Contrastive learning models based on Siamese structure have demonstrated remarkable
performance in self-supervised learning. Such a success of contrastive learning relies on …

Crop management plays a crucial role in determining crop yield economic profitability and
environmental sustainability. Despite the availability of management guidelines optimizing …

Self-supervised representation learning methods have achieved significant success in
computer vision and natural language processing (NLP), where data samples exhibit explicit …

Representation learning stands as one of the critical machine learning techniques across
various domains. Through the acquisition of high-quality features, pre-trained embeddings …

Classifying and segmenting patterns from a limited number of examples is a significant
challenge in remote sensing and earth observation due to the difficulty in acquiring …

Biodiversity is declining at an unprecedented rate, impacting ecosystem services necessary
to ensure food, water, and human health and well-being. Understanding the distribution of …

Given the rapid emergence and applications of Large Language Models (LLMs) across
various scientific fields, insights regarding their applicability in agriculture are still only …

In this study, we uncover the unexpected efficacy of residual-based large language models
(LLMs) as part of encoders for biomedical imaging tasks, a domain traditionally devoid of …

Large language models (LLMs) have reached human-like proficiency in generating diverse
textual content, underscoring the necessity for effective fake text detection to avoid potential …

Crop management, including nitrogen (N) fertilization and irrigation management, has a
significant impact on the crop yield, economic profit, and the environment. Although …