🧠 Project Overview We designed and implemented a two-dimensional convolution processor that performs kernel-based filtering on input image data. The processor supports different kernel sizes and can ...

Image Convolution with Padding This C++ program demonstrates a basic 2D convolution operation between an image and a kernel with zero-padding. The implementation shows how to perform edge detection ...

To address this issue, we present dynamic convolution, a new design that increases model complexity without increasing the network depth or width. Instead of using a single convolution kernel per ...

The 2D convolution unit is configurable to support 2D convolution operations with different sizes of input image matrix and kernel filter. The architecture can reduce memory access time and power as ...

A high performance digital architecture for computing 2D convolution utilizing the quadrant symmetry of the kernels is proposed in this paper. Pixels in the four quadrants of the kernel region with ...

Since CNN Explainer outputs 10 feature maps from 3 inputs corresponding to red, blue, and green, it is explained that there are 3×10=30 kernels. The size of the kernel and the number of pixels to ...