3 papers
cs.CV2026
Fusion of Pervasive RF Data with Spatial Images via Vision Transformers for Enhanced Mapping in Smart Cities
Rafayel Mkrtchyan, Armen Manukyan, Hrant Khachatrian +1
In this paper, we present a deep learning-based approach that integrates the DINOv2 architecture to improve building mapping by combining (possibly erroneous) maps from open-source…
cs.CV2025
Vision Transformers for Efficient Indoor Pathloss Radio Map Prediction
Rafayel Mkrtchyan, Edvard Ghukasyan, Khoren Petrosyan +2
Indoor pathloss prediction is a fundamental task in wireless network planning, yet it remains challenging due to environmental complexity and data scarcity. In this work, we propos…
cs.NI2024
Outdoor Environment Reconstruction with Deep Learning on Radio Propagation Paths
Hrant Khachatrian, Rafayel Mkrtchyan, Theofanis P. Raptis
Conventional methods for outdoor environment reconstruction rely predominantly on vision-based techniques like photogrammetry and LiDAR, facing limitations such as constrained cove…