26 citations · 59 across the 8 of their papers we have counts for
8 papers
Outlier detection in maritime environments using AIS data and deep recurrent architectures
Constantine Maganaris, Eftychios Protopapadakis, Nikolaos Doulamis
A methodology based on deep recurrent models for maritime surveillance, over publicly available Automatic Identification System (AIS) data, is presented in this paper. The setup em…
Multi-scale Intervention Planning based on Generative Design
Ioannis Kavouras, Ioannis Rallis, Emmanuel Sardis +3
The scarcity of green spaces, in urban environments, consists a critical challenge. There are multiple adverse effects, impacting the health and well-being of the citizens. Small s…
Learning using privileged information for segmenting tumors on digital mammograms
Ioannis N. Tzortzis, Konstantinos Makantasis, Ioannis Rallis +3
Limited amount of data and data sharing restrictions, due to GDPR compliance, constitute two common factors leading to reduced availability and accessibility when referring to medi…
Comparison of machine learning algorithms for merging gridded satellite and earth-observed precipitation data
Georgia Papacharalampous, Hristos Tyralis, Anastasios Doulamis +1
Gridded satellite precipitation datasets are useful in hydrological applications as they cover large regions with high density. However, they are not accurate in the sense that the…
Comparison of tree-based ensemble algorithms for merging satellite and earth-observed precipitation data at the daily time scale
Georgia Papacharalampous, Hristos Tyralis, Anastasios Doulamis +1
Merging satellite products and ground-based measurements is often required for obtaining precipitation datasets that simultaneously cover large regions with high density and are mo…
A Few-Shot Attention Recurrent Residual U-Net for Crack Segmentation
Iason Katsamenis, Eftychios Protopapadakis, Nikolaos Bakalos +3
Recent studies indicate that deep learning plays a crucial role in the automated visual inspection of road infrastructures. However, current learning schemes are static, implying n…