[HTML][HTML] A review of uncertainty quantification in deep learning: Techniques, applications and challenges
Uncertainty quantification (UQ) methods play a pivotal role in reducing the impact of
uncertainties during both optimization and decision making processes. They have been …
uncertainties during both optimization and decision making processes. They have been …
A comprehensive survey on robust image watermarking
With the rapid development and popularity of the Internet, multimedia security has become a
general essential concern. Especially, as manipulation of digital images gets much easier …
general essential concern. Especially, as manipulation of digital images gets much easier …
Machine learning and deep learning in smart manufacturing: The smart grid paradigm
Industry 4.0 is the new industrial revolution. By connecting every machine and activity
through network sensors to the Internet, a huge amount of data is generated. Machine …
through network sensors to the Internet, a huge amount of data is generated. Machine …
[HTML][HTML] Maintenance optimization in industry 4.0
This work reviews maintenance optimization from different and complementary points of
view. Specifically, we systematically analyze the knowledge, information and data that can …
view. Specifically, we systematically analyze the knowledge, information and data that can …
Data science and big data analytics: A systematic review of methodologies used in the supply chain and logistics research
Data science and big data analytics (DS &BDA) methodologies and tools are used
extensively in supply chains and logistics (SC &L). However, the existing insights are …
extensively in supply chains and logistics (SC &L). However, the existing insights are …
Process systems engineering–the generation next?
Abstract Process Systems Engineering (PSE) is the scientific discipline of integrating scales
and components describing the behavior of a physicochemical system, via mathematical …
and components describing the behavior of a physicochemical system, via mathematical …
[HTML][HTML] Emerging information and communication technologies for smart energy systems and renewable transition
Since the energy sector is the dominant contributor to global greenhouse gas emissions, the
decarbonization of energy systems is crucial for climate change mitigation. Two major …
decarbonization of energy systems is crucial for climate change mitigation. Two major …
Diagnosis of brain diseases in fusion of neuroimaging modalities using deep learning: A review
A Shoeibi, M Khodatars, M Jafari, N Ghassemi… - Information …, 2023 - Elsevier
Brain diseases, including tumors and mental and neurological disorders, seriously threaten
the health and well-being of millions of people worldwide. Structural and functional …
the health and well-being of millions of people worldwide. Structural and functional …
Renewable energy-powered semi-closed greenhouse for sustainable crop production using model predictive control and machine learning for energy management
Renewable energy consumption in agriculture is ascending, catering to the food needs of
the rising population and protecting the environment. Maximizing renewable energy usage …
the rising population and protecting the environment. Maximizing renewable energy usage …
Look before you leap: An exploratory study of uncertainty measurement for large language models
The recent performance leap of Large Language Models (LLMs) opens up new
opportunities across numerous industrial applications and domains. However, erroneous …
opportunities across numerous industrial applications and domains. However, erroneous …