Hany Ouf

Pooling is performed in neural networks to reduce variance and computation complexity. Many times, beginners blindly use a pooling method without knowing the reason for using it. Here is a comparison of three basic pooling methods that are widely used. The three types of pooling operations are: Max pooling: The maximum pixel value of the batch is selected. Min pooling: The minimum pixel value of the batch is selected. Average pooling: The average value of all the pixels in the batch is selected. The batch here means a group of pixels of size equal to the filter size which is decided based on the size of the image. In the following example, a filter of 9x9 is chosen. The output of the pooling method varies with the varying value of the filter size. The operations are illustrated through the following figures. Average, Max and Min pooling of size 9x9 applied on an image We cannot say that a particular pooling method is better over others generally. The choice of pooling operation is made

  TempDB usage can be considered as a performance bottleneck for workloads that use SQL temp tables and table variables intensively resulted in heavy IO usage. A valuable alternatives for the SQL temp table and table variable are SCHEMA_ONLY Memory-Optimized tables and the Memory-optimized Table Variable, where the data will be completely stored in the memory without the need to touch the TempDB database, providing the best data access performance. SCHEMA_ONLY Memory-Optimized table and the Memory-optimized Table Variable are stored only in the memory with no related component in the disk. It involves no IO activity or TempDB utilization. It can also participate in the transactions without the need to log the transactions. In this article, we will prove practically that the SCHEMA_ONLY Memory-Optimized Table and the Memory- Optimized Variable Tables are the best replacements for the SQL temp tables and variable tables with better CPU, IO and execution time performance. SQL Server In-Me