Deep semi-supervised learning is a fast-growing field with a range of practical applications.
This paper provides a comprehensive survey on both fundamentals and recent advances in …

The building sector accounts for 36% of the total global energy usage and 40% of
associated Carbon Dioxide emissions. Therefore, the forecasting of building energy …

Deep learning has achieved remarkable results in many computer vision tasks. Deep neural
networks typically rely on large amounts of training data to avoid overfitting. However …

Recent developments in natural language processing have led to the creation of large
language models, such as ChatGPT, which could generate human-like text. In this paper, we …

The metaverse aims to build an immersive virtual reality world to support the daily life, work,
and recreation of people. In this survey, the status quo of the metaverse is investigated, and …

In the past few years, it has become increasingly evident that deep neural networks are not
resilient enough to withstand adversarial perturbations in input data, leaving them …

Large language models (LLMs) are a special class of pretrained language models (PLMs)
obtained by scaling model size, pretraining corpus and computation. LLMs, because of their …

With the acceleration of urban expansion, urban change detection (UCD), as a significant
and effective approach, can provide the change information with respect to geospatial …

Wood is a renewable resource with excellent qualities and the potential to become a key
element of a future bioeconomy. The increasing environmental awareness and drive to …

Multi-document summarization (MDS) is an effective tool for information aggregation that
generates an informative and concise summary from a cluster of topic-related documents …