Large Field and High Resolution: Detecting Needle in Haystack

10 Apr 2018 Hadar Gorodissky Daniel Harari Shimon Ullman

The growing use of convolutional neural networks (CNN) for a broad range of visual tasks, including tasks involving fine details, raises the problem of applying such networks to a large field of view, since the amount of computations increases significantly with the number of pixels. To deal effectively with this difficulty, we develop and compare methods of using CNNs for the task of small target localization in natural images, given a limited "budget" of samples to form an image... (read more)

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