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목록논문 리뷰 (37)
Attention please
이번에 리뷰할 논문은 DeepLab: Semantic Image Segmentation with Deep Convolutional Nets, Atrous Convolution, and Fully Connected CRFs 입니다. https://paperswithcode.com/paper/deeplab-semantic-image-segmentation-with-deep Papers with Code - DeepLab: Semantic Image Segmentation with Deep Convolutional Nets, Atrous Convolution, and Fully Connected CR #3 best model for Semantic Segmentation on Event-based Segmen..
이번에 리뷰할 논문은 You Only Look Once: Unified, Real-Time Object Detection 입니다. https://paperswithcode.com/paper/you-only-look-once-unified-real-time-object Papers with Code - You Only Look Once: Unified, Real-Time Object Detection 🏆 SOTA for Real-Time Object Detection on PASCAL VOC 2007 (FPS metric) paperswithcode.com object detection은 image 내에 object의 위치를 예측함과 동시에 해당 object의 class를 분류해야하는 task입니다. 이미..
이번에 리뷰할 논문은 A Method for Detection of Small Moving Objects in UAV Videos 입니다. https://paperswithcode.com/paper/a-method-for-detection-of-small-moving Papers with Code - A Method for Detection of Small Moving Objects in UAV Videos 🏆 SOTA for Small Object Detection on Bee4Exp Honeybee Detection (Average F1 metric) paperswithcode.com Object detection의 경우 많은 발전들이 있었습니다. R-CNN, YOLO와 같은 CNN 기반 object..
이번에 리뷰할 논문은 Spatial Pyramid Pooling in Deep ConvolutionalNetworks for Visual Recognition 입니다. https://paperswithcode.com/method/spatial-pyramid-pooling Papers with Code - Spatial Pyramid Pooling Explained Spatial Pyramid Pooling (SPP) is a pooling layer that removes the fixed-size constraint of the network, i.e. a CNN does not require a fixed-size input image. Specifically, we add an SPP layer o..
이번에 리뷰할 논문은 UNet++: A Nested U-Net Architecture for Medical Image Segmentation 입니다. https://paperswithcode.com/paper/unet-a-nested-u-net-architecture-for-medical Papers with Code - UNet++: A Nested U-Net Architecture for Medical Image Segmentation 🏆 SOTA for Video Polyp Segmentation on SUN-SEG-Easy (Dice metric) paperswithcode.com 본 논문에서 제안하는 모델은 UNet++ 으로, 2015년에 제안되었던 UNet의 업그레이드 버전이라 생각하시면 됩니..
이번에 리뷰할 논문은 U-Net: Convolutional Networks for BiomedicalImage Segmentation 입니다. https://paperswithcode.com/paper/u-net-convolutional-networks-for-biomedical Papers with Code - U-Net: Convolutional Networks for Biomedical Image Segmentation 🏆 SOTA for Semantic Segmentation on Kvasir-Instrument (DSC metric) paperswithcode.com 2015년도에 나온 논문이며 Image segmentation 분야에서 아주 큰 영향을 준 논문이라고 해도 과원이 아닙니다. UN..