Identify plants, birds, and insects in photos. Should an identification to species be unsuccessful, an identification to a higher taxonomic level - like genus, family, or order - is made.
Yellow Sticky Traps Dataset with improved annotations. Based on: "Raw data from Yellow Sticky Traps with insects for training of deep learning Convolutional Neural Network for object detection" by A.T. Nieuwenhuizen et. al.
SwarmSight is a published video analysis tool with modules to a) to track insect antenna and proboscis movements and b) assess the aggregate movement or activity levels of groups or swarms of animals. Developed at Arizona State University, it is used by behavioral scientists to study the behavior of insects, birds, fish, and other animals.
📈 Program that calculates design parameters for an ornithopter in level flight
📈 Simulation of an oscillating airfoil
Detection and analysis of insect defoliators in tree rings
Raspberry Pi 3 bundle for Kaggle dataset "Wingbeats"
Like SMPL but for bugs
A new tool for detecting changes in dynamic rules in population time series data
An iOS application that uses a Machine Learning model to classify different species of butterflies that can be seen in Portugal and around Europe.
Android app for Kaggle dataset "Wingbeats"
Insect Explorer is a fascinating web app that allows users to search, identify, and learn about various insect species using free open-data APIs. This interactive tool is perfect for entomologists, nature enthusiasts, and students who want detailed scientific information and images of insects.
Polytrack is design to track unmarked freely foraging insects in outdoor environments and monitor their pollination behaviour.
A programming game and fun biological simulation used in first-year university programming modules.
Lepilens is a Web application that uses a Machine Learning model perform classification to be able to classify different species of butterflies that can be found in Portugal and across Europe.
Track your insect collection and make entomology-ready labels.
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