Detection, Tracking, and Interdiction for Amateur Drones

By Ismail Güvenç, Farshad Koohifar, Simran Singh, Mihail L. Sichitiu, David W. Matolak. IEEE Communications Magazine, 2018

300 citations recorded by the source corpus.

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

A Comprehensive Overview on 5G-and-Beyond Networks With UAVs: From Communications to Sensing and Intelligence (2020, methodology): “For example, the key techniques of detection, tracking, and interdiction of amateur drones are discussed in [265].”
Survey on Collaborative Smart Drones and Internet of Things for Improving Smartness of Smart Cities (2019, background): “The studies in [27] and [22] focused on the”
A Generative Approach Towards Improved Robotic Detection of Marine Litter (2019, background): “Recent developments in computer vision, particularly spurred on by advances in deep convolutional neural networks (CNNs), have greatly benefited mobile robotics in applications such as autonomous driving [1], drone surveillance [2], harvesting machines [3], and milking robots [4].”
Machine Learning-Based Drone Detection and Classification: State-of-the-Art in Research (2019, background): “Also, some review articles have appeared which consider single or multiple modalities [4], [5].”