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This paper introduces a new method to automate the detection of marine species in aerial imagery using a Machine Learning approach. Our proposed system has at its core, a convolutional neural network. We compare this trainable classifier to a handcrafted classifier based on color features, entropy and shape analysis. Experiments demonstrate that the convolutional neural network outperforms the handcrafted solution. We also introduce a negative training example-selection method for situationsdoi:10.1109/dicta.2014.7008084 dblp:conf/dicta/MaireAH14 fatcat:vdchfzzsoreithow4gwamekyeq