15 citations · 16 across the 6 of their papers we have counts for
4 papers · 1 filter
Do Satellite Tasks Need Special Pretraining?
Ani Vanyan, Alvard Barseghyan, Hakob Tamazyan +4
Foundation models have advanced machine learning across various modalities, including images. Recently multiple teams trained foundation models specialized for remote sensing appli…
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…
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…
Analyzing Local Representations of Self-supervised Vision Transformers
Ani Vanyan, Alvard Barseghyan, Hakob Tamazyan +3
In this paper, we present a comparative analysis of various self-supervised Vision Transformers (ViTs), focusing on their local representative power. Inspired by large language mod…