Many important real-world datasets come in the form of graphs or networks: e.g., social networks. Graph Convolutional Neural Network (GCN) is a generalization of convolution neural network over the graph, where filter parameters are typically shared over all locations in the graph.
I have computed whether it is feasible to using Uber/Lyft instead of leasing/owning a car in the future.
This is my reading note on 网络压缩最新进展：2019年最新文章概览, which covers recent advances in more efficient network architecturem, including quantization, pruning and network architecture search. Those works are published in CVPR 2019, ICLR 2019 and ICML 2019.
This is the step required for installing PyTorch on Nvidia Jetson Nano.
Pyramid is a widely used technique in vision tasks. It applied when you want to obtain features from different scales. There are generally two types of pyramids available:
- image pyramid: where image pyramid is generated first and then feature extract is applied on each level of pyramid. Image pyramid is a very effective way but has high computational cost.
- feature pyramid: feature is extract on the original image and next level of feature is built on the feature of previous level. Feature pyramid may reduce the computational cost by reusing the feature from lower level.