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Relevant bibliographies by topics / SUAV detection techniques

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Academic literature on the topic 'SUAV detection techniques'

Author: Grafiati

Published: 5 June 2025

Last updated: 2 August 2025

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Journal articles on the topic "SUAV detection techniques"

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Vinaya, Bamane, Sapkale Jayesh, Pawar Anisha, P.G.Chilveri, Akhter Nargis, and Arockia Bazil Raj A. "A Review on AI Based Target Classification Advanced Techniques." International Journal of Engineering Research and Reviews 10, no. 4 (2022): 88–99. https://doi.org/10.5281/zenodo.7491584.

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<strong>Abstract:</strong> As we know that surveillance in the air has become one of the important defence precautions that we must take. So, for that reason radar plays a very important role as it captures images that can fool a human eye and then converts it into process able data. Then this data can be sorted and classified by our Artificial Intelligence Algorithms. Even here we have a variety of models for this purpose but it is up to us and our data and the output we expect, which Algorithm should be used. Here in this Survey, we have researched on different Radar Systems as well as the d

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Yang Zhang, Nirvana Meratnia, and Paul Havinga. "Outlier Detection Techniques for Wireless Sensor Networks: A Survey." IEEE Communications Surveys & Tutorials 12, no. 2 (2010): 159–70. http://dx.doi.org/10.1109/surv.2010.021510.00088.

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Cheng, Tsung-Huan, Ying-Dar Lin, Yuan-Cheng Lai, and Po-Ching Lin. "Evasion Techniques: Sneaking through Your Intrusion Detection/Prevention Systems." IEEE Communications Surveys & Tutorials 14, no. 4 (2012): 1011–20. http://dx.doi.org/10.1109/surv.2011.092311.00082.

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Kaur, Ratinder, and Maninder Singh. "A Survey on Zero-Day Polymorphic Worm Detection Techniques." IEEE Communications Surveys & Tutorials 16, no. 3 (2014): 1520–49. http://dx.doi.org/10.1109/surv.2014.022714.00160.

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Fragkiadakis, Alexandros G., Elias Z. Tragos, and Ioannis G. Askoxylakis. "A Survey on Security Threats and Detection Techniques in Cognitive Radio Networks." IEEE Communications Surveys & Tutorials 15, no. 1 (2013): 428–45. http://dx.doi.org/10.1109/surv.2011.122211.00162.

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Patil, Sujata. "A Data-Driven Approach to Small UAV Detection using Micro-Doppler Signatures and Deep Convolutional Architecture." International Scientific Journal of Engineering and Management 04, no. 05 (2025): 1–9. https://doi.org/10.55041/isjem03688.

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Abstract - Detecting and classifying Small Unmanned Aerial Vehicles (SUAVs) remains a complex task for radar systems due to their compact size and radar cross-section, which often resemble those of birds, insects, or background clutter. As SUAVs are increasingly used in security-sensitive contexts, improving detection methods is essential for defence and airspace monitoring. Traditional radar approaches often fall short in reliably distinguishing SUAVs from similar targets. However, micro-Doppler signatures derived from Continuous Wave (CW) radar offer valuable motion-based features that can h

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Hollenbeck, Derek, Demitrius Zulevic, and Yangquan Chen. "Advanced Leak Detection and Quantification of Methane Emissions Using sUAS." Drones 5, no. 4 (2021): 117. http://dx.doi.org/10.3390/drones5040117.

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Detecting and quantifying methane emissions is gaining an increasingly vital role in mitigating emissions for the oil and gas industry through early detection and repair and will aide our understanding of how emissions in natural ecosystems are playing a role in the global carbon cycle and its impact on the climate. Traditional methods of measuring and quantifying emissions utilize chamber methods, bagging individual equipment, or require the release of a tracer gas. Advanced leak detection techniques have been developed over the past few years, utilizing technologies, such as optical gas imag

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Kyritsis, Alexandros, Rodoula Makri, and Nikolaos Uzunoglu. "Small UAS Online Audio DOA Estimation and Real-Time Identification Using Machine Learning." Sensors 22, no. 22 (2022): 8659. http://dx.doi.org/10.3390/s22228659.

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The wide range of unmanned aerial system (UAS) applications has led to a substantial increase in their numbers, giving rise to a whole new area of systems aiming at detecting and/or mitigating their potentially unauthorized activities. The majority of these proposed solutions for countering the aforementioned actions (C-UAS) include radar/RF/EO/IR/acoustic sensors, usually working in coordination. This work introduces a small UAS (sUAS) acoustic detection system based on an array of microphones, easily deployable and with moderate cost. It continuously collects audio data and enables (a) the d

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Sandhya, Guduru. "Web3 Smart Contract Security: Slither Static Analysis, Echidna Fuzzing, and Certora Formal Verification." European Journal of Advances in Engineering and Technology 11, no. 5 (2024): 147–50. https://doi.org/10.5281/zenodo.15387253.

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Ensuring the security of smart contracts is essential in Web3 development, as vulnerabilities in Solidity-based agreements can result in significant financial and operational risks. This study explores automated security auditing techniques, focusing on Slither for static analysis, Echidna for property-based fuzz testing, and Certora for formal verification. By integrating these tools, the research enhances vulnerability detection and reduces reliance on manual audits. Additionally, the study assesses Maximum Extractable Value (MEV) risks and evaluates Flashbots SUAVE as a mitigation strategy.

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Yakno, Marlina, Junita Mohamad-Saleh, and Mohd Zamri Ibrahim. "Dorsal Hand Vein Image Enhancement Using Fusion of CLAHE and Fuzzy Adaptive Gamma." Sensors 21, no. 19 (2021): 6445. http://dx.doi.org/10.3390/s21196445.

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Enhancement of captured hand vein images is essential for a number of purposes, such as accurate biometric identification and ease of medical intravenous access. This paper presents an improved hand vein image enhancement technique based on weighted average fusion of contrast limited adaptive histogram equalization (CLAHE) and fuzzy adaptive gamma (FAG). The proposed technique is applied using three stages. Firstly, grey level intensities with CLAHE are locally applied to image pixels for contrast enhancement. Secondly, the grey level intensities are then globally transformed into membership p

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Conference papers on the topic "SUAV detection techniques"

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Soni, Samraddhi, Mainak Chakraborty, and A. A. Bazil Raj. "AI based Small Unmanned Aerial Vehicle (SUAV) Targets Detection and Tracking Techniques." In 2022 International Conference on Augmented Intelligence and Sustainable Systems (ICAISS). IEEE, 2022. http://dx.doi.org/10.1109/icaiss55157.2022.10010718.

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Chauhan, Balwantray C., and Terry A. McCormick. "Influence of the Cardiac Cycle on Topographic Measurements of the Optic Nerve Head and Peripapillary Retina." In Vision Science and its Applications. Optica Publishing Group, 1995. http://dx.doi.org/10.1364/vsia.1995.sua2.

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Confocal scanning laser tomography is an imaging technique used for determining the topography of the optic nerve head and retina. Since images can be acquired through undilated pupils and analysed rapidly, the technique is particularly suited for clinical use. One of the largest potentials of scanning laser tomography is the detection of structural alterations in the optic nerve head and peripapillary retina caused by glaucoma. The ability to detect change depends on obtaining an accurate estimate of test-retest variability of regional measurements due to instrumental, computational and a hos

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Sevil, Hakki Erhan, Atilla Dogan, Kamesh Subbarao, and Brian Huff. "Evaluation of extant computer vision techniques for detecting intruder sUAS." In 2017 International Conference on Unmanned Aircraft Systems (ICUAS). IEEE, 2017. http://dx.doi.org/10.1109/icuas.2017.7991373.

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