This study introduces a lightweight visual segmentation model named TinySegformer,
specifically designed for agricultural pest detection, aiming to address edge computing issues in …

Protecting crop yields is the most important aspect of agricultural production, and one of the
important measures in preserving yields is the control of crop pests and diseases; therefore, …

The detection of plant disease is of vital importance in practical agricultural production. It
scrutinizes the plant's growth and health condition and guarantees the regular operation and …

Simple Summary Achieving automatic detection of plant diseases in real agricultural scenarios
where low-computing-power platforms are deployed is a significant research topic. As fine…

Different from the current cloud storage solutions, which are mostly centralized storage
providers, this paper proposes a decentralized storage system based on blockchain technology, …

Polygonum chinense Linn. (Polygonum chinense L.) is one of the main raw materials of
Chinese patent medicines such as Guangdong herbal tea. The increasing antibiotic resistance …

With the rapid development of artificial intelligence and deep learning technologies, their
applications in the field of agriculture, particularly in plant disease detection, have become …

This research introduces a novel high-accuracy time-series forecasting method, namely the
Time Neural Network (TNN), which is based on a kernel filter and time attention mechanism. …

This research primarily explores the application of Natural Language Processing (NLP)
technology in precision financial fraud detection, with a particular focus on the implementation …

In this study, an innovative approach based on multimodal data and the transformer model
was proposed to address challenges in agricultural disease detection and question-…