7 citations · 9 across the 8 of their papers we have counts for
7 papers · 1 filter
Domain Adaptation via Feature Refinement
Savvas Karatsiolis, Andreas Kamilaris
We propose Domain Adaptation via Feature Refinement (DAFR2), a simple yet effective framework for unsupervised domain adaptation under distribution shift. The proposed method syner…
A model-agnostic approach for generating Saliency Maps to explain inferred decisions of Deep Learning Models
Savvas Karatsiolis, Andreas Kamilaris
The widespread use of black-box AI models has raised the need for algorithms and methods that explain the decisions made by these models. In recent years, the AI research community…
Exploiting Digital Surface Models for Inferring Super-Resolution for Remotely Sensed Images
Savvas Karatsiolis, Chirag Padubidri, Andreas Kamilaris
Despite the plethora of successful Super-Resolution Reconstruction (SRR) models applied to natural images, their application to remote sensing imagery tends to produce poor results…
Focusing on Shadows for Predicting Heightmaps from Single Remotely Sensed RGB Images with Deep Learning
Savvas Karatsiolis, Andreas Kamilaris
Estimating the heightmaps of buildings and vegetation in single remotely sensed images is a challenging problem. Effective solutions to this problem can comprise the stepping stone…
The pursuit of beauty: Converting image labels to meaningful vectors
Savvas Karatsiolis, Andreas Kamilaris
A challenge of the computer vision community is to understand the semantics of an image, in order to allow image reconstruction based on existing high-level features or to better a…
Identification of Tree Species in Japanese Forests based on Aerial Photography and Deep Learning
Sarah Kentsch, Savvas Karatsiolis, Andreas Kamilaris +2
Natural forests are complex ecosystems whose tree species distribution and their ecosystem functions are still not well understood. Sustainable management of these forests is of hi…
Training Deep Learning Models via Synthetic Data: Application in Unmanned Aerial Vehicles
Andreas Kamilaris, Corjan van den Brink, Savvas Karatsiolis
This paper describes preliminary work in the recent promising approach of generating synthetic training data for facilitating the learning procedure of deep learning (DL) models, w…