Infrared and visible image fusion aims to integrate complementary multi-modal information into a single fused result. However, existing methods 1) fail to account for the degradation visible images under adverse weather conditions, thereby compromising fusion performance; and 2) rely on fixed network architectures, limiting their adaptability to diverse degradation scenarios. To address these issues, we propose a one-stop degradation-aware image fusion framework for multi-degradation scenarios driven by a large language model (MdaIF). Given the distinct scattering characteristics of different degradation scenarios (e.g., haze, rain, and snow) in atmospheric transmission, a mixture-of-experts (MoE) system is introduced to tackle image fusion across multiple degradation scenarios. To adaptively extract diverse weather-aware degradation knowledge and scene feature representations, collectively referred to as the semantic prior, we employ a pre-trained vision-language model (VLM) in our framework. Guided by the semantic prior, we propose degradation-aware channel attention module (DCAM), which employ degradation prototype decomposition to facilitate multi-modal feature interaction in channel domain. In addition, to achieve effective expert routing, the semantic prior and channel-domain modulated features are utilized to guide the MoE, enabling robust image fusion in complex degradation scenarios. Extensive experiments validate the effectiveness of our MdaIF, demonstrating superior performance over SOTA methods.

For the past few years, the 5G + Internet of Things (IoT) technology and big data mining and analysis applications have gradually entered various areas of people's lives.. The rapid expansion of 5G + IoT and automation technology is the basis for the formation and construction of the smart dairy cattle pasture production. Big data and artificial intelligence have greatly improved the management level and economic benefits of dairy farms. The practical application of Blockchain + 5G IoT and big data in the production of dairy products can ensure the quality and safety of milk, and is expected to bring greater social and ecological benefits. The smart dairy farm is proposed to effectively improve the production and economic benefits of the pasture. This article aims to propose an intelligent way of identifying individual cattle and precise feeding of dairy cows based on 5G IoT technology. Within the frame of smart pasture management, the cow image identification makes feasible the timely identification of abnormal individuals in order to take suitable treatment for a different situation. The application of 5G image processing technology could save labor and promote efficient management. The combination of this technology and intelligence can effectively improve the economic benefits and production efficiency of the cattle farm through image recognition technology.