D. Michail

发表

Strongly Stable Matchings in Time O ( nm )

Kurt Mehlhorn, Telikepalli Kavitha, Dimitrios Michail, 2003 .

Challenges for Qualitative Spatial Reasoning in Linked Geospatial Data

Stavros Vassos, Charalambos Kontoes, Ioannis Papoutsis, 2011 .

Hephaestus: A large scale multitask dataset towards InSAR understanding

I. Papoutsis, D. Michail, P. Elias, 2022, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW).

Lobster- A Load Balanced P2P Content Sharing Network

Euripides G. M. Petrakis, Peter Triantafillou, Manolis Koubarakis, 2002 .

Dependable Integration Concepts for Human-Centric AI-Based Systems

Davide Bacciu, Eric Armengaud, Georg Macher, 2021, SAFECOMP Workshops.

Learning from Synthetic InSAR with Vision Transformers: The case of volcanic unrest detection

I. Papoutsis, D. Michail, N. Bountos, 2022, IEEE Transactions on Geoscience and Remote Sensing.

Efficient deep learning models for land cover image classification

I. Papoutsis, Christos Tryfonopoulos, D. Michail, 2021, ArXiv.

Benchmarking and scaling of deep learning models for land cover image classification

I. Papoutsis, Christos Tryfonopoulos, D. Michail, 2021, ISPRS Journal of Photogrammetry and Remote Sensing.

Deep Learning for Global Wildfire Forecasting

I. Papoutsis, N. Carvalhais, D. Michail, 2022, ArXiv.

Fungal contamination of beef carcasses and the environment in a slaughterhouse

D. Michail, A. Nassar, M. Ismail, 1995 .

A Faster Algorithm for Minimum Cycle Basis of Graphs

Kurt Mehlhorn, Telikepalli Kavitha, Dimitrios Michail, 2004, ICALP.

A Survey on the Use of Graph Convolutional Networks for Combating Fake News

Iraklis Varlamis, D. Michail, Foteini Glykou, 2022, Future Internet.

Cycle bases in graphs characterization, algorithms, complexity, and applications

Kurt Mehlhorn, Telikepalli Kavitha, Romeo Rizzi, 2009, Comput. Sci. Rev..

Deep Learning for Global Wildfire Forecasting

I. Papoutsis, N. Carvalhais, D. Michail, 2022, ArXiv.

Rank-maximal matchings

Kurt Mehlhorn, Telikepalli Kavitha, Robert W. Irving, 2004, TALG.

A driving profile recommender system for autonomous driving using sensor data and reinforcement learning

Iraklis Varlamis, Christos Sardianos, Christos Chronis, 2021, PCI.

Detection of fake news campaigns using graph convolutional networks

Iraklis Varlamis, D. Michail, Nikos Kanakaris, 2022, Int. J. Inf. Manag. Data Insights.

Learning class prototypes from Synthetic InSAR with Vision Transformers pdf

Ioannis Papoutsis, Dimitrios Michail, Nikolaos Ioannis Bountos, 2022, ArXiv.

JGraphT—A Java Library for Graph Data Structures and Algorithms

Dimitrios Michail, Joris Kinable, Barak Naveh, 2019, ACM Trans. Math. Softw..

Benchmark Comparison of Methods for Approximate Neighborhood Estimation of Road Segments in Large-Scale Traffic Networks

C. K. Filelis-Papadopoulos, G. Gravvanis, D. Michail, 2020, PCI.

An experimental comparison of single-sided preference matching algorithms

Dimitrios Michail, D. Michail, 2011, JEAL.

Bounded Unpopularity Matchings

Telikepalli Kavitha, Meghana Nasre, Chien-Chung Huang, 2008, Algorithmica.

Reducing rank-maximal to maximum weight matching

Dimitrios Michail, D. Michail, 2007, Theor. Comput. Sci..

A methodology for near real-time change detection between Unmanned Aerial Vehicle and wide area satellite images

Charalambos Kontoes, Konstantinos Koutroumbas, Dimitrios Michail, 2016 .

TEACHING - Trustworthy autonomous cyber-physical applications through human-centred intelligence

Davide Bacciu, Claudio Gallicchio, Alessio Micheli, 2021, 2021 IEEE International Conference on Omni-Layer Intelligent Systems (COINS).

Rank-maximal through maximum weight matchings

D. Michail, 2005 .

Cycle bases of graphs and sampled manifolds

Kurt Mehlhorn, Craig Gotsman, Evangelia Pyrga, 2007, Comput. Aided Geom. Des..

Minimum Cycle Basis, Algorithms & Applications

Kurt Mehlhorn, Markus Bläser, Dimitrios Michail, 2006 .

Fair Matchings and Related Problems

Kurt Mehlhorn, Telikepalli Kavitha, Chien-Chung Huang, 2016, Algorithmica.

Self-Supervised Contrastive Learning for Volcanic Unrest Detection

Nantheera Anantrasirichai, Ioannis Papoutsis, Dimitrios Michail, 2021, IEEE Geoscience and Remote Sensing Letters.

JHeaps: An open-source library of priority queues

D. Michail, 2021, SoftwareX.

Bounded Unpopularity Matchings

T. Kavitha, Chien-Chung Huang, D. Michail, 2008, Scandinavian Workshop on Algorithm Theory.

Wildfire monitoring using satellite images, ontologies and linked geospatial data

Charalambos Kontoes, Ioannis Papoutsis, Konstantina Bereta, 2014, J. Web Semant..

Computationally Efficient Rehearsal for Online Continual Learning

Iraklis Varlamis, K. Tserpes, D. Michail, 2022, ICIAP.

Graph matching on social networks without any side information

Iraklis Varlamis, Dimitrios Michail, Charalampos Davalas, 2019, 2019 IEEE International Conference on Big Data (Big Data).

TeleViT: Teleconnection-driven Transformers Improve Subseasonal to Seasonal Wildfire Forecasting

I. Papoutsis, D. Michail, N. Bountos, 2023, 2023 IEEE/CVF International Conference on Computer Vision Workshops (ICCVW).

An $\tilde{O}(m^{2}n)$ Algorithm for Minimum Cycle Basis of Graphs

Kurt Mehlhorn, Telikepalli Kavitha, Dimitrios Michail, 2008, Algorithmica.

New Approximation Algorithms for Minimum Cycle Bases of Graphs

Kurt Mehlhorn, Telikepalli Kavitha, Dimitrios Michail, 2007, Algorithmica.