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Found 9 papers, 3 papers with code
Integrated Sensing and Communication Under DISCO Physical-Layer Jamming Attacks
Moreover, a theoretical analysis is conducted to quantify the impact of DISCO jamming attacks.
Vision Transformer-based Multimodal Feature Fusion Network for Lymphoma Segmentation on PET/CT Images
Methods: Our lymphoma segmentation approach combines a vision transformer with dual encoders, adeptly fusing PET and CT data via multimodal cross-attention fusion (MMCAF) module.
DISCO Might Not Be Funky: Random Intelligent Reflective Surface Configurations That Attack
Moreover, we outline future research directions and challenges for the DIRS-based FPJ and its anti-jamming precoding to stimulate this line of research and pave the way for practical applications.
Anti-Jamming Precoding Against Disco Intelligent Reflecting Surfaces Based Fully-Passive Jamming Attacks
Numerical results are also presented to evaluate the effectiveness of the proposed anti-jamming precoder against the DIRS-based FPJs and the feasibility of the designed data frame used by the legitimate AP to estimate the statistical characteristics.
An Anti-Jamming Strategy for Disco Intelligent Reflecting Surfaces Based Fully-Passive Jamming Attacks
Emerging intelligent reflecting surfaces (IRSs) significantly improve system performance, while also pose a huge risk for physical layer security.
Temporal Dynamic Synchronous Functional Brain Network for Schizophrenia Diagnosis and Lateralization Analysis
The available evidence suggests that dynamic functional connectivity (dFC) can capture time-varying abnormalities in brain activity in resting-state cerebral functional magnetic resonance imaging (rs-fMRI) data and has a natural advantage in uncovering mechanisms of abnormal brain activity in schizophrenia(SZ) patients.
Disco Intelligent Reflecting Surfaces: Active Channel Aging for Fully-Passive Jamming Attacks
A theoretical analysis of the proposed DIRS-based FPJ that provides an evaluation of the DIRS-based jamming attacks is derived.
Segment as Points for Efficient Online Multi-Object Tracking and Segmentation
The resulting online MOTS framework, named PointTrack, surpasses all the state-of-the-art methods including 3D tracking methods by large margins (5. 4% higher MOTSA and 18 times faster over MOTSFusion) with the near real-time speed (22 FPS).
Multi-Object Tracking
Multi-Object Tracking and Segmentation
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Towards End-to-End License Plate Detection and Recognition: A Large Dataset and Baseline
Most current license plate (LP) detection and recognition approaches are evaluated on a small and usually unrepresentative dataset since there are no publicly available large diverse datasets.
