IEEE IGARSS’20 | Testing rotationally equivariant convolutional neural networks on overhead imagery data.
This work came out of a collaboration during my time as a Research Associate at Pacific Northwest National Laboratory. In the paper, we test a rotationally equivariant steerable filter convolutional neural network (SFCNN) on overhead imagery data. You can checkout the paper here.
Note: authors are sorted alphabetically.
Text and figures are licensed under Creative Commons Attribution CC BY-ND 4.0. The figures that have been reused from other sources don't fall under this license and can be recognized by a note in their caption: "Figure from ...".