☆ 4.6 Article

MS3Net: Multiscale stratified-split symmetric network with quadra-view attention for hyperspectral image classification

SIGNAL PROCESSING (2023)

Related references

Note: Only part of the references are listed.
Article Computer Science, Artificial Intelligence

Hyper-sausage coverage function neuron model and learning algorithm for image classification

Xin Ning et al.

Summary: In this study, a flexible and plastic hyper-sausage coverage function (HSCF) neuron model is proposed based on the mechanism of human cognition. A novel cross-entropy and volume-coverage (CE_VC) loss function is defined to enhance class separability and intra-class compactness. The introduced divisive iteration method adaptively determines the optimal number of HSCF neurons and a end-to-end learning framework is constructed. Experimental results demonstrate the effectiveness of the proposed method and its potential for boosting deep neural networks with neuron plasticity.

PATTERN RECOGNITION (2023)

Add to Collection
Article Environmental Sciences

Two-Branch Convolutional Neural Network with Polarized Full Attention for Hyperspectral Image Classification

Haimiao Ge et al.

Summary: In this study, a two-branch convolutional neural network with a polarized full attention mechanism is proposed for hyperspectral image classification. The network efficiently extracts spectral and spatial features through two branches and simplifies the kernel sizes of convolutional layers to reduce complexity. The one-shot connection technique improves feature extraction efficiency, and the polarized full attention mechanism fuses feature maps and provides global contextual information. Experimental results validate the effectiveness of the proposed network.

REMOTE SENSING (2023)

Add to Collection
Article Engineering, Electrical & Electronic

Progress and Challenges in Intelligent Remote Sensing Satellite Systems

Bing Zhang et al.

Summary: Due to advances in remote sensing satellite imaging and image processing technologies, intelligent remote sensing satellites have the potential to provide personalized, real-time, and accurate remote sensing information services. However, there are technological breakthroughs and legal challenges in the design of intelligent remote sensing satellites.

IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING (2022)

Add to Collection
Article Engineering, Electrical & Electronic

Multiscale Densely Connected Attention Network for Hyperspectral Image Classification

Xin Wang et al.

Summary: The proposed multiscale densely connected attention network (MSDAN) aims to enhance the classification performance and feature reuse for hyperspectral image classification, solving the issue of classification accuracy degradation caused by fixed-scale convolution kernels.

IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING (2022)

Add to Collection
Article Remote Sensing

A novel spectral-spatial multi-scale network for hyperspectral image classification with the Res2Net block

Zhongqiang Zhang et al.

Summary: A novel end-to-end spectral-spatial multi-scale network (SSMSN) is proposed for hyperspectral image (HSI) classification. The SSMSN utilizes multi-scale spectral module and multi-scale spatial module to extract multi-scale spectral and spatial features separately, achieving higher classification accuracy on limited training samples.

INTERNATIONAL JOURNAL OF REMOTE SENSING (2022)

Add to Collection
Article Geography, Physical

HyperLoopNet: Hyperspectral image classification using multiscale self-looping convolutional networks

Shivam Pande et al.

Summary: This article introduces a more efficient method for hyperspectral image classification, which utilizes self-looping convolutional neural networks for better feature extraction. Compared to traditional CNNs, this method has higher information flow efficiency and is able to extract abstract representations at multiple spatial levels.

ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING (2022)

Add to Collection
Article Geography, Physical

Hybrid retrieval of crop traits from multi-temporal PRISMA hyperspectral imagery

Giulia Tagliabue et al.

Summary: The recently launched and upcoming hyperspectral satellite missions have opened new opportunities for vegetation trait retrieval. In this study, a hybrid retrieval workflow was developed and tested using hyperspectral data from the PRISMA satellite. Crop traits were accurately mapped using this approach, demonstrating the potential of spaceborne imaging spectroscopy for crop monitoring.

ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING (2022)

Add to Collection
Article Environmental Sciences

One-Shot Dense Network with Polarized Attention for Hyperspectral Image Classification

Haizhu Pan et al.

Summary: This article proposes a novel one-shot dense network with polarized attention (OSDN) for hyperspectral image (HSI) classification. OSDN has two independent branches to extract spectral and spatial features and uses specially designed filtering methods to maintain high internal resolution in both the channel and spatial dimensions. Extensive experiments on benchmark HSI datasets demonstrate that OSDN can significantly reduce computational cost and parameters while maintaining high accuracy with a few training samples.

REMOTE SENSING (2022)

Add to Collection
Article Environmental Sciences

Hyperspectral Image Classification Based on Non-Parallel Support Vector Machine

Guangxin Liu et al.

Summary: This article proposes a non-parallel SVM model, which improves the classification effect and generalization performance for hyperspectral images by adding an additional empirical risk minimization term and bias constraint.

REMOTE SENSING (2022)

Add to Collection
Article Computer Science, Artificial Intelligence

Polarized self-attention: Towards high-quality pixel-wise mapping

Huajun Liu et al.

Summary: This study addresses the pixel-wise mapping problem in fine-grained computer vision tasks and proposes a Polarized Self-Attention (PSA) block for high-quality pixel-wise mapping. The PSA block effectively handles long-range dependencies and nonlinear outputs with low computation overheads. Experimental results show that PSA significantly improves the performance of standard baselines and state-of-the-art techniques.

NEUROCOMPUTING (2022)

Add to Collection
Article Computer Science, Artificial Intelligence

Commonality Autoencoder: Learning Common Features for Change Detection From Heterogeneous Images

Yue Wu et al.

Summary: An unsupervised change detection method is proposed using a convolutional autoencoder and a commonality autoencoder to extract common features in heterogeneous images, distinguishing changed and unchanged regions. Experimental results demonstrate the promising performance of this method compared to existing approaches.

IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS (2022)

Add to Collection
Article Engineering, Electrical & Electronic

Fine-Grained Classification of Urban Functional Zones and Landscape Pattern Analysis Using Hyperspectral Satellite Imagery: A Case Study of Wuhan

Jingwen Yuan et al.

Summary: This article evaluates and analyzes the classification of fine-grained urban functional zones in Wuhan, China, using hyperspectral satellite imagery. The results show that hyperspectral images allow for more accurate UFZ classification, with deep learning algorithms, particularly the SSUN-CRF algorithm, achieving high accuracy. The study demonstrates the significant potential of hyperspectral remote sensing imagery in mapping fine-grained UFZ, benefiting further urban study and planning.

IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING (2022)

Add to Collection
Article Computer Science, Artificial Intelligence

Res2Net: A New Multi-Scale Backbone Architecture

Shang-Hua Gao et al.

Summary: This paper introduces a novel building block for CNNs, Res2Net, which represents multiscale features within one single residual block by constructing hierarchical residual-like connections. The Res2Net enhances the representation of multiscale features in various vision tasks and consistently outperforms baseline models in performance gains.

IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE (2021)

Add to Collection
Article Geochemistry & Geophysics

Joint Spatial-Spectral Attention Network for Hyperspectral Image Classification

Lei Li et al.

Summary: The letter proposes a data-driven joint spatial-spectral attention network (JSSAN) to extract more representative features from hyperspectral images by designing spatial-spectral attention blocks and inserting them into a CNN structure. The method outperforms several state-of-the-art algorithms in experimental results.

IEEE GEOSCIENCE AND REMOTE SENSING LETTERS (2021)

Add to Collection
Article Geochemistry & Geophysics

Flexible Gabor-Based Superpixel-Level Unsupervised LDA for Hyperspectral Image Classification

Sen Jia et al.

Summary: This study proposes a framework, FG-SuULDA, for extracting informative and discriminating features from hyperspectral images for material classification. By designing flexible Gabor filters and introducing the SuULDA method, the classification capability and peculiarity of features are enhanced. Experimental results demonstrate the superiority of the proposed method in both classification performance and computational efficiency.

IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING (2021)

Add to Collection
Article Environmental Sciences

A Novel 2D-3D CNN with Spectral-Spatial Multi-Scale Feature Fusion for Hyperspectral Image Classification

Dongxu Liu et al.

Summary: This study presents a novel 2D-3D CNN with spectral-spatial multi-scale feature fusion for hyperspectral image classification, leveraging two feature extraction streams and a classification scheme to achieve higher accuracy. Experimental results demonstrate its superiority over existing methods.

REMOTE SENSING (2021)

Add to Collection
Article Geochemistry & Geophysics

Multiscale Residual Network With Mixed Depthwise Convolution for Hyperspectral Image Classification

Hongmin Gao et al.

Summary: This study introduces a novel multiscale residual network (MSRN) for hyperspectral image classification, which utilizes depthwise separable convolution and mixed depthwise convolution to achieve multiscale feature extraction and reduce network parameters. Experimental results on three benchmark hyperspectral images demonstrate the superiority of this method.

IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING (2021)

Add to Collection
Article Geochemistry & Geophysics

An Enhanced 3-D Discrete Wavelet Transform for Hyperspectral Image Classification

Xiangyong Cao et al.

Summary: The study proposes an enhanced 3DDWT approach to address noise contamination in hyperspectral image classification, utilizing a combination of CNN model and active learning strategy to achieve better categorized results compared to other advanced methods.

IEEE GEOSCIENCE AND REMOTE SENSING LETTERS (2021)

Add to Collection
Article Geochemistry & Geophysics

Graph Convolutional Networks for Hyperspectral Image Classification

Danfeng Hong et al.

Summary: This article thoroughly investigates the applications of Convolutional Neural Networks (CNNs) and Graph Convolutional Networks (GCNs) in hyperspectral image classification. By developing a new minibatch GCN (miniGCN) to train and infer large-scale GCNs, as well as exploring fusion strategies for different types of HS features, the study achieves good classification performance.

IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING (2021)

Add to Collection
Article Environmental Sciences

Self-training algorithm for hyperspectral imagery classification based on mixed measurement k-nearest neighbor and support vector machine

Haimiao Ge et al.

Summary: A self-training algorithm based on a mixed measurement k-NN and SVM framework is proposed to address the issue of noise and outliers in hyperspectral imagery classification. The mixed measurement combines spectral distance, spatial distance, and local outlier factor to explore feature differences. This method effectively reduces computational complexity and outperforms competitors in experimental results.

JOURNAL OF APPLIED REMOTE SENSING (2021)

Add to Collection
Article Computer Science, Artificial Intelligence

A survey: Deep learning for hyperspectral image classification with few labeled samples

Sen Jia et al.

Summary: With the advancement of deep learning technology, there is a growing focus on building deep learning models for HSI classification with few labeled samples, utilizing methods such as transfer learning, active learning, and few-shot learning. The results of the research indicate that the fusion of deep learning methods and related techniques can effectively address the issues of small-sample sets in HSI classification.

NEUROCOMPUTING (2021)

Add to Collection
Article Engineering, Electrical & Electronic

A Multiscale Dual-Branch Feature Fusion and Attention Network for Hyperspectral Images Classification

Hongmin Gao et al.

Summary: A novel multiscale dual-branch feature fusion and attention network was proposed to address feature extraction singleness and rough feature fusion process in existing methods, achieving improved classification performance by extracting spatial-spectral features at a granular level and utilizing a dual-branch feature fusion interactive module. Additionally, the introduction of a shuffle attention mechanism further enhanced the adaptive weighting of spatial and spectral features, leading to improved classification performance over state-of-the-art methods on benchmark datasets.

IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING (2021)

Add to Collection
Article Engineering, Electrical & Electronic

A Survey on Superpixel Segmentation as a Preprocessing Step in Hyperspectral Image Analysis

Subhashree Subudhi et al.

Summary: Recent advancements in hyperspectral sensors allow for higher resolution hyperspectral images, but also present challenges. Superpixels offer a potential solution to these challenges by simplifying processing steps. Superpixels have been successfully applied in various areas of hyperspectral image processing, including classification, spectral unmixing, dimensionality reduction, band selection, active learning, denoising, and anomaly detection.

IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING (2021)

Add to Collection
Article Engineering, Electrical & Electronic

HResNetAM: Hierarchical Residual Network With Attention Mechanism for Hyperspectral Image Classification

Zhixiang Xue et al.

Summary: This study introduces a novel hierarchical residual network combined with attention mechanism for hyperspectral image classification to extract multiscale spatial and spectral features, showing competitive advantages in classification performance compared to other state-of-the-art deep learning models.

IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING (2021)

Add to Collection
Article Engineering, Electrical & Electronic

Hyperspectral Image Classification With Mixed Link Networks

Zhe Meng et al.

Summary: In this article, two novel mixed link networks (MLNets) are proposed to enhance the representational ability of CNNs for HSI classification. Experimental results demonstrate that our MLNets achieve competitive results on three hyperspectral benchmark datasets compared with other state-of-the-art HSI classification approaches.

IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING (2021)

Add to Collection
Article Remote Sensing

Dual-branch dense residual network for hyperspectral imagery classification

Yuhao Wang et al.

INTERNATIONAL JOURNAL OF REMOTE SENSING (2020)

Add to Collection
Article Geochemistry & Geophysics

HybridSN: Exploring 3-D-2-D CNN Feature Hierarchy for Hyperspectral Image Classification

Swalpa Kumar Roy et al.

IEEE GEOSCIENCE AND REMOTE SENSING LETTERS (2020)

Add to Collection
Article Geochemistry & Geophysics

Learning to Pay Attention on Spectral Domain: A Spectral Attention Module-Based Convolutional Network for Hyperspectral Image Classification

Lichao Mou et al.

IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING (2020)

Add to Collection
Article Environmental Sciences

Classification of Hyperspectral Image Based on Double-Branch Dual-Attention Mechanism Network

Rui Li et al.

REMOTE SENSING (2020)

Add to Collection
Article Computer Science, Artificial Intelligence

Squeeze-and-Excitation Networks

Jie Hu et al.

IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE (2020)

Add to Collection
Article Environmental Sciences

Three-dimensional convolutional neural network model for tree species classification using airborne hyperspectral images

Bin Zhang et al.

REMOTE SENSING OF ENVIRONMENT (2020)

Add to Collection
Article Environmental Sciences

WHU-Hi: UAV-borne hyperspectral with high spatial resolution (H2) benchmark datasets and classifier for precise crop identification based on deep convolutional neural network with CRF

Yanfei Zhong et al.

REMOTE SENSING OF ENVIRONMENT (2020)

Add to Collection
Article Engineering, Electrical & Electronic

Hyperspectral Image Classification Method Based on 2D-3D CNN and Multibranch Feature Fusion

Zixian Ge et al.

IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING (2020)

Add to Collection
Article Geochemistry & Geophysics

Deep Pyramidal Residual Networks for Spectral-Spatial Hyperspectral Image Classification

Mercedes E. Paoletti et al.

IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING (2019)

Add to Collection
Article Engineering, Electrical & Electronic

Hyperspectral Image Classification Method Based on CNN Architecture Embedding With Hashing Semantic Feature

Chunyan Yu et al.

IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING (2019)

Add to Collection
Article Geochemistry & Geophysics

Learning Compact and Discriminative Stacked Autoencoder for Hyperspectral Image Classification

Peicheng Zhou et al.

IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING (2019)

Add to Collection
Article Geochemistry & Geophysics

A CNN With Multiscale Convolution and Diversified Metric for Hyperspectral Image Classification

Zhiqiang Gong et al.

IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING (2019)

Add to Collection
Article Environmental Sciences

Double-Branch Multi-Attention Mechanism Network for Hyperspectral Image Classification

Wenping Ma et al.

REMOTE SENSING (2019)

Add to Collection
Article Geochemistry & Geophysics

Unsupervised Spatial-Spectral Feature Learning by 3D Convolutional Autoencoder for Hyperspectral Classification

Shaohui Mei et al.

IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING (2019)

Add to Collection
Article Geochemistry & Geophysics

Deep Learning for Hyperspectral Image Classification: An Overview

Shutao Li et al.

IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING (2019)

Add to Collection
Article Multidisciplinary Sciences

Automated optimized parameters for T-distributed stochastic neighbor embedding improve visualization and analysis of large datasets

Anna C. Belkina et al.

NATURE COMMUNICATIONS (2019)

Add to Collection
Article Environmental Sciences

Hyperspectral Images Classification Based on Dense Convolutional Networks with Spectral-Wise Attention Mechanism

Bei Fang et al.

REMOTE SENSING (2019)

Add to Collection
Article Geochemistry & Geophysics

Deformable Convolutional Neural Networks for Hyperspectral Image Classification

Jian Zhu et al.

IEEE GEOSCIENCE AND REMOTE SENSING LETTERS (2018)

Add to Collection
Article Engineering, Electrical & Electronic

Nonlocal Similarity Based Nonnegative Tucker Decomposition for Hyperspectral Image Denoising

Xiao Bai et al.

IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING (2018)

Add to Collection
Article Geochemistry & Geophysics

Hyperspectral Image Classification With Deep Learning Models

Xiaofei Yang et al.

IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING (2018)

Add to Collection
Article Geochemistry & Geophysics

Generative Adversarial Networks for Hyperspectral Image Classification

Lin Zhu et al.

IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING (2018)

Add to Collection
Article Geochemistry & Geophysics

Spectral-Spatial Residual Network for Hyperspectral Image Classification: A 3-D Deep Learning Framework

Zilong Zhong et al.

IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING (2018)

Add to Collection
Article Environmental Sciences

A Fast Dense Spectral-Spatial Convolution Network Framework for Hyperspectral Images Classification

Wenju Wang et al.

REMOTE SENSING (2018)

Add to Collection
Article Automation & Control Systems

A 3-D Gabor Phase-Based Coding and Matching Framework for Hyperspectral Imagery Classification

Sen Jia et al.

IEEE TRANSACTIONS ON CYBERNETICS (2018)

Add to Collection
Article Geochemistry & Geophysics

Deep Recurrent Neural Networks for Hyperspectral Image Classification

Lichao Mou et al.

IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING (2017)

Add to Collection
Article Geochemistry & Geophysics

Learning to Diversify Deep Belief Networks for Hyperspectral Image Classification

Ping Zhong et al.

IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING (2017)

Add to Collection
Article Computer Science, Artificial Intelligence

Going Deeper With Contextual CNN for Hyperspectral Image Classification

Hyungtae Lee et al.

IEEE TRANSACTIONS ON IMAGE PROCESSING (2017)

Add to Collection
Article Computer Science, Artificial Intelligence

Convolutional neural networks for hyperspectral image classification

Shiqi Yu et al.

NEUROCOMPUTING (2017)

Add to Collection
Article Environmental Sciences

Spectral-Spatial Classification of Hyperspectral Imagery with 3D Convolutional Neural Network

Ying Li et al.

REMOTE SENSING (2017)

Add to Collection
Article Geochemistry & Geophysics

Deep Feature Extraction and Classification of Hyperspectral Images Based on Convolutional Neural Networks

Yushi Chen et al.

IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING (2016)

Add to Collection
Article Geography, Physical

Learning multiscale and deep representations for classifying remotely sensed imagery

Wenzhi Zhao et al.

ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING (2016)

Add to Collection
Article Geochemistry & Geophysics

A Survey on Spectral-Spatial Classification Techniques Based on Attribute Profiles

Pedram Ghamisi et al.

IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING (2015)

Add to Collection
Article Engineering, Electrical & Electronic

Deep Convolutional Neural Networks for Hyperspectral Image Classification

Wei Hu et al.

JOURNAL OF SENSORS (2015)

Add to Collection
Article Engineering, Electrical & Electronic

A Study on the Effectiveness of Different Independent Component Analysis Algorithms for Hyperspectral Image Classification

Nicola Falco et al.

IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING (2014)

Add to Collection
Article Geochemistry & Geophysics

Spectral-Spatial Hyperspectral Image Classification via Multiscale Adaptive Sparse Representation

Leyuan Fang et al.

IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING (2014)

Add to Collection
Review Environmental Sciences

Good practices for estimating area and assessing accuracy of land change

Pontus Olofsson et al.

REMOTE SENSING OF ENVIRONMENT (2014)

Add to Collection
Article Geochemistry & Geophysics

Hyperspectral Remote Sensing Data Analysis and Future Challenges

Jose M. Bioucas-Dias et al.

IEEE GEOSCIENCE AND REMOTE SENSING MAGAZINE (2013)

Add to Collection
Article Geochemistry & Geophysics

Semi-supervised graph-based hyperspectral image classification

Gustavo Camps-Valls et al.

IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING (2007)

Add to Collection
Article Geochemistry & Geophysics

Band, selection for hyperspectral image classification using mutual information

Baofeng Guo et al.

IEEE GEOSCIENCE AND REMOTE SENSING LETTERS (2006)

Add to Collection
Webinars Posters Questions Hubs Funding Journals Papers Connect Collections Reviewers About Us FAQs Mobile App Privacy Policy Terms of Use
© Peeref 2019-2024. All rights reserved.