Download TreeLogy APK latest version Free for Android
Version | 1.0 |
Update | 6 years ago |
Size | 4.33 MB (4,544,982 bytes) |
Developer | Duman Emre Akın |
Category | Apps, Education |
Package Name | com.payinekereg.treelogy |
OS | 2.3 and up |
TreeLogy APPLICATION description
Leaf-Based Tree Identification System
“Treelogy” is a mobile application, which can perform leaf-based tree identification among
tree species in Turkey using one picture of a given leaf.
There is only handful of applications interested in tree identification and they are designed
primarily for detecting North American and European tree species. There is no application
which has a good performance and localization support for identifying tree species native to
Turkey. This project is aimed to fill this gap.
While we are constructing this application, we worked on supervised learning for classi-
fication task. We focused on both Deep Learning (specifically Deep Convolutional Neural
Networks) and Support Vector Machines. Tree identification process uses leaf image features
gathered from Caffe, a convolutional neural network framework, and our image processing
module.
After several experiments, we reached the optimal classification accuracy of 93.59% for 57
tree species. Experiments involve 16096 training and 3020 testing leaf images. According to
our findings, we come to the following conclusion. Certain image processing procedures for
extracting features such as shape and texture descriptors, which we have used in our project,
does not produce features as feasible as convolutional neural networks.
"Created by group paY inekereG"
tree species in Turkey using one picture of a given leaf.
There is only handful of applications interested in tree identification and they are designed
primarily for detecting North American and European tree species. There is no application
which has a good performance and localization support for identifying tree species native to
Turkey. This project is aimed to fill this gap.
While we are constructing this application, we worked on supervised learning for classi-
fication task. We focused on both Deep Learning (specifically Deep Convolutional Neural
Networks) and Support Vector Machines. Tree identification process uses leaf image features
gathered from Caffe, a convolutional neural network framework, and our image processing
module.
After several experiments, we reached the optimal classification accuracy of 93.59% for 57
tree species. Experiments involve 16096 training and 3020 testing leaf images. According to
our findings, we come to the following conclusion. Certain image processing procedures for
extracting features such as shape and texture descriptors, which we have used in our project,
does not produce features as feasible as convolutional neural networks.
"Created by group paY inekereG"
↓ Read more
![TreeLogy screen 1](/img/1.gif)
![TreeLogy screen 2](/img/1.gif)
![TreeLogy screen 3](/img/1.gif)
![TreeLogy screen 4](/img/1.gif)
![TreeLogy screen 5](/img/1.gif)
![TreeLogy screen 6](/img/1.gif)
![TreeLogy screen 7](/img/1.gif)
![TreeLogy screen 8](/img/1.gif)
Old versions
Version | Size | Update |
---|---|---|
⇢ 1.0 (2 variants) | ↓ 4.10 MB | ◴ 7 years ago |