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This is just an idea Given a set of pixels, the task is to decide: Which pixel is the center of an object? What is the size of the bounding boxes with the center is the pixel in part 1? Formula, consider this is a 2D image, call $(x,y)$ is the horizontal and vertical coordinate and $(w_i,h_i)$ is the size of bouding box of object $i$: $\text{For }m \in[x,x+...


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Then how do each filter differ by? Is it in hovering over the input matrix? Or is it in the values contained by filter itself? Or differs in both hovering and content? The filters (aka kernels) are the learnable parameters of the CNN, in the same way that the weights of the connections between the neurons (or nodes) are the learnable parameters of a multi-...


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Since this a classification problem you will use a CNN preferably. Then you need to fix an architecture of the CNN like VGGNet or Resnet or Le-net. You can find details on architectures here- Neural Network Architecures. As a beginner you can use VGG 16. You can read about the architecure here- Medium.com blog on VGG 16. which tools/tutorials i should look ...


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The neural network will learn what we teach it, for example with that image only, after finish training, your model will hard to recognize humans with dark skin, glasses, big eyes, etc, the features that two annotated targets don't have. If your data is big enough, and contain all the feature of humans face, the result should be good. If not, I recommend a ...


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? This means that there are not promising versions of this algorithm fro regression until 2012. After your question, I have found one of the survey research paper which is done or ensemple methods for regression. This table also extracted from this paper. Read this paper, it will help you a lot more This one is latest paper published on object detection with ...


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