# Treelogy: A Novel Tree Classifier Utilizing Deep and Hand-crafted Representations

arXiv: https://arxiv.org/abs/1701.08291 · HTML: https://mlsanity.com/paper/1701.08291/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 28 Jan 2017.

## Built on by (most cited first, 1 of 1)

- [A Light Weight Multi-Features-View Convolution Neural Network For Plant Disease Identification](https://mlsanity.com/paper/2605.00903/) (2026)

## Abstract (arXiv)

We propose a novel tree classification system called Treelogy, that fuses deep representations with hand-crafted features obtained from leaf images to perform leaf-based plant classification. Key to this system are segmentation of the leaf from an untextured background, using convolutional neural networks (CNNs) for learning deep representations, extracting hand-crafted features with a number of image processing techniques, training a linear SVM with feature vectors, merging SVM and CNN results, and identifying the species from a dataset of 57 trees. Our classification results show that fusion of deep representations with hand-crafted features leads to the highest accuracy. The proposed algorithm is embedded in a smart-phone application, which is publicly available. Furthermore, our novel dataset comprised of 5408 leaf images is also made public for use of other researchers.