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In our data driven world, categorization is of major importance to help end-users and decision makers understanding information structures. Supervised learning techniques rely on annotated samples that are often difficult to obtain and training often overfits. On the other hand, unsupervised clustering techniques study the structure of the data without disposing of any training data. Given the difficulty...
In our data driven world, clustering is of major importance to help end-users and decision makers understanding information structures. Supervised learning techniques rely on ground truth to perform the classification and are usually subject to overtraining issues. On the other hand, unsupervised clustering techniques study the structure of the data without disposing of any training data. Given the...
When considering multimedia database growth, one current challenging issue is to design accurate navigation tools. End user basic needs, such as exploration, similarity search and favorite suggestions, lead to investigate how to find semantically resembling media. One way is to build numerous continuous dissimilarity measures from low-level image features. In parallel, an other way is to build discrete...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.