Biblio
With the rapid development of artificial intelligence, video target tracking is widely used in the fields of intelligent video surveillance, intelligent transportation, intelligent human-computer interaction and intelligent medical diagnosis. Deep learning has achieved remarkable results in the field of computer vision. The development of deep learning not only breaks through many problems that are difficult to be solved by traditional algorithms, improves the computer's cognitive level of images and videos, but also promotes the progress of related technologies in the field of computer vision. This paper combines the deep learning algorithm and target tracking algorithm to carry out relevant experiments on basketball motion detection video, hoping that the experimental results can be helpful to basketball motion detection video target tracking.
Quality assurance and food safety are the most problem that the consumers are special care. To solve this problem, the enterprises must improve their food supply chain management system. In addition to tracking and storing orders and deliveries, it also ensures transparency and traceability of food production and transportation. This is a big challenge that the food supply chain system using the client-server model cannot meet with the requirements. Blockchain was first introduced to provide distributed records of digital currency exchanges without reliance on centralized management agencies or financial institutions. Blockchain is a disruptive technology that can improve supply chain related transactions, enable to access data permanently, data security, and provide a distributed database. In this paper, we propose a method to design a food supply chain management system base on Blockchain technology that is capable of bringing consumers’ trust in food traceability as well as providing a favorable supply and transaction environment. Specifically, we design a system architecture that is capable of controlling and tracking the entire food supply chain, including production, processing, transportation, storage, distribution, and retail. We propose the KDTrace system model and the Channel of KDTrace network model. The Smart contract between the organizations participating in the transaction is implemented in the Channel of KDTrace network model. Therefore, our supply chain system can decrease the problem of data explosion, prevent data tampering and disclosure of sensitive information. We have built a prototype based on Hyperledger Fabric Blockchain. Through the prototype, we demonstrated the effectiveness of our method and the suitability of the use cases in a supply chain. Our method that uses Blockchain technology can improve efficiency and security of the food supply chain management system compared with traditional systems, which use a clientserver model.
In an agricultural supply chain, farmers, food processors, transportation agencies, importers, and exporters must comply with different regulations imposed by one or more jurisdictions depending on the nature of their business operations. Supply chain stakeholders conventionally transport their goods, along with the corresponding documentation via regulators for compliance checks. This is generally followed by a tedious and manual process to ensure the goods meet regulatory requirements. However, supply chain systems are changing through digitization. In digitized supply chains, data is shared with the relevant stakeholders through digital supply chain platforms, including blockchain technology. In such datadriven digital supply chains, the regulators may be able to leverage digital technologies, such as artificial intelligence and machine learning, to automate the compliance verification process. However, a barrier to progress is the risk that information will not be credible, thus reversing the gains that automation could achieve. Automating compliance based on inaccurate data may compromise the safety and credibility of the agricultural supply chain, which discourages regulators and other stakeholders from adopting and relying on automation. Within this article we consider the challenges of digital supply chains when we describe parts of the compliance management process and how it can be automated to improve the operational efficiency of agricultural supply chains. We introduce assisted autonomy as a means to pragmatically automate the compliance verification process by combining the power of digital systems while keeping the human in-the-loop. We argue that autonomous compliance is possible, but that the need for human led inspection processes will never be replaced by machines, however it can be minimised through “assisted autonomy”.