Results 1 to 10 of about 89 (83)
Spoofing Herzog and Herzog Spoofing [PDF]
Transit, 2010 Author(s): Ames, Eric | Abstract: This essay explores how humor, parody, and self-parody have shaped and reshaped the public image of the filmmaker Werner Herzog, especially since the 1990s and with the help of various spectators, particularly those who create and circulate their own images of the iconic German director. To see this dynamic at work, we
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Spoof plasmon hybridization [PDF]
Laser & Photonics Reviews, 2017 AbstractPlasmon hybridization between closely spaced nanoparticles yields new hybrid modes not found in individual constituents, allowing for the engineering of resonance properties as well as field enhancement capabilities of metallic nanostructure.
Zhang, Jingjing +5 more
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Spoof Diarization: "What Spoofed When" in Partially Spoofed Audio
Interspeech 2024This paper defines Spoof Diarization as a novel task in the Partial Spoof (PS) scenario. It aims to determine what spoofed when, which includes not only locating spoof regions but also clustering them according to different spoofing methods. As a pioneering study in spoof diarization, we focus on defining the task, establishing evaluation metrics, and ...
Zhang, Lin +6 more
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On Disentangling Spoof Trace for Generic Face Anti-spoofing [PDF]
, 2020 Prior studies show that the key to face anti-spoofing lies in the subtle image pattern, termed "spoof trace", e.g., color distortion, 3D mask edge, Moire pattern, and many others. Designing a generic anti-spoofing model to estimate those spoof traces can improve not only the generalization of the spoof detection, but also the interpretability of the ...
Liu, Yaojie +2 more
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Journal of Field Robotics, EarlyView.ABSTRACT Personal autonomous vehicles can sense their surrounding environment, plan their route, and drive with little or no involvement of human drivers. Despite the latest technological advancements and the hopeful announcements made by leading entrepreneurs, to date no personal vehicle is approved for road circulation in a “fully” or “semi ...
Xingshuai Dong +13 more
wiley +1 more source
International Journal of Satellite Communications and Networking, EarlyView.ABSTRACT The integration of low Earth orbit (LEO) satellite constellations with commercial aircraft communication systems presents critical challenges in maintaining continuous connectivity during dynamic flight conditions. Current geostationary satellite systems suffer from high round‐trip latency (>$$ > $$ 500 ms) and inadequate coverage at high ...
Raúl Parada +4 more
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Advanced Hybrid Techniques for Cyberattack Detection and Defense in IoT Networks
SECURITY AND PRIVACY, Volume 8, Issue 2, March/April 2025.ABSTRACT The Internet of Things (IoT) represents a vast network of devices connected to the Internet, making it easier for users to connect to modern technology. However, the complexity of these networks and the large volume of data pose significant challenges in protecting them from persistent cyberattacks, such as distributed denial‐of‐service (DDoS)
Zaed S. Mahdi +2 more
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CAAI Transactions on Intelligence Technology, EarlyView.Abstract Graph neural networks (GNNs) have revolutionised the processing of information by facilitating the transmission of messages between graph nodes. Graph neural networks operate on graph‐structured data, which makes them suitable for a wide variety of computer vision problems, such as link prediction, node classification, and graph classification.
Amit Sharma +4 more
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A Probability‐Aware AI Framework for Reliable Anti‐Jamming Communication
CAAI Transactions on Intelligence Technology, EarlyView.ABSTRACT Adversarial jamming attacks have increased on communication systems, causing distortion and threatening transmissions. Typical attacks rely on traditional, well‐defined cryptographic protocols and frequency‐hopping techniques. Nevertheless, these techniques become vulnerable when facing intelligent jammers.
Tawfeeq Shawly, Ahmed A. Alsheikhy
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A Survey for Deep Reinforcement Learning Based Network Intrusion Detection
Applied AI Letters, Volume 7, Issue 2, June 2026.This paper surveys deep reinforcement learning (DRL) for network intrusion detection, evaluating model efficiency, minority attack detection, and dataset imbalance. Findings show DRL achieves state‐of‐the‐art results on public datasets, sometimes surpassing traditional deep learning.
Wanrong Yang +3 more
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