Rechargeable batteries of the future—the state of the art from a BATTERY 2030+ perspective
The development of new batteries has historically been achieved through discovery and
development cycles based on the intuition of the researcher, followed by experimental trial …
development cycles based on the intuition of the researcher, followed by experimental trial …
Deep learning in mechanical metamaterials: from prediction and generation to inverse design
Mechanical metamaterials are meticulously designed structures with exceptional
mechanical properties determined by their microstructures and constituent materials …
mechanical properties determined by their microstructures and constituent materials …
Is ChatGPT leading generative AI? What is beyond expectations?
Generative AI has the potential to change the way we do things. The chatbot is one of the
most popular implementation areas. Even though companies like Google and Meta had …
most popular implementation areas. Even though companies like Google and Meta had …
Data augmentation in classification and segmentation: A survey and new strategies
In the past decade, deep neural networks, particularly convolutional neural networks, have
revolutionised computer vision. However, all deep learning models may require a large …
revolutionised computer vision. However, all deep learning models may require a large …
[PDF][PDF] Advances in machine learning-driven pore pressure prediction in complex geological settings
Ogbu, Iwe, Ozowe, & Ikevuje, P. 1648-1665 Page 1649 significant promise in capturing the
intricate relationships between geological variables and pore pressure. These models can …
intricate relationships between geological variables and pore pressure. These models can …
Emotion recognition in EEG signals using deep learning methods: A review
Emotions are a critical aspect of daily life and serve a crucial role in human decision-making,
planning, reasoning, and other mental states. As a result, they are considered a significant …
planning, reasoning, and other mental states. As a result, they are considered a significant …
Specialized deep neural networks for battery health prognostics: Opportunities and challenges
Lithium-ion batteries are key drivers of the renewable energy revolution, bolstered by
progress in battery design, modelling, and management. Yet, achieving high-performance …
progress in battery design, modelling, and management. Yet, achieving high-performance …
Applications of deep learning techniques for automated multiple sclerosis detection using magnetic resonance imaging: A review
Multiple Sclerosis (MS) is a type of brain disease which causes visual, sensory, and motor
problems for people with a detrimental effect on the functioning of the nervous system. In …
problems for people with a detrimental effect on the functioning of the nervous system. In …
Recent progresses in machine learning assisted Raman spectroscopy
With the development of Raman spectroscopy and the expansion of its application domains,
conventional methods for spectral data analysis have manifested many limitations. Exploring …
conventional methods for spectral data analysis have manifested many limitations. Exploring …
[책][B] Machine learning
E Alpaydin - 2021 - books.google.com
MIT presents a concise primer on machine learning—computer programs that learn from
data and the basis of applications like voice recognition and driverless cars. No in-depth …
data and the basis of applications like voice recognition and driverless cars. No in-depth …