In natural images, information is conveyed at different frequencies where higher frequencies are usually encoded with fine details and lower frequencies are usually encoded with global structures.

Fiber optics are a reliable medium for sensing and transmission, but processing these optical data requires switching to the electrical domain, which introduces large latency and thermal footprints.

It has long been recognized that the standard convolution is not rotation equivariant and thus not appropriate for downside fisheye images which are rotationally symmetric. This paper introduces ...

Understand the process of convolution and its applications in blurring and sharpening images using two-dimensional filters.

Convolution is used in a variety of signal-processing applications, including time-domain-waveform filtering. In a recent series on the inverse fast Fourier transform (FFT), we concluded with a ...

Therefore, for event-based cameras, sparse convolution based on hash tables is difficult to fully realize its potential in terms of computational delay. In addition to the hash table-based sparse ...

A MATLAB-based project implementing an 18-layer Convolutional Neural Network for object detection, using the CIFAR-10 dataset. It focuses on image classification into ten categories, with custom ...

Generally, shifted convolution sums are of number theoretic interest due to their connection to moments of and subconvexity bounds for L -functions (2 – 4). However, identities such as [1] would be ...