THESIS - Aerial Monitoring System Web Application
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Updated
Apr 27, 2023 - TypeScript
THESIS - Aerial Monitoring System Web Application
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. 👨🏫
You can use this repo to generate semantic segmentations on drone images using the trained model's checkpoint.
Object Detection from Aierial Images with Different Approaches
O GCP Finder é um programa identifica Aruco Markers em imagens.
Semi-supervised aerial image object detection
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.
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%
An oriented object detection framework based on TensorRT
YOLOv8 Aerial Sheep Detection and Counting. Simulated on Gazebo.
Deep Learning model implementation for Fire detection both classification and segmentation from the FLAME dataset.
A reimplementation of the S2ANet algorithm for Oriented Object Detection
Code for finding targets in aerial imagery.
Create plastic trash aerial image dataset - HAIDA
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
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).
The code for “Oriented RepPoints for Aerial Object Detection (CVPR 2022)”
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