Data Cleansing to Enhance Quality of Multimedia Data Using Convultional Neural Networks

Determining the clean-up procedures and the new ways of data cleansing for quality improvement is crucial if you want to identify data cleansing errors early and successfully address them. Data cleansing is a well-researched method for removing inaccurate labels from databases. Because of its exceptional performance, data purification technology is a fairly widespread computer technology utilized extensively in many fields. The major goal of the study was to create a framework for data purification that would improve multimedia images' quality. In order to eliminate duplicates, a Convolutional Neural Network (CNN) was used to categorize the objects in photos. The study's findings show how a Convolutional Neural Network framework may handle data purification in multimedia sources.