Bluefield (KDE TUT) at LifeCLEF 2016 Plant Identification Task
نویسندگان
چکیده
In this paper, we propose an automatic approach for plant image identification. We enhanced the well-known VGG 16-layers Convolutional Neural Network model [1] by replacing the last pooling layer with a Spatial Pyramid Pooling layer [2]. Rectified Linear Units (ReLU) are also replaced with Parametric ReLUs [3]. The enhanced model is trained without external dataset. A post processing method is also proposed to reject irrelevant samples. We further improved identification performance using observation identity (ObservationId) provided in the dataset. Our methods showed outstanding performance in official evaluation results of the LifeCLEF 2016 Plant Identification Task.
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