PyTorch Wildlife: a Collaborative Deep Learning Framework for Conservation.

Video and Image Analytics for Multiple Environments

Tools for detecting wildlife in aerial images using active learning

Simplify camera trap image analysis with AI species recognition models based around the MegaDetector model

A Python package for identifying hundreds of kinds of animals, training custom models, and estimating distance from camera trap videos and images

trends.earth - measure land change

ArcGIS tools to automate mapping and prioritization of wildlife habitat corridors

AI-Powered Camera-Trap Image Processing

Restor's ML pipeline for tree crown mapping in aerial images

Distance Estimation for Estimating Animal Abundance

Automated Camera Trapping Identification and Organization Network (ACTION)

Pytorch implementation for "Iterative Human and Automated Identification of Wildlife Images" (Nature -Machine Intelligence, 2021)

A collection of modules to programmatically search for/download imagery from live cam feeds across the state of California.

ACES is a workflow to query small sequences in a large set of genomes. It provides several outputs including BLAST results, a multiple sequence alignment file, a graphical fragment assembly file, and a phylogenetic tree file.

Code for training and evaluating a detector for the USGS Izembek goose survey dataset

The Image Level Label to Bounding Box (IL2BB) pipeline automates the generation of labeled bounding boxes by leveraging an organization’s previous labeling efforts.

A Flask web application for the classification of bird species built using TFServing, Docker and MySQL.

The pipeline used to calculate evolutionary conservation featured in the INTAA web server.

OH!SHOWN 野生動物出沒痕跡通報系統

Segmentation of coral reefs in benthic imagery to quantify the long-term growth or decline of coral cover within marine protected areas.