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Found 10 papers, 3 papers with code
Sharp inequality for $\ell_p$ quasi-norm and $\ell_q$-norm with $0<p\leq 1$ and $q>1$
A sharp inequality for $\ell_p$ quasi-norm with $0<p\leq 1$ and $\ell_q$-norm with $q>1$ is derived, which shows that the difference between $\|\textbf{\textit{x}}\|_p$ and $\|\textbf{\textit{x}}\|_q$ of an $n$-dimensional signal $\textbf{\textit{x}}$ is upper bounded by the difference between the maximum and minimum absolute value in $\textbf{\textit{x}}$.
Interference-Resilient OFDM Waveform Design with Subcarrier Interval Constraint for ISAC Systems
Conventional orthogonal frequency division multiplexing (OFDM) waveform design in integrated sensing and communications (ISAC) systems usually selects the channels with high-frequency responses to transmit communication data, which does not fully consider the possible interference in the environment.
Towards ISAC-Empowered Vehicular Networks: Framework, Advances, and Opportunities
Connected and autonomous vehicle (CAV) networks face several challenges, such as low throughput, high latency, and poor localization accuracy.
Spatio-Temporal Point Process for Multiple Object Tracking
As such, we propose a novel framework that can effectively predict and mask-out the noisy and confusing detection results before associating the objects into trajectories.
Name Your Colour For the Task: Artificially Discover Colour Naming via Colour Quantisation Transformer
Besides, our colour quantisation method also offers an efficient quantisation method that effectively compresses the image storage while maintaining high performance in high-level recognition tasks such as classification and detection.
Exploring Resolution and Degradation Clues as Self-supervised Signal for Low Quality Object Detection
Image restoration algorithms such as super resolution (SR) are indispensable pre-processing modules for object detection in low quality images.
Multitask AET with Orthogonal Tangent Regularity for Dark Object Detection
To enhance object detection in a dark environment, we propose a novel multitask auto encoding transformation (MAET) model which is able to explore the intrinsic pattern behind illumination translation.
Ranked #1 on
2D Object Detection
on ExDark
Explainable Analysis of Deep Learning Methods for SAR Image Classification
Deep learning methods exhibit outstanding performance in synthetic aperture radar (SAR) image interpretation tasks.
RestoreDet: Degradation Equivariant Representation for Object Detection in Low Resolution Images
Image restoration algorithms such as super resolution (SR) are indispensable pre-processing modules for object detection in degraded images.
Integrated Sensing and Communications for V2I Networks: Dynamic Predictive Beamforming for Extended Vehicle Targets
The first stage is exploited for ISAC transmission, where a wide beam is adopted for both communication and sensing.
