01134naa a2200337 a 450000100080000000500110000800800410001902400560006010000160011624501810013226000090031350000540032265000280037665000260040465000190043065300230044970000210047270000210049370000190051470000220053370000230055570000150057870000210059370000240061470000210063870000190065970000180067870000200069670000230071677300570073921432932023-01-20       2022    bl uuuu     u00u1 u    #d7 ahttps://doi.org/10.1016/j.infrared.2022.1042032DOI1 aOSCO, L. P.  aAn impact analysis of pre-processing techniques in spectroscopy data to classify insect-damaged in soybean plants with machine and deep learning methods.h[electronic resource]  c2022  aNa publicação: Maria Carolina Blassioli-Moraes.  aArtificial intelligence  aPrecision agriculture  aRemote sensing  aField spectroscopy1 aFURUYA, D. E. G.1 aFURUYA, M. T. G.1 aCORRÊA, D. V.1 aGONÇALVEZ, W. N.1 aMARCATO JUNIOR, J.1 aBORGES, M.1 aMORAES, M. C. B.1 aMICHEREFF, M. F. F.1 aAQUINO, M. F. S.1 aLAUMANN, R. A.1 aLISENBERG, V.1 aRAMOS, A. P. M.1 aJORGE, L. A. de C.  tInfrared Physics & Technologygv. 123, 2022. 104203.