운동하는 공대생

논문 - https://arxiv.org/abs/1706.05587v3 Rethinking Atrous Convolution for Semantic Image Segmentation In this work, we revisit atrous convolution, a powerful tool to explicitly adjust filter's field-of-view as well as control the resolution of feature responses computed by Deep Convolutional Neural Networks, in the application of semantic image segmentatio arxiv.org 1. Intro 기존의 컨볼루션 기반의 모델들은 지역..

https://arxiv.org/abs/1406.4729v4 Spatial Pyramid Pooling in Deep Convolutional Networks for Visual Recognition Existing deep convolutional neural networks (CNNs) require a fixed-size (e.g., 224x224) input image. This requirement is "artificial" and may reduce the recognition accuracy for the images or sub-images of an arbitrary size/scale. In this work, we equip th arxiv.org 1 Intro 논문에서 제시한 문제..