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Hi all, I am currently trying to train a deep learning framework for detecting bats from thermal imagery taken from a drone. You will see in the below image the bats are the detectable as the bright circles against a dark background: So far, I have been defining training samples by drawing a circle from the center of each bat to just outside the edge of the animal. However, this is not giving me good results: You will see in some instances, completely dark areas are classified as bats, or just the edge of a bat is detected. I suspect that the issue here is how I am defining the bats in the training samples. I am thinking about trying this process again with rectangular training samples. Is anyone able to offer advice on the best way to define a bat in my training images? Thanks in advance for your help! Elie
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04-19-2020
11:52 PM
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I'm trying to train a deep learning model from thermal drone imagery, following along with the 'Use Deep Learning to assess palm tree health' tutorial. At the Training step, I get this error part way through the epochs: "Runtimeerror: expected a non-empty list of tensors" (see snip below). Does any one know how to troubleshoot this error?
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04-18-2020
11:11 PM
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I am trying to classify thermal imagery using object based image analysis using Random Trees and Maximum likelihood classifiers. I was wondering if there are rules for how many training samples we should generate per class?
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01-16-2020
09:01 PM
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