Large-Scale Plant Classification using Deep Convolutional Neural Networks

Deep learning techniques have significantly improved plant species classification in recent years. The goal of the 2018 ExpertLifeCLEF challenge was to compare the performance of human experts to machines trained on the PlantCLEF 2017 dataset containing 10.000 classes. We used the Inception, ResNet and DenseNet architectures to solve this complex task. In our experiments, complex neural net layouts yield strong results, comparable to human performance. We further push the overall accuracy through iterative adjustment of class weights. An ensemble consisting of a ResNet50 and two DenseNet201 with fine-tuned class weights reached a top1-accuracy of 77% on the test set.