Turnitin
降AI改写
早检测系统
早降重系统
Turnitin-UK版
万方检测-期刊版
维普编辑部版
Grammarly检测
Paperpass检测
checkpass检测
PaperYY检测
Crop type classification by DESIS hyperspectral imagery and machine learning algorithms
Developments in space-based hyperspectral sensors, advanced remote sensing, and
machine learning can help crop yield measurement, modelling, prediction, and crop …
machine learning can help crop yield measurement, modelling, prediction, and crop …
MATNet: A combining multi-attention and transformer network for hyperspectral image classification
Hyperspectral image (HSI) has rich spatial–spectral information, high spectral correlation,
and large redundancy between information. Due to the sparse background distribution of …
and large redundancy between information. Due to the sparse background distribution of …
Multiscale dual-branch residual spectral–spatial network with attention for hyperspectral image classification
The development of remote sensing images in recent years has made it possible to identify
materials in inaccessible environments and study natural materials on a large scale. But …
materials in inaccessible environments and study natural materials on a large scale. But …
AMSSE-Net: Adaptive multiscale spatial–spectral enhancement network for classification of hyperspectral and LiDAR data
With the abundant emergence of remote sensing (RS) data sources, multimodal remote
sensing observation has become an active field. Extracting valuable information from …
sensing observation has become an active field. Extracting valuable information from …
A cross-modal feature aggregation and enhancement network for hyperspectral and LiDAR joint classification
Advancements in Earth observation technologies have greatly enhanced the potential of
integrating hyperspectral (HS) images with Light Detection and Ranging (LiDAR) data for …
integrating hyperspectral (HS) images with Light Detection and Ranging (LiDAR) data for …
Combining novel feature selection strategy and hyperspectral vegetation indices to predict crop yield
S Fei, L Li, Z Han, Z Chen, Y **ao - Plant Methods, 2022 - Springer
Background Wheat is an important food crop globally, and timely prediction of wheat yield in
breeding efforts can improve selection efficiency. Traditional yield prediction method based …
breeding efforts can improve selection efficiency. Traditional yield prediction method based …
Depthwise separable convolutional autoencoders for hyperspectral image change detection
Hyperspectral image change detection (HSI-CD) has recently become a research hotspot.
Current methods rely heavily on a huge amount of training samples to perform the change …
Current methods rely heavily on a huge amount of training samples to perform the change …
A dual-branch siamese spatial-spectral transformer attention network for Hyperspectral Image Change Detection
The convolutional neural networks have recently gained widespread attention in
Hyperspectral Image Change Detection (HSI-CD) due to their outstanding feature extraction …
Hyperspectral Image Change Detection (HSI-CD) due to their outstanding feature extraction …
Interactive enhanced network based on multihead self-attention and graph convolution for classification of hyperspectral and lidar data
The fusion of multimodal data plays a crucial role in classification tasks. However, existing
research typically mines and analyzes the individual features of each data source separately …
research typically mines and analyzes the individual features of each data source separately …
MS3Net: Multiscale stratified-split symmetric network with quadra-view attention for hyperspectral image classification
M Liu, H Pan, H Ge, L Wang - Signal Processing, 2023 - Elsevier
Recently, hyperspectral image (HSI) classification has become a promising research
direction in remote sensing image processing. Many HSI classification methods have been …
direction in remote sensing image processing. Many HSI classification methods have been …