A5007233154- Indoor and Outdoor Localization Technologies
- Underwater Vehicles and Communication Systems
- Radio Wave Propagation Studies
- Robotics and Sensor-Based Localization
- Millimeter-Wave Propagation and Modeling
- Advanced Image and Video Retrieval Techniques
- Distributed Sensor Networks and Detection Algorithms
- Limits and Structures in Graph Theory
- Speech and Audio Processing
- Rings, Modules, and Algebras
- Advanced Topology and Set Theory
Yerevan State University
2023-2024
The challenging problem of non-line-of-sight (NLOS) localization is critical for many wireless networking applications. lack available datasets has made NLOS difficult to tackle with ML-driven methods, but recent developments in synthetic dataset generation have provided new opportunities research. This paper explores three different input representations: (i) single radio path features, (ii) link features (multi-path), and (iii) image-based representations. Inspired by the two latter...
An improper edge-coloring of a graph [Formula: see text] is mapping text]. called an interval coloring if the colors (excluding repetitions) edges incident to each vertex form integral interval. text]-improper coloring, there are at most adjacent with same color. In this note we show that complete multipartite graphs have coloring; proves conjecture Casselgren and Petrosyan.
Conventional methods for outdoor environment reconstruction rely predominantly on vision-based techniques like photogrammetry and LiDAR, facing limitations such as constrained coverage, susceptibility to environmental conditions, high computational energy demands. These challenges are particularly pronounced in applications augmented reality navigation, especially when integrated with wearable devices featuring resources budgets. In response, this paper proposes a novel approach harnessing...
Vision Transformers (ViTs) have demonstrated remarkable success in achieving state-of-the-art performance across various image-based tasks and beyond. In this study, we employ a ViT-based neural network to address the problem of indoor pathloss radio map prediction. The network's generalization ability is evaluated diverse settings, including unseen buildings, frequencies, antennas with varying radiation patterns. By leveraging extensive data augmentation techniques pretrained DINOv2...
The challenging problem of non-line-of-sight (NLOS) localization is critical for many wireless networking applications. lack available datasets has made NLOS difficult to tackle with ML-driven methods, but recent developments in synthetic dataset generation have provided new opportunities research. This paper explores three different input representations: (i) single radio path features, (ii) link features (multi-path), and (iii) image-based representations. Inspired by the two latter...