cch8ii 님의 블로그

논문 링크: https://arxiv.org/abs/1905.11946 EfficientNet: Rethinking Model Scaling for Convolutional Neural NetworksConvolutional Neural Networks (ConvNets) are commonly developed at a fixed resource budget, and then scaled up for better accuracy if more resources are available. In this paper, we systematically study model scaling and identify that carefully balancing narxiv.org한 줄 정리 CNN(합성곱 신경망) 모..

논문 링크: https://arxiv.org/abs/1708.02002 Focal Loss for Dense Object DetectionThe highest accuracy object detectors to date are based on a two-stage approach popularized by R-CNN, where a classifier is applied to a sparse set of candidate object locations. In contrast, one-stage detectors that are applied over a regular, dense samplarxiv.org한 줄 정리 Focal Loss 적용Object detection에서 클래스 불균형 문제 해결 Fea..

논문 링크: [1406.4729] Spatial Pyramid Pooling in Deep Convolutional Networks for Visual Recognition Spatial Pyramid Pooling in Deep Convolutional Networks for Visual RecognitionExisting 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/..

논문 링크: [1512.00567] Rethinking the Inception Architecture for Computer Vision Rethinking the Inception Architecture for Computer VisionConvolutional networks are at the core of most state-of-the-art computer vision solutions for a wide variety of tasks. Since 2014 very deep convolutional networks started to become mainstream, yielding substantial gains in various benchmarks. Although incrarxiv.o..