[R] FastDetect

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FastDetect is a library (and a hobby research project) that essentially attempts to conquer object detection by combining a data efficient generative object model with classical object detection techniques to detect objects in scenes in a scale-invariant fashion. Due to its nature, it can be trained on single objects, or on scenes with multiple objects, while offering similar performance across variations. Plus, it works on low-spec hardware (the current instantiation is able to train and test on an AMD E2-7110 APU in ~15 seconds). The choice for combining classical object detection techniques with the Recursive Cortical Network (RCN) arouse from the fact that it is not clear whether or not the RCN is able to be trained on a scene with multiple objects.


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