Subjects: Computer Science >> Integration Theory of Computer Science submitted time 2019-01-03 Cooperative journals: 《计算机应用研究》
Abstract： In order to understand the development of single image super-resolution reconstruction (SISR) based on deep learning and grasp the hotspots and directions of the current research, this paper combs the existing model of single image super-resolution reconstruction based on deep learning. Firstly, the paper introduces the related deep learning algorithm, these models based on deep learning and their evaluation index. In addition, it compares the performance of existing models through experiments, which aims to understand the advantages of single-image super-resolution reconstruction model based on deep learning. Finally, the paper summarizes the key issues of single-image super-resolution reconstruction, and prospects the future development trends.
Subjects: Computer Science >> Integration Theory of Computer Science submitted time 2019-01-03 Cooperative journals: 《计算机应用研究》
Abstract： In order to understand the latest research progress of the classical clustering algorithm K-means in Spark environment, and grasp the current research hotspots and directions of K-means algorithm, this paper reviews the initial center point optimization research on K-means algorithm. Firstly, it introduces the memory computing framework Spark and K-means algorithms, and analyzes the cause and effects of clustering instability of K-means algorithm, which aimed to point out the importance of optimizing K-means algorithm. And it introduces the main methods and the latest research status of optimizing the initial center point of K-means in Spark environment in detail, and also discusses the future research trends in initial center point optimization of K-means.
Hits
Hits
Downloads
Comment