arXiv:1911.08169
Dense Fusion Classmate Network for Land Cover Classification
원문 초록
Recently, FCNs based methods have made great progress in semantic segmentation. Different with ordinary scenes, satellite image owns specific characteristics, which elements always extend to large scope and no regular or clear boundaries. Therefore, effective mid-level structure information extremely missing, precise pixel-level classification becomes tough issues. In this paper, a Dense Fusion Classmate Network (DFCNet) is proposed to adopt in land cover classification.
함께 살펴볼 논문
공통 태그를 근거로 연결했습니다. 실제 인용 관계나 논문의 우수성을 뜻하지 않습니다.
MACD R-CNN: An Abnormal Cell Nucleus Detection Method
Generalized Scene Classification from Small-Scale Datasets with Multi-Task Learning
Generative Adversarial Minority Oversampling for Spectral-Spatial Hyperspectral Image Classification
Attention-Based Adaptive Spectral-Spatial Kernel ResNet for Hyperspectral Image Classification
Image and Text fusion for UPMC Food-101 \\using BERT and CNNs
Kidney Level Lupus Nephritis Classification using Uncertainty Guided Bayesian Convolutional Neural Networks
토론
이 논문과 연결된 포럼 글이 아직 없습니다.