Large kernel convolutional networks date back to early deep learning models but were overshadowed by small kernel networks like VGG-Net and ResNet. Recently, models like ConvNeXt and RepLKNet have ...

The proposed algorithm can also process input feature maps and generate output feature maps with the same flexible block sizes that are independent of convolution weight kernel size. The memory access ...

Repository files navigation Image-Filtering-Python 2D Convolution for Image Filtering. This program convolves a kernel (or a filter) with a grayscale image. Kernel can be defined by updating kernel ...

Sparse convolution in python. Uses Toeplitz convolutional matrix multiplication to perform sparse convolution. This allows for extremely fast convolution when: The kernel is small (<= 100x100) The ...

The basement imaged by the stacked refraction convolution section is similar in geometry to that obtained by seismic reflection processing. The stacked refraction convolution section identifies the ...

To conclude that part, these 4 examples show that DiAGAN can generate 3D realizations that are close to the 3D references from 2D examples. There are some differences but one has to remember that the ...