Deep learning approaches, particularly convolutional neural networks (CNNs) and other architectures, were used in 49 papers. These models excel at image-based tasks such as land cover classification, ...

This paper proposes a deep learning framework F-GCN that integrates multiple wavelet bases, and extracts MI brain electrical ...

A deep learning model was able to determine the presence or absence of distinct autoimmune neuroinflammatory disorders.

Scientists have created a novel probabilistic model for 5-minutes ahead PV power forecasting. The method combines a convolutional neural network with bidirectional long short-term memory, attention ...

The world of artificial intelligence (AI) is rapidly evolving, and AI is increasingly enabling applications that were previously unattainable or very difficult to implement. A subsequent article, ...

More recently, deep learning and evolutionary algorithms have enabled long-term ecological forecasting, carbon emission ...

A recent study suggests that cyberattacks on future, AI-guided spacecraft could be thwarted by unpicking what the AI has been "thinking." ...

In today's data-driven environment, Python has become the mainstream language in the fields of machine learning and data science due to its concise syntax, rich library support, and active community, ...

Deep learning models, particularly Convolutional Neural Networks (CNN), are the core technologies for current Chinese handwriting recognition. The workflow can be summarized in the following steps: ...

Large language models have captured the news cycle, but there are many other kinds of machine learning and deep learning with many different use cases. Amid all the hype and hysteria about ChatGPT, ...