University of Twente Student Theses
As of Friday, 8 August 2025, the current Student Theses repository is no longer available for thesis uploads. A new Student Theses repository will be available starting Friday, 15 August 2025.
Multilabel Classification of Orchid Features based on Deep Learning
Post, Cassandra (2020) Multilabel Classification of Orchid Features based on Deep Learning.
PDF
1MB |
Abstract: | There are many different types of orchids, with many inter-class similarities. Classifying them using the conven-tional method of comparing the features to registered orchid types is very time consuming. Thus it would be useful to have an image based orchid feature classifier. In this paper a single output multilabel classifier using transfer learning is designed to classify six different orchid features. The design is based on experiments on different loss functions, pre-trained models, number of neurons in the dense layer, dropout rates and fine-tuning. The final model uses an Xception model with one untrainable layer as feature extractor. The classifier consists of two dense layers with a dropout of 0.5 in between. The final model gets a macro average f1-score of 0.85. The model is reliable for the non-color features, however it doesn’t perform well on some rare classes of the color features. |
Item Type: | Essay (Bachelor) |
Faculty: | EEMCS: Electrical Engineering, Mathematics and Computer Science |
Subject: | 53 electrotechnology |
Programme: | Electrical Engineering BSc (56953) |
Link to this item: | https://purl.utwente.nl/essays/85599 |
Export this item as: | BibTeX EndNote HTML Citation Reference Manager |
Repository Staff Only: item control page