Πλοήγηση ανά Θέμα "Machine learning approaches"
Αποτελέσματα 1-10 από 10
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Assessing Durum Wheat Yield through Sentinel-2 Imagery: A Machine Learning Approach
(2022)Two modeling approaches for the estimation of durum wheat yield based on Sentinel-2 data are presented for 66 fields across three growing periods. In the first approach, a previously developed multiple linear regression ... -
Conventional and machine learning approaches as countermeasures against hardware trojan attacks
(2020)Every year, the rate at which technology is applied on areas of our everyday life is increasing at a steady pace. This rapid development drives the technology companies to design and fabricate their integrated circuits ... -
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 ... -
Improving Multiclass Classification of Cybersecurity Breaches in Railway Infrastructure using Imbalanced Learning
(2021)Machine learning approaches and algorithms are spreading in wide areas in research and technology. Cybersecurity breaches are the common anomalies for networked and distributed infrastructures which are monitored, registered, ... -
A learning approach for strategic consumers in smart electricity markets
(2016)In this paper we consider the design and the implementation of a machine learning approach and its integration with a widely used energy simulation platform. We focus on auction based energy markets which require their ... -
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 approaches for predicting health risk of cyanobacterial blooms in Northern European Lakes
(2020)Cyanobacterial blooms are considered a major threat to global water security with documented impacts on lake ecosystems and public health. Given that cyanobacteria possess highly adaptive traits that favor them to prevail ... -
Physical activity as a risk factor in the progression of osteoarthritis: a machine learning perspective
(2020)Knee osteoarthritis (KOA) comes with a variety of symptoms’ intensity, frequency and pattern. Most of the current methods in KOA diagnosis are very expensive commonly measuring changes in joint morphology and function. So, ...