arXiv Machine Learning

Compact convolutional neural networks for AI-based drone detection system

arXiv:2607. 16455v1 Announce Type: new Abstract: The increasing use of first-person-view drones in modern conflicts has created a demand for compact and reliable detection systems capable of operating in complex electromagnetic environments.

arXiv Machine Learning

Jul 14

End-to-End Real-Time Drone-Based Person Detection Framework Using Deep Learning

arXiv:2607. 10605v1 Announce Type: cross Abstract: In recent years, Unmanned Aerial Vehicles (UAVs) or drones have gained rapid response in terms of security, search and rescue (SAR), border surveillance, etc.

By Payel Sarmah, Ayush Ranjan, Piyush Kaushik Bhattacharyya, Anil Kr. Shaw, Pradip Kr. Das

robotics

arXiv Machine Learning

Jun 11

DroneShield-AI: A Multi-Modal Sensor Fusion Framework for Real-Time Autonomous Drone Threat Detection, Behavioral Intent Classification, and Swarm Intelligence in Contested Airspace

arXiv:2606. 11687v1 Announce Type: cross Abstract: Unmanned Aerial Vehicle (UAV) threats have emerged as a defining security challenge of the 21st century.

By Marius Bayizere

agents robotics multimodal safety

arXiv Machine Learning

Aug 4

An Uncertainty-Driven Hybrid Deep Learning Approach for Broad-Coverage RF Modulation Recognition

arXiv:2608. 00796v1 Announce Type: cross Abstract: Automatic RF modulation recognition is of critical importance in spectrum monitoring, electronic warfare, and cognitive radio applications, where low signal-to-noise ratio (SNR) conditions and the growing diversity of modulation schemes limit the performance of existing methods.

By Nurettin Safak, Durdu Can Yerdeyatar, Muhammet Sefa Demirel, Alperen Marasli, Taha Eren Atmaca, Ozgun Ersoy

arXiv AI

Jun 16

Multi-Sensor Fusion for UAV Classification Based on Feature Maps of Image and Radar Data

arXiv:2410. 16089v2 Announce Type: replace Abstract: The unique cost, flexibility, speed, and efficiency of modern UAVs make them an attractive choice in many applications in contemporary society.

By Nikos Sakellariou (Centre for Research and Technology Hellas, Information Technologies Institute), Antonios Lalas (Centre for Research and Technology Hellas, Information Technologies Institute), Konstantinos Votis (Centre for Research and Technology Hellas, Information Technologies Institute), Dimitrios Tzovaras (Centre for Research and Technology Hellas, Information Technologies Institute)

computer-vision

arXiv Machine Learning

Jul 2

Computer vision-based neural networks for radioisotope identification in urban environments

arXiv:2607. 00270v1 Announce Type: cross Abstract: Algorithm development for radioisotope identification in mobile urban search scenarios face significant challenges from non-uniform backgrounds, momentary source encounters, and severe class imbalance between rare threat signatures and background measurements.

By Masen Bachleda, Peter Lalor

llms computer-vision benchmarks

arXiv AI

22h ago

Training with synthetic data for drone detection in thermal imagery

arXiv:2608. 17799v1 Announce Type: cross Abstract: Ground-to-Air (G2A) drone detection in medium- and long-wave infrared (MWIR/LWIR) imagery is challenging due to reduced texture information, sensor noise, weak thermal contrast, and the scarcity of annotated data.

By Tanel Liiv, Sander Soodla, Nzamba Bignoumba, Alma M. Liezenga, Toomas Pruuden

robotics fine-tuning safety

arXiv Machine Learning

Jun 2

Classification and detection of multiple UAVs using rational Gaussian wavelet neural networks

arXiv:2605. 26310v2 Announce Type: replace Abstract: The detection of unmanned aerial vehicles (UAVs) is important for the protection of civilian and military infrastructure.

By Ungv\'ari Gerg\H{o}, Ferenc Braun, Attila \'Amon, P\'eter Kackst\"adter, J\'anos Volk, P\'eter Kov\'acs, Tam\'as D\'ozsa

robotics safety

arXiv Machine Learning

Jul 23

DREMnet: An Interpretable Denoising Framework for Semi-Airborne Transient Electromagnetic Signal

arXiv:2503. 22223v2 Announce Type: replace Abstract: The semi-airborne transient electromagnetic method (SATEM) is capable of conducting rapid surveys over large-scale and hard-to-reach areas.

By Shuang Wang, Ming Guo, Xuben Wang, Fei Deng, Lifeng Mao, Bin Wang, Wenlong Gao

llms rag safety

arXiv AI

22h ago

Comparative Study of Out-of-the-Box Technology for Automatic Target Detection and Recognition

arXiv:2608. 17917v1 Announce Type: cross Abstract: Automatic Target Detection and Recognition (ATD/R) is critical for military decision support and (semi-)autonomous operations.

By Alma M. Liezenga, Lotte Nijskens, Henrik R. Baumann, Stefan Becker, Simon Bensberg, Niccol\`o Camarlinghi, H{\aa}vard R. Eiring, Alexander W. Johnsgaard, Tanel Liiv, Giuseppe Martino, Matteo Marturini, Matthias Rapp, Jan Erik van Woerden, Alexander Wolpert, Hugo J. Kuijf

agents computer-vision fine-tuning benchmarks

arXiv Machine Learning

Jul 30

Low-cost Embedded Breathing Rate Determination Using 802.15.4z IR-UWB Hardware for Remote Healthcare

arXiv:2504. 03772v3 Announce Type: replace-cross Abstract: Respiratory diseases account for a significant portion of global mortality.

By Anton Lambrecht, Stijn Luchie, Jaron Fontaine, Ben Van Herbruggen, Adnan Shahid, Eli De Poorter

efficiency

arXiv AI

Jul 22

Computing on the Fly: Navigating a Vision for the Future of Drone Computing

arXiv:2607. 19213v1 Announce Type: cross Abstract: The report envisions a decade in which drones move goods, medical supplies, and information at a scale comparable to national infrastructure investments like highways and the electric grid.

By Kevin Butler, Christopher Stewart, Nils Aschenbruck, Alina Gerall, Weisong Shi, Deborah Silver, Ufuk Topcu

agents robotics

arXiv AI

Jun 16

Near--Real-Time Conflict-Related Fire Detection in Sudan Using Unsupervised Deep Learning

arXiv:2512. 07925v4 Announce Type: replace-cross Abstract: Ongoing armed conflict in Sudan highlights the need for rapid monitoring of conflict-related fire-affected areas.

By Kuldip Singh Atwal, Dieter Pfoser, Daniel Rothbart

rag

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