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An approach that is not specific to the image domain is to use a probabilistic data structure like a Count-Min Sketch. A Count-Min Sketch data structure can accumulate information to estimate the observed frequency of an input value based on the past set of input values by using multiple hashing functions over the input.


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One problem with this is that dark images simply contain less information. Anyone with a background in photography will tell you it’s easier to decrease exposure on a bright image than increase exposure on a dark one (you can’t create what’s not there but you can throw away information you have). If you want all images on the same playing field, perhaps do ...


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You may find Apolloscape dataset interesting. It was recently released by Baidu. From the article describing the dataset: In this paper, we present a large-scale open dataset, ApolloScape, that consists of RGB videos and corresponding dense 3D point clouds. Apart from the article, there have been some blog posts with summarized information on the ...


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I don't know, there might be disasters which happened due to ML but my guess is that it might be hard to really consider ML as the cause: ML is always deployed in a setting designed by humans for a very specific task, and the design must take into account the statistical nature of ML. So I would tend to interpret most problems as caused by a wrong design, ...


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To answer your question no. The term "imbalance" usually refers to classification problems. For your case, i.e. a regression problem you can only look at the distribution of your target variable. If by "balance" you mean them having a uniform distribution, you could argue that they are, if fact imbalanced. However, I'd argue that this is not the problem ...


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~ If we consider the problem as an image classification task, Basically, we can use a CNN trained on images belonging to 7 classes ( which represent the steering levels ). We give an image to the CNN and it outputs a steering level. This is a classification problem which will take each frame ( image ) of the video and output the steering level. So as the ...


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