing: Should we normalise images pixel-wise?

Let me present you with a toy example and a reasoning on image normalisation I had: Suppose we have a CNN architecture to classify NxN grayscale images in two categories. Pixel values range from 0 (...
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Faster-RCNN how anchor work with slider in RPN layer?

I am trying to understand the whole Faster-RCNN, From https://www.quora.com/How-does-the-region-proposal-network-RPN-in-Faster-R-CNN-work Then a sliding window is run spatially on these feature ...
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Why choose TensorFlow?

I have noticed that most of the deep learning developers use TensorFlow. So why choose TensorFlow? What is the advantage of TensorFlow over Theano and CNTK?
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How to visualize image segmentation results

I am using u-net to do semantic segmentation for N>1 classes. The input size is (128,128,3), the output size will be (128,128,N). what is the correct way see the prediction as an image ot size n1 x n2 ...
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What is the different between Fine-tuning and Transfer-learning?

Usually the neural network training has at least 2 steps: first trained on a large set of some standard data (ImageNet, ...) and then the resulting weights are trained on a small set of my data (in ...
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2answers
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Training Validation Testing set split for facial expression dataset

I am using Convolutional Neural Networks (CNN) and I just want to ask if the way I split my training/validation/testing set is correct. I have a total of 55 subjects. I plan to split them into 80–10–...
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2answers
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3D point reconstruction from 2D images

I know this must exist, but I'm having enormous trouble finding the right search terms. Say I have a bunch of labelled 3D points, and I capture multiple 2D images of it. If I want to reconstruct the ...
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1answer
1k views

How to arrange the image dataset in CNN?

How do I arrange the image dataset in CNN? Should I put each image category in a separate folder? Or all of them in the same folder? Should the image name be the category name? I would like to see an ...
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936 views

Meaning of dropout

What does model.add(Dropout(0.4)) mean in Keras? Does it mean ignoring 40% of the neurons in the Neural Network? OR Does it mean ignoring the neurons that give ...
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Which is the fastest image pretrained model?

I had been working with pre-trained models and was just curious to know the fastest forward propagating model of all the computer vision pre-trained models. I have been trying to achieve faster ...
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Data augmentation based on the class type in the CNN model

I would like to use CNN model to classify images but some classes in my dataset have low amount of data. Can I apply data augmentation based on the number of the images in the class? For example, ...
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1answer
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Implement the following loss function without interrupting the gradient chain registered by the gradient tape

I have spent five days trying to implement the following algorithm as a loss function to use it in my neural network, but it has been impossible for me. Impossible because, when I have finally ...
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cv2.error: OpenCV(3.4.3) (-215:Assertion failed) !empty() in function

Would anyone have a tip on how to fix this empty function error in OpenCV? I am attempting to follow the guides on OpenCV.org The script will detect a face in an image and draw boxes around ...