摘要:In recent years, few-shot object detection (FSOD) in remote sensing images (RSIs) has garnered significant attention from the research community. This technique aims to empower object detectors to identify novel object categories using a minimal number of labeled samples within RSIs. The importance of this research is underscored by the vast amounts of unlabeled remote sensing data available, making the efficient utilization of limited labeled data crucial. The core challenge in FSOD for RSIs lies in the requirement for base class samples during the learning process of novel class knowledge. In practical scenarios, object categories are constantly evolving and adapting to changing environments. This dynamic nature poses a significant obstacle for traditional FSOD methods, as they rely heavily on base class samples to learn novel class. However, such a dependency limits the ability of these methods to adapt tonovel class indefinitely. Furthermore, as the number of learned categories accumulates, the memory usage, storage requirements, and computational demands increase significantly. This scalability issue can become a major bottleneck, especially when dealing with large-scale remote sensing datasets. To address these challenges, we propose a class-incremental few-shot object detection method based on distillation response in remote sensing images (DR-CFSOD). This innovative approach differs significantly from existing methods by enabling the learning of novel class independently, without relying on base class. This crucial aspect alleviates the need for continuously incorporating base class samples, thereby overcoming the limitations of traditional FSOD methods. Moreover, DR-CFSOD addresses the catastrophic forgetting problem that often occurs in incremental learning scenarios. By distilling the knowledge learned from previous classes, the algorithm preserves the discriminative ability of the model, ensuring that it can accurately detect both base and novel class. To validate the effectiveness of our proposed method, we conducted extensive experiments on two diverse remote sensing image datasets. The results obtained demonstrate the superior performance of DR-CFSOD compared to baseline methods. Our method not only achieves competitive detection accuracy but also exhibits superior scalability and adaptability to new categories. Concurrently, our proposed method boasts an impressive 95FPS real-time detection performance, ensuring swift and accurate identification. This outstanding feature provides a solid foundation for seamless integration and effective application in practical scenarios, further enhancing its utility and value.
摘要:By constructing an intelligent algorithm-driven metrology business service platform, this paper reviews the research and implementation of providing customers with more accurate, secure, reliable, trustworthy, and convenient data services. Establishing this platform strengthens the integration of metrology work with modern digital technology and network technology, significantly enhancing data mining capabilities and achieving data integration, sharing, and application. Additionally, the application of this platform has positively impacted the intelligent management level, work efficiency, and work quality of metrology technical institutions.
摘要:This paper discusses the innovative application of broadcasting meta-universe and generative artificial intelligence technology. The radio and television meta-universe refers to the virtual space constructed by the radio and television media, which contains all kinds of media resources and user interaction functions. Generative AI technology is a technology based on machine learning that can generate content similar to human creation. In this study, we first introduce the concept and characteristics of the radio and television meta-universe, including the digitization of radio and television media resources and the application of virtual reality technology. Then, we explore the potential of generative AI technology for innovative applications in the broadcast meta-universe. With generative AI technology, broadcast media can automatically generate various forms of content, such as articles, images, audio and video. In addition, generative AI techniques can be used for personalized recommendation and sentiment analysis to enhance user experience. Finally, this paper also discusses the challenges and future directions of broadcast meta-universe and generative AI technologies, including the issues of data privacy protection and algorithmic interpretability. The research on the innovative application of broadcasting meta-universe and generative AI technology can promote the development of the broadcasting media industry and provide a more personalized and rich media experience.
摘要:This paper introduces the origin of the concept of virtual digital man, the definition and development history of virtual digital man, and then summarizes and analyzes the key technology and standardization of virtual digital man in detail. Finally, combined with the current situation of China's virtual digital man policy and application, it puts forward suggestions on the construction and improvement of virtual digital man policy and standards and the enhancement of technological innovation ability of virtual digital man.
关键词:Virtual Digital human;artificial intelligence;key technology;Standardization;High-quality development
摘要:This paper mainly discusses the development of smart communities and the role of TV screens in the construction of smart communities, analyzes the development status and technological evolution of smart communities in China through case analysis, from the use of all-in-one cards as an integrated carrier to the triple play system and then to the combination of traditional digital TV set-top boxes with the Internet and information services. Then the paper takes Topway TV smart community as an example to analyze the information engineering transformation and technical advantages and community service mode of TV large screens, also summarizes the advantages and difficulties of TV large screens in the construction of smart communities. The further development direction of large TV screens in the smart community market is proposed, aiming to optimize the community governance structure and improving the quality of people's livelihood services.
摘要:Virtual reality (VR) technology can create a virtual, realistic operating environment that is ideal for IV infusion process training and puncture training. However, virtual reality technology is not widely used in nurses' infusion teaching and training, and the use effect is uneven. The main problem is that the virtual reality infusion training system lacks the involvement of professional nurses. Through an in-depth understanding of the clinical needs of the intravenous infusion training system and the integration of the operational experience of professional nurses, an intravenous infusion training system based on virtual reality technology was designed. The system is divided into five parts: system management, training and examination, scoring model, infusion steps and data recording. The operator wears the HTC VIVE to achieve 3D scene rendering. The system uses leap motion to capture user movements, Unity for programming, Steam VR for 3D content display, and physically based rendering (PBR) for model visual rendering design. The system has been put into practical use in nurse training, so that the trained nurses are familiar with the intravenous infusion process and puncture techniques, and overcome the influence of psychological stress.