Abstract: A single instruction multiple data (SIMD) processor is used to implement a dropout layer between a first layer and a second layer of a neural network. The SIMD processor can implement the dropout layer by setting one or more elements in an output tensor of the first layer to zero before providing it as an input tensor to the second layer. Setting of the one or more elements to zero is based on a dropout rate, and pseudo-random numbers generated by a random number generator in the SIMD processor.

Abstract: A dynamic rule strategy and fraud detection method for detecting fraud trends is provided. The method includes storing captured transaction data in at least one data warehouse and utilizing a computer server including at least one processor for performing multiple steps. The steps include continuously monitoring the captured transaction data for detecting a concentration of fraud attacks in selected segments; receiving, the selected segments identified and developing a set of fraud detection rules based on the selected segments; and validating and implementing the fraud detection rules.

Abstract: Matte-based video restoration technique embodiments are presented which model spatio-temporally varying film wear artifacts found in digitized copies of film media. In general, this is accomplished by employing residual color information in recovering of artifact mattes. To this end, the distributions of artifact colors and their fractional contribution to each pixel of each frame being considered are extracted based on color information from the spatial and temporal neighborhoods of the pixel. The extracted information can then be used to restore the video by removing the artifacts.

Abstract: Aspects of the present invention are related to systems and methods for selecting backlight array driving values.

Abstract: Matte-based video restoration technique embodiments are presented which model spatio-temporally varying film wear artifacts found in digitized copies of film media. In general, this is accomplished by employing residual color information in recovering of artifact mattes. To this end, the distributions of artifact colors and their fractional contribution to each pixel of each frame being considered are extracted based on color information from the spatial and temporal neighborhoods of the pixel. The extracted information can then be used to restore the video by removing the artifacts.