The annotations used during the training process are crucial for the inference results of
remote sensing images (RSIs) based on a deep learning framework. Unlabeled RSIs can be …

Abstract Knowledge-based Visual Question Answering (KB-VQA) requires VQA systems to
utilize knowledge from external knowledge bases to answer visually-grounded questions …

Certain fields present significant challenges when attempting to train complex Deep
Learning architectures, particularly when the available datasets are limited and imbalanced …

Creating a successful small molecule drug is a challenging multiparameter optimization
problem in an effectively infinite space of possible molecules. Generative models have …

In the clinical and healthcare domains, medical images play a critical role. A mature medical
visual question answering system (VQA) can improve diagnosis by answering clinical …

Transformers were initially introduced for natural language processing, leveraging the self-
attention mechanism. They require minimal inductive biases in their design and can function …

Image captioning is a technique that enables the automatic extraction of natural language
descriptions about the contents of an image. On the one hand, information in the form of …

Large language models (LLMs) have emerged as powerful machine-learning systems
capable of handling a myriad of tasks. Tuned versions of these systems have been turned …

This manuscript presents a new benchmark for assessing the quality of visual summaries
without the need for human annotators. It is based on the Signature Transform, specifically …

In recent years, there has been a growing interest in remote sensing image–text cross-
modal retrieval due to the rapid development of space information technology and the …