Animal Detection in Man-made Environments using Deep Learning
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Updated
Jul 6, 2023 - Python
Animal Detection in Man-made Environments using Deep Learning
Animal Detection using YOLOv5
A U-Net-based deep learning ensemble model for wildebeest-sized animal detection from satellite imagery. A version used for the paper accepted by Nature Communications: "Deep learning enables satellite-based monitoring of large populations of terrestrial mammals across heterogeneous landscape" (https://rdcu.be/dc8bU).
Detection of Animals in camera trapped images using RetinaNet in pytorch.
🐬 Code accompanying the article "Weakly Supervised Detection of Marine Animals in High Resolution Aerial Images"
Closed-loop feedback optogenetic system
Animal Detection and Classification using YOLO
An application which uses the camera to detect and identify animals, sounding an alert after their detection and emailing the owner about it
Agri-Pal is the simplest solution to aid a farmer in Agriculture - Crop and Poultry Farming. Agri-Pal is a simple Plug n Play device ensuring Disease Detection and Animal Breach Detection.
Image Processing and Deep Learning algorithm to detect leopards from a live camera feed.
Animals object detection such as deer, horse, and rabbit in diverse settings using YOLOv5
Sem. VI Neural networks created to detect animals hidden in their natural environments.
HSE project. Idea to create animal detection system with voice guidance
Animal detection application
This Python-based code that utilizes OpenCV's DNN module with MobileNetSSD to detect animals in the farmland.The code provides a GUI using Tkinter, allowing users to select a video file and start the animal detection process. When an animal is detected, an alert is triggered with a siren sound.
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