01897naa a2200373 a 450000100080000000500110000800800410001910000200006024501110008026000090019152008100020065000200101065000250103065000190105565000180107465000180109265000140111070000200112470000230114470000160116770000190118370000230120270000220122570000210124770000210126870000180128970000280130770000230133570000250135870000230138370000200140670000160142677300810144217869482020-11-06       2020    bl uuuu     u00u1 u    #d1 aWEBER, V. A. M.  aCattle weight estimation using active contour models and regression trees Bagging .h[electronic resource]  c2020  aMonitoring the weight of beef cattle is important for productive strategies. The main goal of this work was to automatically extract measurements from 2D images of the dorsal area of Nellore cattle to estimate the weight of these cattle using regression algorithms. For this purpose, Euclidean distances from points generated by the Active Contour Model, together with features obtained from the dorsal Convex Hull, were selected. These were submitted to Bagging, Regression by Discretization and Random Forest algorithms for analysis of the predicted error metrics. The Bagging algorithm showed the best results, with Mean Absolute Error (MAE) of 13.44 kg (2.76), Square Root of the Mean Error (RMSE) of 15.88 kg (2.86), Mean Absolute Percentage Error (MAPE) of 2.27% and correlation coefficient at 0.75.  aComputer vision  aLivestock production  aWeight control  aGado de Corte  aGanho de Peso  aPecuária1 aWEBER, F. de L.1 aOLIVEIRA, A. da S.1 aASTOLFI, G.1 aMENEZES, G. V.1 aPORTO, J. V. de A.1 aREZENDE, F. P. C.1 aMORAES, P. H. de1 aMATSUBARA, E. T.1 aMATEUS, R. G.1 aARAÚJO, T. L. A. C. de1 aSILVA, L. O. C. da1 aQUEIROZ, E. Q, A. de1 aABREU, U. G. P. de1 aGOMES, R. da C.1 aPISTORI, H.  tComputers and Electronics in Agriculturegv.179, 105804, p. 1-12, dec, 2020.