Nature Tourism is an industry that is currently thriving and a lot of tourists visit places abundant in flora and fauna. A lot of times while hiking, tourists come across exotic looking flowers that mesmerize them but they are unable to discern what species the flowers belong to. The system proposed in this paper can help nature enthusiasts identify these flowers correctly. The proposed system examines the various features of the flower and identifies it by retraining models on flower datasets, using transfer learning methods. A review of three convolutional neural network models pre-trained on the ImageNet dataset, using the TensorFlow backend, was conducted to suggest the superior algorithm for flower classification systems in order to identify plant species accurately. The system was then implemented in the form of an Android mobile application that provides relevant information along with the species and family of the flower.
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