Contrastive multi-view subspace clustering of hyperspectral images based on graph convolutional networks
High-dimensional and complex spectral structures make the clustering of hyperspectral
images (HSIs) a challenging task. Subspace clustering is an effective approach for …
images (HSIs) a challenging task. Subspace clustering is an effective approach for …
Spatial-spectral graph contrastive clustering with hard sample mining for hyperspectral images
Hyperspectral image (HSI) clustering is a fundamental yet challenging task that groups
image pixels with similar features into distinct clusters. Among various approaches …
image pixels with similar features into distinct clusters. Among various approaches …
Pixel-superpixel contrastive learning and pseudo-label correction for hyperspectral image clustering
Hyperspectral image (HSI) clustering is gaining considerable attention owing to recent
methods that overcome the inefficiency and misleading results from the absence of …
methods that overcome the inefficiency and misleading results from the absence of …
EMVCC: Enhanced multi-view contrastive clustering for hyperspectral images
Cross-view consensus representation plays a critical role in hyperspectral images (HSIs)
clustering. Recent multi-view contrastive cluster methods utilize contrastive loss to extract …
clustering. Recent multi-view contrastive cluster methods utilize contrastive loss to extract …
Shared and private information learning in multimodal sentiment analysis with deep modal alignment and self-supervised multi-task learning
Designing an effective representation learning method for multimodal sentiment analysis is
a critical research area. The primary challenge is capturing shared and private information …
a critical research area. The primary challenge is capturing shared and private information …
Lr-fpn: Enhancing remote sensing object detection with location refined feature pyramid network
H Li, R Zhang, Y Pan, J Ren, F Shen - arxiv preprint arxiv:2404.01614, 2024 - arxiv.org
Remote sensing target detection aims to identify and locate critical targets within remote
sensing images, finding extensive applications in agriculture and urban planning. Feature …
sensing images, finding extensive applications in agriculture and urban planning. Feature …
Effective hyperspectral image classification based on segmented PCA and 3D-2D CNN leveraging multibranch feature fusion
We present an innovative hyperspectral image (HSI) classification method addressing
challenges posed by closely spaced wavelength bands. Our approach combines 3D-2D …
challenges posed by closely spaced wavelength bands. Our approach combines 3D-2D …
[HTML][HTML] Rolling Bearing Fault Diagnosis in Agricultural Machinery Based on Multi-Source Locally Adaptive Graph Convolution
F **e, E Sun, L Wang, G Wang, Q **ao - Agriculture, 2024 - mdpi.com
Maintaining agricultural machinery is crucial for efficient mechanized farming. Specifically,
diagnosing faults in rolling bearings, which are essential rotating components, is of …
diagnosing faults in rolling bearings, which are essential rotating components, is of …
ResNet50 in remote sensing and agriculture: evaluating image captioning performance for high spectral data
Remote sensing image captioning is crucial as it enables the automatic interpretation and
description of complex images captured from satellite or aerial sensors, facilitating the …
description of complex images captured from satellite or aerial sensors, facilitating the …
UUVSim: Intelligent modular simulation platform for unmanned underwater vehicle learning
Z Zhang, J Xu, J Du, W Mi, Z Wang… - … Joint Conference on …, 2024 - ieeexplore.ieee.org
Unmanned underwater vehicles (UUVs) face challenges such as high hardware costs,
security concerns, a lack of training data in the actual development and debugging. Creating …
security concerns, a lack of training data in the actual development and debugging. Creating …