[PDF][PDF] 高光谱遥感影像分类研究进展
杜培军， 夏俊士， 薛朝辉， 谭琨， 苏红军， 鲍蕊 - 遥感学报, 2021 - ygxb.ac.cn
随着模式识别, 机器学习, 遥感技术等相关学科领域的发展, 高光谱遥感影像分类研究取得快速
进展. 本文系统总结和评述了当前高光谱遥感影像分类的相关研究进展, 在总结分类策略的基础 …
进展. 本文系统总结和评述了当前高光谱遥感影像分类的相关研究进展, 在总结分类策略的基础 …
Remote sensing in field crop monitoring: A comprehensive review of sensor systems, data analyses and recent advances
The key elements that underpin food security require the adaptation of agricultural systems
to support productivity increases while minimizing inputs and the adverse effects of climate …
to support productivity increases while minimizing inputs and the adverse effects of climate …
Advances in spectral-spatial classification of hyperspectral images
Recent advances in spectral-spatial classification of hyperspectral images are presented in
this paper. Several techniques are investigated for combining both spatial and spectral …
this paper. Several techniques are investigated for combining both spatial and spectral …
Self-supervised learning with adaptive distillation for hyperspectral image classification
Hyperspectral image (HSI) classification is an important topic in the community of remote
sensing, which has a wide range of applications in geoscience. Recently, deep learning …
sensing, which has a wide range of applications in geoscience. Recently, deep learning …
Hyperspectral and LiDAR data fusion: Outcome of the 2013 GRSS data fusion contest
C Debes, A Merentitis, R Heremans… - IEEE Journal of …, 2014 - ieeexplore.ieee.org
The 2013 Data Fusion Contest organized by the Data Fusion Technical Committee (DFTC)
of the IEEE Geoscience and Remote Sensing Society aimed at investigating the synergistic …
of the IEEE Geoscience and Remote Sensing Society aimed at investigating the synergistic …
Spectral-spatial latent reconstruction for open-set hyperspectral image classification
Deep learning-based methods have produced significant gains for hyperspectral image
(HSI) classification in recent years, leading to high impact academic achievements and …
(HSI) classification in recent years, leading to high impact academic achievements and …
Object detection in remote sensing images based on improved bounding box regression and multi-level features fusion
The objective of detection in remote sensing images is to determine the location and
category of all targets in these images. The anchor based methods are the most prevalent …
category of all targets in these images. The anchor based methods are the most prevalent …
Spatial sequential recurrent neural network for hyperspectral image classification
In hyperspectral image processing, classification is one of the most popular research topics.
In recent years, research progress made in deep-learning-based hierarchical feature …
In recent years, research progress made in deep-learning-based hierarchical feature …
Processing of multiresolution thermal hyperspectral and digital color data: Outcome of the 2014 IEEE GRSS data fusion contest
This paper reports the outcomes of the 2014 Data Fusion Contest organized by the Image
Analysis and Data Fusion Technical Committee (IADF TC) of the IEEE Geoscience and …
Analysis and Data Fusion Technical Committee (IADF TC) of the IEEE Geoscience and …
Smooth giou loss for oriented object detection in remote sensing images
X Qian, N Zhang, W Wang - Remote Sensing, 2023 - mdpi.com
Oriented object detection (OOD) can more accurately locate objects with an arbitrary
direction in remote sensing images (RSIs) compared to horizontal object detection. The most …
direction in remote sensing images (RSIs) compared to horizontal object detection. The most …