17 citations · 40 across the 8 of their papers we have counts for
8 papers
Solarsystem: A Validated Lightweight Python Package for Planetary Positions and Solar-Lunar Event Calculations
Ioannis Nasios
This paper presents solarsystem, a validated lightweight and dependency-free Python package for planetary positions and solar-lunar event calculations. The package provides helioce…
The ecosystem of machine learning competitions: Platforms, participants, and their impact on AI development
Ioannis Nasios
Machine learning competitions (MLCs) play a pivotal role in advancing artificial intelligence (AI) by fostering innovation, skill development, and practical problem-solving. This s…
Multi-Modal Landslide Detection from Sentinel-1 SAR and Sentinel-2 Optical Imagery Using Multi-Encoder Vision Transformers and Ensemble Learning
Ioannis Nasios
Landslides represent a major geohazard with severe impacts on human life, infrastructure, and ecosystems, underscoring the need for accurate and timely detection approaches to supp…
AI-driven multi-source data fusion for algal bloom severity classification in small inland water bodies: Leveraging Sentinel-2, DEM, and NOAA climate data
Ioannis Nasios
Harmful algal blooms are a growing threat to inland water quality and public health worldwide, creating an urgent need for efficient, accurate, and cost-effective detection methods…
Enhancing kelp forest detection in remote sensing images using crowdsourced labels with Mixed Vision Transformers and ConvNeXt segmentation models
Ioannis Nasios
Kelp forests, as foundation species, are vital to marine ecosystems, providing essential food and habitat for numerous organisms. This study explores the integration of crowdsource…
Citizen participation: crowd-sensed sustainable indoor location services
Ioannis Nasios, Konstantinos Vogklis, Avleen Malhi +3
In the present era of sustainable innovation, the circular economy paradigm dictates the optimal use and exploitation of existing finite resources. At the same time, the transition…
Blending gradient boosted trees and neural networks for point and probabilistic forecasting of hierarchical time series
Ioannis Nasios, Konstantinos Vogklis
In this paper we tackle the problem of point and probabilistic forecasting by describing a blending methodology of machine learning models that belong to gradient boosted trees and…
Analyze Mass Spectrometry data with Artificial Intelligence to assist the understanding of past habitability of Mars and provide insights for future missions
Ioannis Nasios
This paper presents an application of artificial intelligence on mass spectrometry data for detecting habitability potential of ancient Mars. Although data was collected for planet…