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Cross corpus multi-lingual speech emotion recognition using ensemble learning
(
Springer
, 2021 , Article)
Receiving an accurate emotional response from robots has been a challenging task for researchers for the past few years. With the advancements in technology, robots like service robots interact with users of different ...
Data fusion strategies for energy efficiency in buildings: Overview, challenges and novel orientations
(
Elsevier
, 2020 , Article)
Recently, tremendous interest has been devoted to develop data fusion strategies for energy efficiency in buildings, where various kinds of information can be processed. However, applying the appropriate data fusion strategy ...
Shear capacity prediction of FRP-RC beams using single and ensenble ExPlainable Machine learning models
(
Elsevier
, 2022 , Article)
Corrosion in steel reinforcement is a central issue behind the severe deterioration of existing reinforced concrete (RC) structures. Nowadays, fiber-reinforced polymer (FRP) is increasingly being used as a viable alternative ...
Forecasting the impact of environmental stresses on the frequent waves of COVID19
(
Springer
, 2021 , Article)
A novel approach to link the environmental stresses with the COVID-19 cases is adopted during this research. The time-dependent data are extracted from the online repositories that are freely available for knowledge and ...
Power transformer health condition evaluation: A deep generative model aided intelligent framework
(
Elsevier Ltd
, 2023 , Article)
This paper presents a deep generative model-aided intelligent framework for effective health condition evaluation of power grid transformers. The health assessment of a power transformer is required to guarantee the stable ...
Machine learning for cybersecurity in smart grids: A comprehensive review-based study on methods, solutions, and prospects
(
Elsevier B.V.
, 2022 , Article Review)
In modern Smart Grids (SGs) ruled by advanced computing and networking technologies, condition monitoring relies on secure cyberphysical connectivity. Due to this connection, a portion of transported data, containing ...
Machine learning in the Internet of Things: Designed techniques for smart cities
(
Elsevier B.V.
, 2019 , Article)
Machine learning is one of the emerging technologies that has grabbed the attention of academicians and industrialists, and is expected to evolve in the near future. Machine learning techniques are anticipated to provide ...
A machine learning framework for enhancing digital experiences in cultural heritage
(
Emerald Group Publishing Ltd.
, 2020 , Article)
Purpose: Digital tools have been used to document cultural heritage with high-quality imaging and metadata. However, some of the historical assets are totally or partially unlabeled and some are physically damaged, which ...
Machine Learning and Digital Heritage: The CEPROQHA Project Perspective
(
Springer
, 2020 , Conference Paper)
Through this paper, we aim at investigating the impact of artificial intelligence technologies on cultural heritage promotion and long-term preservation in terms of digitization effectiveness, attractiveness of the assets, ...
An integrated framework for the interaction and 3D visualization of cultural heritage
(
Springer
, 2023 , Article)
In this study, the aim is to design and develop a 3D acquisition, visualization, and interaction framework to preserve cultural heritage and provide new ways to enable museum visitors and cultural audiences to virtually ...