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DeepForest is a python package for training and predicting ecological objects in airborne imagery. DeepForest currently comes with a tree crown object detection model and a bird detection model. Both are single class modules that can be extended to species classification based on new data.
DeepForest is a python package for training and predicting ecological objects in airborne imagery. DeepForest comes with prebuilt models for immediate use and fine-tuning by annotating and training custom models on your own data. DeepForest models can also be extended to species classification based on new data. DeepForest is designed for:
2 ημέρες πριν · DeepForest is an open-source library providing tools for object detection and geospatial analysis in ecology, specifically for analyzing forest canopy data.
DeepForest is a python package for training and predicting ecological objects in airborne imagery. DeepForest currently comes with a tree crown object detection model and a bird detection model. Both are single class modules that can be extended to species classification based on new data.
1 Φεβ 2021 · DF21 is an implementation of Deep Forest 2021.2.1. It is designed to have the following advantages: Powerful: Better accuracy than existing tree-based ensemble methods. Easy to Use: Less efforts on tunning parameters. Efficient: Fast training speed and high efficiency. Scalable: Capable of handling large-scale data.
Free software: MIT license. Why DeepForest? Remote sensing can transform the speed, scale, and cost of biodiversity and forestry surveys. Data acquisition currently outpaces the ability to identify individual organisms in high-resolution imagery.
DeepForest: A Python package for RGB deep learning tree crown delineation | Weecology. Ben G Weinstein, Sergio Marconi, Mélaine Aubry-Kientz, Gregoire Vincent, Henry Senyondo, Ethan White. January 2020. PDF Cite Dataset Source Document. Type. Journal article. Publication. Methods in Ecology and Evolution. Ethan White.
