Compartmental modeling is a widely used tool in neurophysiology but the detail and scope of such models is frequently limited by lack of computational resources. Here we implement compartmental modeling on low cost Graphical Processing Units (GPUs), which significantly increases simulation speed compared to NEURON. Testing two methods for solving the current diffusion equation system revealed w...

CBIR is the method of searching the digital images from an image database. “Content-based” means that the search analyzes the contents of the image rather than the metadata such as colours, shapes, textures, or any other information that can be derived from the image itself. The GPU is a powerful graphics engine and a highly parallel programmable processor having better efficiency and high spee...

In this manuscript, we present an implementation of a correlation method for face recognition application on GPU. Our correlator is based on the famous ”4f” setup and the use of a Phase Only Filter (POF). Traditionally, the correlation approach is implemented using optical components for real-time application. Unfortunately, optical implementation is complex and has exorbitant price. To cope wi...

Graphical processing units used for mathematical and scientific computing are known as general purpose graphical processing units (GPGPUs). This paper is an introduction to the most popular GPGPU technology, NVIDIA's Compute Unified Device Architecture (CUDA). We approach CUDA from the perspective of a software developer, discussing the structure and organization of programs to explain the func...

This paper presents Phase Only Correlation (POC) methods in hierarchical search motion estimation for high resolution digital video using Graphical Processing Unit (GPU). Using the POC function, one can estimate the translational displacement as well as the degree of similarity between two image blocks from the location and height of the correlation peak, respectively[1]. Motion Estimation is a...

<p>A multitude of research has been rising for predicting the behavior different real-world problems through machine learning models. An erratic nature occurs due to augmented and inadequacy prerequisite dataset prediction water level over fundamental models that show flat or low-set accuracy. In this paper, a powerful scaling strategy is proposed improvised back-propagation algorithm usi...

Apreviously proposednonlinear inverse reconstruction for autocalibrated parallel imaging simultaneously estimates coil sensitivities and image content. This work exploits this property for real-time MRI, where coil sensitivities need to be dynamically adapted to the conditions generated by moving objects. The development comprises (i) an extension of the nonlinear inverse algorithm to non-Carte...

A previously proposed nonlinear inverse reconstruction for autocalibrated parallel imaging simultaneously estimates coil sensitivities and image content. This work exploits this property for real-time MRI, where coil sensitivities need to be dynamically adapted to the conditions generated by moving objects. The development comprises (i) an extension of the nonlinear inverse algorithm to non-Car...