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Found 9 papers, 0 papers with code
Non-Contact Acquisition of PPG Signal using Chest Movement-Modulated Radio Signals
With this, we first utilize principal component analysis for dimensionality reduction of the radio data.
On the Interplay of Artificial Intelligence and Space-Air-Ground Integrated Networks: A Survey
In this work, we aim to investigate the interplay of AI and SAGINs by providing a holistic overview of state-of-the-art research in AI-enabled SAGINs.
Multi-RIS-Enabled 3D Sidelink Positioning
Positioning is expected to be a core function in intelligent transportation systems (ITSs) to support communication and location-based services, such as autonomous driving, traffic control, etc.
Equitable 6G Access Service via Cloud-Enabled HAPS for Optimizing Hybrid Air-Ground Networks
The evolvement of wireless communication services concurs with significant growth in data traffic, thereby inflicting stringent requirements on terrestrial networks.
Weight Vector Tuning and Asymptotic Analysis of Binary Linear Classifiers
Applying this method to a number of linear classifiers under a variety of data dimensionality and sample size settings reveals that the classification performance loss due to non-optimal native hyperparameters can be compensated for by weight vector tuning.
Details Preserving Deep Collaborative Filtering-Based Method for Image Denoising
Extensive experiments show that the DeepCoFiB performed quantitatively (in terms of PSNR and SSIM) and qualitatively (visually) better than many of the state-of-the-art denoising algorithms.
Dense-Sparse Deep CNN Training for Image Denoising
We extend this training approach to a reduced DnCNN (RDnCNN) network resulting in a faster denoising network with significantly reduced parameters and comparable performance to the DnCNN.
Collaborative Filtering-Based Method for Low-Resolution and Details Preserving Image Denoising
Many also distort images of lower resolution resulting in a partial or complete structural loss.
Risk Convergence of Centered Kernel Ridge Regression with Large Dimensional Data
This paper carries out a large dimensional analysis of a variation of kernel ridge regression that we call \emph{centered kernel ridge regression} (CKRR), also known in the literature as kernel ridge regression with offset.
