Autonomous drones based forest surveillance using Faster R-CNN
Author:
Affiliation:
1. VR Siddhartha Engineering College, India,Department of Computer Science & Engineering,Vijayawada,India
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9751779/9751722/09752298.pdf?arnumber=9752298
Reference24 articles.
1. UAV Image-based Forest Fire Detection Approach Using Convolutional Neural Network
2. Early Detection of Forest Fire Based on Unmaned Aerial Vehicle Platform
3. Forest Fire Detection with Color Features and Wavelet Analysis Based on Aerial Imagery
4. Early Wildfire Smoke Detection Based on Motion-based Geometric Image Transformation and Deep Convolutional Generative Adversarial Networks
5. Real-Time Detection of Ground Objects Based on Unmanned Aerial Vehicle Remote Sensing with Deep Learning: Application in Excavator Detection for Pipeline Safety
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1. Accuracy Assessment of Drone Real-Time Open Burning Imagery Detection for Early Wildfire Surveillance;Forests;2023-09-12
2. CLIP: Train Faster with Less Data;2023 IEEE International Conference on Big Data and Smart Computing (BigComp);2023-02
3. DroneNet: Crowd Density Estimation using Self-ONNs for Drones;2023 IEEE 20th Consumer Communications & Networking Conference (CCNC);2023-01-08
4. BHAC-MRI: Backdoor and Hybrid Attacks on MRI Brain Tumor Classification Using CNN;Image Analysis and Processing – ICIAP 2023;2023
5. Drone Assisted Deep Learning based Wildfire Detection System;2022 Seventh International Conference on Parallel, Distributed and Grid Computing (PDGC);2022-11-25
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