Design And Implementation Of Labeling System Based On Image Segmentation Algorithm

The most critical technology that comes with the rise of AI is deep learning.As the basis of deep learning,neural networks are an input-oriented algorithm,and the accuracy of the results depends on the data close to the "infinite" magnitude.Therefore,in addition to those complex intermediate links,the most critical aspect of deep learning is the need for a large amount of data training,which is why AI can rise in the era of Internet big data.Before the data training,a large amount of data must be marked first as a pilot experience of machine learning.Therefore,the generation of the data annotation system has been spawned.This paper introduces the design and implementation of an annotation system for image data.Firstly,it introduces the research and analysis of the current status of similar products,discusses the advantages and disadvantages of the data labeling company,and emphasizes the particularity and confidentiality of the companyls departmental needs.Then,through the nirther demand analysis,the system is divided into functional modules and their sub-modules,the business logic and process are clarified,and the overall architecture of the system is built.Based on the overall architecture of the system,the implementation of the functions of each module of the system is designed in detail,including data annotation,data review,etc.,and also involves the process analysis of human body gestures,object annotations,icon annotations,etc.The explanation of the image segnentation algonthm.This system is a Web system based on SpringMVC framework.The database uses relational database MySQL,image or short video raw data is stored in Blobstore storage service,data loading and annotation information is drawn by means of JavaScript script function and Canvas canvas element.In addition,a multi-level audit mechanism has been added to ensure the quality and effectiveness of the annotated data through multiple audits.The audit module is also used to review machine-labeled data for the purpose of accounting for its identification efficiency and accuracy.At present,there are more and more types of marking systems.If you want to be able to serve the research of enterprises according to local conditions,you must design and develop an marking system suitable for the specific needs of the company and the department.Under the premise of ensuring data security and high quality,we will improve the company's AI technology level.