Results 61 to 70 of about 417 (152)

Hyperspectral Image Classification Based on Multiscale Feature Search Graph Convolutional Network With Meta Pseudolabels

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
In recent years, graph convolutional networks (GCNs) have been introduced for hyperspectral image (HSI) classification due to their ability to effectively process the inherent graph structure of HSI data.
Suyi Li, Ke Wu, Huize Liu, Dandan Zhou, Ying Xu   +4 more
doaj   +1 more source

Hyperspectral imagery quality assessment and band reconstruction using the prophet model

CAAI Transactions on Intelligence Technology, Volume 10, Issue 1, Page 47-61, February 2025.
Abstract In Hyperspectral Imaging (HSI), the detrimental influence of noise and distortions on data quality is profound, which has severely affected the following‐on analytics and decision‐making such as land mapping. This study presents an innovative framework for assessing HSI band quality and reconstructing the low‐quality bands, based on the ...
Ping Ma, Jinchang Ren, Zhi Gao, Yinhe Li, Rongjun Chen   +4 more
wiley   +1 more source

Multiscale Superpixelwise Locality Preserving Projection for Hyperspectral Image Classification

Applied Sciences, 2019
Manifold learning is a powerful dimensionality reduction tool for a hyperspectral image (HSI) classification to relieve the curse of dimensionality and to reveal the intrinsic low-dimensional manifold.
Lin He, Xianjun Chen, Jun Li, Xiaofeng Xie   +3 more
doaj   +1 more source

Artificial intelligence methods used in various aquaculture applications: A systematic literature review

Journal of the World Aquaculture Society, Volume 56, Issue 1, February 2025.
Abstract This research article presents a systematic literature review on the current state‐of‐the‐art artificial intelligence (AI) methodologies used in aquaculture applications. As the demand for seafood continues to grow, the aquaculture industry faces numerous challenges, including disease management, feeding optimization, water quality monitoring,
Thurein Aung, Rafiza Abdul Razak, Adibi Rahiman Bin Md Nor   +2 more
wiley   +1 more source

Multiscale NMF based on intra-pixel and inter-pixel structure adjustment for spectral unmixing

International Journal of Applied Earth Observations and Geoinformation
Various improved nonnegative matrix factorization (NMF) methods have been widely used in spectral unmixing (SU), including nonlinear versions to counter for the lower spatial resolution and interaction between materials.
Tingting Yang, Meiping Song, Sen Li, Haimo Bao   +3 more
doaj   +1 more source

A Review of Deep Learning‐Based Medical Image Segmentation

IET Image Processing, Volume 19, Issue 1, January/December 2025.
Comprehensive overview of supervised medical image segmentation using deep learning. Summary of technological innovations and empirical results. Exploration of future research directions for deep learning‐based medical image segmentation. ABSTRACT Medical image segmentation, the process of precisely delineating regions of interest (e.g. organs, lesions,
Xinyue Zhang, Jianfeng Wang, Xiaochun Cheng, Junran Li   +3 more
wiley   +1 more source

Sparse Representation-Based Hyperspectral Image Classification Using Multiscale Superpixels and Guided Filter

IEEE Geoscience and Remote Sensing Letters, 2019
We propose a spatial–spectral hyperspectral image classification method based on multiscale superpixels and guided filter (MSS–GF). In order to use spatial information effectively, MSSs are used to get local information from different region scales. Sparse representation classifier is used to generate classification maps for each region scale.
Tugcan Dundar, Taner Ince
openaire   +2 more sources

USNet: underwater image superpixel segmentation via multi-scale water-net

Frontiers in Marine Science
Underwater images commonly suffer from a variety of quality degradations, such as color casts, low contrast, blurring details, and limited visibility.
Chuhong Wang, Chuhong Wang, Wenli Duan, Chengche Luan, Junyan Liang, Lengyu Shen, Hua Li   +6 more
doaj   +1 more source

From Global to Local: A Dual-Branch Structural Feature Extraction Method for Hyperspectral Image Classification

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Extracting discriminative spectral-spatial features from hyperspectral images (HSIs) remains a crucial topic within the remote sensing community. However, most feature extraction methods suffer from coarse textures, leading to poor performance in ...
Ying Zhang, Lianhui Liang, Jianxu Mao, Yaonan Wang, Lin Jia   +4 more
doaj   +1 more source

Spatial Multifeature and Dual-Layer Multihop Graph Convolution Networks for Hyperspectral Image Classification

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Hyperspectral image (HSI) classification constitutes a crucial research direction within the domain of remote sensing. Convolutional neural networks (CNNs) and graph convolutional network (GCN) have exhibited outstanding classification performance in ...
Xiangyue Yu, Ning Li, Di Wu, Zheng Li, Zhenyuan Wu, Ximing Ma   +5 more
doaj   +1 more source