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Found 19 papers, 4 papers with code
DeepCRF: Deep Learning-Enhanced CSI-Based RF Fingerprinting for Channel-Resilient WiFi Device Identification
This paper presents DeepCRF, a new framework that harnesses deep learning to extract subtle micro-signals from channel state information (CSI) measurements, enabling robust and resilient radio-frequency fingerprinting (RFF) of commercial-off-the-shelf (COTS) WiFi devices across diverse channel conditions.
Age of Information-Oriented Probabilistic Link Scheduling for Device-to-Device Networks
However, finding the optimal policy for the formulated MDP in its original form is challenging due to the intertwined AoI dynamics of all D2D links.
Spurious Stationarity and Hardness Results for Mirror Descent
Despite the considerable success of Bregman proximal-type algorithms, such as mirror descent, in machine learning, a critical question remains: Can existing stationarity measures, often based on Bregman divergence, reliably distinguish between stationary and non-stationary points?
Towards Channel-Resilient CSI-Based RF Fingerprinting using Deep Learning
The construction of a framework that is resilient to channel variability is essential for the practical deployment of CSI-RFF techniques.
Physical-Layer Authentication of Commodity Wi-Fi Devices via Micro-Signals on CSI Curves
This paper presents a new radiometric fingerprint that is revealed by micro-signals in the channel state information (CSI) curves extracted from commodity Wi-Fi devices.
The Power of Large Language Models for Wireless Communication System Development: A Case Study on FPGA Platforms
We begin by exploring LLM-assisted code refactoring, reuse, and validation, using an open-source software-defined radio (SDR) project as a case study.
Pulse Shape-Aided Multipath Delay Estimation for Fine-Grained WiFi Sensing
Considering the limited number of paths in physical environments, we formulate the multipath delay estimation as a sparse recovery problem.
RF-Based Simultaneous Localization and Source Seeking for Multi-Robot Systems
This paper considers a radio-frequency (RF)-based simultaneous localization and source-seeking (SLASS) problem in multi-robot systems, where multiple robots jointly localize themselves and an RF source using distance-only measurements extracted from RF signals and then control themselves to approach the source.
Consecutive Pretraining: A Knowledge Transfer Learning Strategy with Relevant Unlabeled Data for Remote Sensing Domain
Currently, under supervised learning, a model pretrained by a large-scale nature scene dataset and then fine-tuned on a few specific task labeling data is the paradigm that has dominated the knowledge transfer learning.
A Behavior-aware Graph Convolution Network Model for Video Recommendation
Interactions between users and videos are the major data source of performing video recommendation.
Towards Efficient Graph Convolutional Networks for Point Cloud Handling
In this paper, we aim at improving the computational efficiency of graph convolutional networks (GCNs) for learning on point clouds.
Capturing Detailed Deformations of Moving Human Bodies
The key idea behind our system is a new type of motion capture suit which contains a special pattern with checkerboard-like corners and two-letter codes.
The Card Shuffling Hypotheses: Building a Time and Memory Efficient Graph Convolutional Network
State-of-the-art GCNs adopt $K$-nearest neighbor (KNN) searches for local feature aggregation and feature extraction operations from layer to layer.
Multi-person 3D Pose Estimation in Crowded Scenes Based on Multi-View Geometry
In this paper, we depart from the multi-person 3D pose estimation formulation, and instead reformulate it as crowd pose estimation.
Ranked #13 on
3D Multi-Person Pose Estimation
on Panoptic
(using extra training data)
3D Multi-Person Human Pose Estimation
3D Multi-Person Pose Estimation
+2
Flow Sampling: Network Monitoring in Large-Scale Software-Defined IoT Networks
Software-defined Internet-of-Things networking (SDIoT) greatly simplifies the network monitoring in large-scale IoT networks by per-flow sampling, wherein the controller keeps track of all the active flows in the network and samples the IoT devices on each flow path to collect real-time flow statistics.
Optimizing Information Freshness in Two-Hop Status Update Systems under a Resource Constraint
We derive approximate closed-form expressions of the average AoI at the destination, and the average number of forwarding operations at the relay for the DTR policy, by modelling the tangled evolution of age at relay and destination as a Markov chain (MC).
Information Theory Networking and Internet Architecture Signal Processing Information Theory
Physical Layer Authentication for Non-Coherent Massive SIMO-Enabled Industrial IoT Communications
This method realizes PLA by embedding an authentication signal (tag) into a message signal, referred to as "message-based tag embedding".
Curvature: A signature for Action Recognition in Video Sequences
In this paper, a novel signature of human action recognition, namely the curvature of a video sequence, is introduced.
Multi-Normal Estimation via Pair Consistency Voting
This paper presents a unified definition for point cloud normals of feature and non-feature points, which allows feature points to possess multiple normals.
