Πλοήγηση ανά Θέμα "Machine learning techniques"
Αποτελέσματα 1-14 από 14
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Assessment of Machine Learning Techniques for Building an Efficient IDS
(2020)Intrusion Detection Systems (IDS) are the systems that detect and block any potential threats (e.g. DDoS attacks) in the network. In this project, we explore the performance of several machine learning techniques when used ... -
ETH analysis and predictions utilizing deep learning
(2020)This paper attempts to provide a data analysis of cryptocurrency markets. Such markets have been developed rapidly and their volatility poses significant research challenges and justifies intensive behavior analysis. For ... -
Exploring deep learning capabilities in knee osteoarthritis case study for classification
(2019)This research study is devoted to the investigation of deep neural networks (DNN) for classification of the complex problem of knee osteoarthritis diagnosis. Osteoarthritis (OA) is the most common chronic condition of the ... -
Gesture recognition technologies for gestural know-how management: Preservation and transmission of expert gestures in wheel throwing pottery
(2015)The acquisition of gestural know-how in manual professions constitutes a real challenge since it passes from master to learner, through a many years long « in person » transmission. However this binding transmission is not ... -
Long Short-Term Memory (LSTM) Deep Neural Networks in Energy Appliances Prediction
(2019)The application of Long Short-Term Memory (LSTM) Deep Neural Networks has been increased the last years. This paper proposes a novel methodology based on a hybrid model using the Long Short-Term Memory (LSTM) Networks and ... -
Machine learning applied on the district heating and cooling sector: a review
(2022)Driven by the continuous growing demand for heating and cooling, district heating and cooling systems (DHC) play a major role in the field of energy by providing environmentally friendly solutions for citizens with significant ... -
A Machine Learning Approach for NILM based on Odd Harmonic Current Vectors
(2019)This paper examines the application of machine learning techniques in NILM methodologies based on the first three odd harmonic order current vectors as the only attributes of the appliances. Proper formulation of the ... -
A Machine Learning approach to the EFT re-interpretation of the WZjj fully leptonic electroweak production
(2021)In this paper we study the use of Machine Learning techniques to set constraints on indirect signatures of physics beyond the Standard Model in Vector Boson Scattering (VBS), in the electroweak (EWK) production of ... -
Machine learning symbolic equations for diffusion with physics-based descriptions
(2022)This work incorporates symbolic regression to propose simple and accurate expressions that fit to material datasets. The incorporation of symbolic regression in physical sciences opens the way to replace "black-box"machine ... -
Machine learning technique in time series prediction of gross domestic product
(2017)Artificial intelligence is gaining ground the last years in many scientific sectors with the development of new machine learning techniques. In this research, a machine learning methodology is proposed in the Gross Domestic ... -
On the Employment of Machine Learning Techniques for Troubleshooting WiFi Networks
(2019)The rapidly increasing popularity of 802.11 WLANs along with the co-existence of multiple heterogeneous devices in the unlicensed frequency bands have created unprecedented levels of congestion, especially in densely ... -
Real-time arm gesture recognition using 3D skeleton joint data
(2019)In this paper we present an approach towards real-time hand gesture recognition using the Kinect sensor, investigating several machine learning techniques. We propose a novel approach for feature extraction, using measurements ... -
Using machine learning to predict mortality and morbidity after Traumatic Brain Injury
(2022)A very interesting and important application of machine learning relates to healthcare. There are several studies that illustrate that machines can assist clinicians to make treatment decisions and forecast disease outcomes. ... -
Which machine learning paradigm for fake news detection?
(2019)Fake news detection/classification is gradually becoming of paramount importance to out society in order to avoid the so-called reality vertigo, and protect in particular the less educated persons. Various machine learning ...