Abstract: Convolution neural networks (CNNs) have been extensively used in machine learning applications. The most time-consuming part of CNNs are convolution operations. A common approach to ...

Abstract: Image convolution is an integral operator in the field of digital image processing. For any operation to be processed in images say whether it is edge detection, image smoothing, image ...

A high-performance hardware accelerator designed for image convolution operations in Convolutional Neural Networks (CNNs). This implementation provides an efficient FPGA-based solution for ...

2D Convolution: Wrote a custom implementation of image convolution in Assembly and compared its execution time to a Python implementation. The goal was to demonstrate how low-level memory control and ...

Using the combinatorics of non-crossing partitions, we construct a conditionally free analogue of Voiculescu's S-transform. The result is applied to the analytical description of conditionally free ...

The marriage of deep neural network (DNN) and secure 2-party computation (2PC) enables private inference (PI) on the encrypted client-side data and server-side models with both privacy and accuracy ...