01634naa a2200301 a 450000100080000000500110000800800410001902400540006010000200011424501230013426000090025752007090026665000110097565000200098665000200100665000180102665000090104465000280105370000230108170000190110470000300112370000170115370000260117070000210119670000160121770000230123377300760125620889722020-08-17       2020    bl uuuu     u00u1 u    #d7 ahttps://doi.org/10.1016/j.compag.2020.1055482DOI1 aWEBER, F. de L.  aRecognition of Pantaneira cattle breed using computer vision and convolutional neural networks.h[electronic resource]  c2020  aThe objective of this paper is to provide recognition for Pantaneira cattle breed using Convolutional Neural Networks (CNN). Fifty-one animals from the Aquidauana Pantaneira cattle Center (NUBOPAN) were studied. The center is located in the Midwest region of Brazil. Four monitoring cameras were distributed in the fences and took 27,849 images of Pantaneira cattle breed using different angles and positions. The following three CNN architectures were used for the experiment: DenseNet-201, Resnet50 and Inception-Resnet-V. All networks were submitted to 10-fold stratified cross-validation over 50 epochs. The results showed an accuracy of 99% in all networks, which is encouraging for future research.  aCattle  aComputer vision  aNeural networks  aGado de Corte  aRede  aSistema de Informação1 aWEBER, V. A. de M.1 aMENEZES, G. V.1 aOLIVEIRA JUNIOR, A. da S.1 aALVES, D. A.1 aOLIVEIRA, M. V. M. de1 aMATSUBARA, E. T.1 aPISTORI, H.1 aABREU, U. G. P. de  tComputers and Electronics in Agriculturegv. 175, 105548, p. 1-9, 2020.