Official code of the paper "Align Deep Features for Oriented Object Detection"

The code for “Oriented RepPoints for Aerial Object Detection (CVPR 2022)”

Detect objects in drone videos and plot them on a map

JDet is an object detection benchmark based on Jittor. Mainly focus on aerial image object detection (oriented object detection).

Official implementation for DMNet: Density map guided object detection in aerial image (CVPR 2020 EarthVision workshop)

FCOSR: A Simple Anchor-free Rotated Detector for Aerial Object Detection

YOLOv8 Aerial Sheep Detection and Counting. Simulated on Gazebo.

Deep Learning model implementation for Fire detection both classification and segmentation from the FLAME dataset.

Create plastic trash aerial image dataset - HAIDA

Semi-supervised aerial image object detection

An oriented object detection framework based on TensorRT

A reimplementation of the S2ANet algorithm for Oriented Object Detection

Object Detection from Aierial Images with Different Approaches

Successfully optimized deep learning models to detect 15 distinct objects through implementation of image tiling and innovative Strategic Aerial Homogenization for Inference (SAHI) approach to improve mean average precision by 36%

This project is about training a deep neural network to identify and track a target in simulation using Udacity's RoboND drone simulator. 🛸 Applications like this are key to many fields of robotics and the techniques applied can be extended to scenarios like advanced cruise control in autonomous vehicles or human-robot collaboration. 👨‍🏫

O GCP Finder é um programa identifica Aruco Markers em imagens.

THESIS - Aerial Monitoring System Web Application

You can use this repo to generate semantic segmentations on drone images using the trained model's checkpoint.

Web-Interface-GCP-Finder é um projeto que pretende simplificar a utilização da ferramenta GCP Finder, que em sí é um programa capaz de identificar Aruco Markers em imagens.

Code for finding targets in aerial imagery.