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JasonRDalton t1_jdkt4a4 wrote

Object detection in an RGB image doesn’t seem like the right approach for the malaria census. What is the phenomenon you’re looking for? You can’t ‘see’ malaria on the ground, so instead how about looking for conditions that would indicate higher mosquito levels. Like stagnant water mosquito breeding areas, appropriate temperature ranges, lack of predators for mosquitos, low wind speeds, population density, lots of outdoor living, etc. you’ll need some multispectral data but you’ll have better prediction results.

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FesseJerguson t1_jdl5bdt wrote

To be fair you could just throw the "RGB" data at it and eventually it would conclude those things and *** possibly find more *** which is the most exciting thing about ml right?

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JasonRDalton t1_jdlqni1 wrote

it can’t identify phenomena that don’t appear in the scene at all.

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R_K_J-DK OP t1_jdlxxnu wrote

We are also giving our model other data. So far we give it satellite images, land cover, temperature and precipitation. The hypothesis about the satellite images is that we can get some nuances with it that has been lost in the land cover data.

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JasonRDalton t1_jdlyrz3 wrote

There you go! That sounds great. I bet you’ll do well. Maybe if you find some animal habitat models, population density, etc you can augment further. Would love to hear how it performs.

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