76 citations · 137 across the 11 of their papers we have counts for
13 papers
MedShapeNet -- A Large-Scale Dataset of 3D Medical Shapes for Computer Vision
Jianning Li, Zongwei Zhou, Jiancheng Yang +154
Prior to the deep learning era, shape was commonly used to describe the objects. Nowadays, state-of-the-art (SOTA) algorithms in medical imaging are predominantly diverging from co…
An evaluation of time series forecasting models on water consumption data: A case study of Greece
Ioannis Kontopoulos, Antonios Makris, Konstantinos Tserpes +1
In recent years, the increased urbanization and industrialization has led to a rising water demand and resources, thus increasing the gap between demand and supply. Proper water di…
Partially Oblivious Neural Network Inference
Panagiotis Rizomiliotis, Christos Diou, Aikaterini Triakosia +2
Oblivious inference is the task of outsourcing a ML model, like neural-networks, without disclosing critical and sensitive information, like the model's parameters. One of the most…
TraClets: Harnessing the power of computer vision for trajectory classification
Ioannis Kontopoulos, Antonios Makris, Konstantinos Tserpes +1
Due to the advent of new mobile devices and tracking sensors in recent years, huge amounts of data are being produced every day. Therefore, novel methodologies need to emerge that…
AI-as-a-Service Toolkit for Human-Centered Intelligence in Autonomous Driving
Valerio De Caro, Saira Bano, Achilles Machumilane +11
This paper presents a proof-of-concept implementation of the AI-as-a-Service toolkit developed within the H2020 TEACHING project and designed to implement an autonomous driving per…
TEACHING -- Trustworthy autonomous cyber-physical applications through human-centred intelligence
Davide Bacciu, Siranush Akarmazyan, Eric Armengaud +32
This paper discusses the perspective of the H2020 TEACHING project on the next generation of autonomous applications running in a distributed and highly heterogeneous environment c…
Context agnostic trajectory prediction based on -architecture
Evangelos Psomakelis, Konstantinos Tserpes, Dimitris Zissisc +2
Predicting the next position of movable objects has been a problem for at least the last three decades, referred to as trajectory prediction. In our days, the vast amounts of data…
BUDAMAF: Data Management in Cloud Federations
Evangelos Psomakelis, Konstantinos Tserpes, Dimosthenis Anagnostopoulos +1
Data management has always been a multi-domain problem even in the simplest cases. It involves, quality of service, security, resource management, cost management, incident identif…
Employing traditional machine learning algorithms for big data streams analysis: the case of object trajectory prediction
Angelos Valsamis, Konstantinos Tserpes, Dimitrios Zissis +2
In this paper, we model the trajectory of sea vessels and provide a service that predicts in near-real time the position of any given vessel in 4', 10', 20' and 40' time intervals.…
Big IoT and social networking data for smart cities: Algorithmic improvements on Big Data Analysis in the context of RADICAL city applications
Evangelos Psomakelis, Fotis Aisopos, Antonios Litke +3
In this paper we present a SOA (Service Oriented Architecture)-based platform, enabling the retrieval and analysis of big datasets stemming from social networking (SN) sites and In…
CONSENSUS Project: Identifying publicly acceptable policy implementations
Konstantinos Tserpes
Even though it is unrealistic to expect citizens to pinpoint the policy implementation that they prefer from the set of alternatives, it is still possible to infer such information…
SocIoS API: A data aggregator for accessing user generated content from online social networks
Magdalini Kardara, Vasilis Kalogirou, Athanasios Papaoikonomou +2
Following the boost in popularity of online social networks, both enterprises and researchers looked for ways to access the social dynamics information and user generated content r…
Comparing methods for Twitter Sentiment Analysis
Evangelos Psomakelis, Konstantinos Tserpes, Dimosthenis Anagnostopoulos +1
This work extends the set of works which deal with the popular problem of sentiment analysis in Twitter. It investigates the most popular document ("tweet") representation methods…