Papers with Code · CC BY-SA 4.0

Hyperspectral Image Classification

Hyperspectral › Hyperspectral Image Classification 96 평가 기록 8 datasets

Hyperspectral Image Classification is a task in the field of remote sensing and computer vision. It involves the classification of pixels in hyperspectral images into different classes based on their spectral signature. Hyperspectral images contain information about the reflectance of objects in hundreds of narrow, contiguous wavelength bands, making them useful for a wide range of applications, including mineral mapping, vegetation analysis, and urban land-use mapping. The goal of this task is to accurately identify and classify different types of objects in the image, such as soil, vegetation, water, and buildings, based on their spectral properties.

<span style="color:grey; opacity: 0.6">( Image credit: Shorten Spatial-spectral RNN with Parallel-GRU for Hyperspectral Image Classification )</span>

개요는 각 항목의 일부입니다. 위 탭에서 전체 기록을 페이지별로 탐색할 수 있습니다.

벤치마크

Papers with Code 아카이브의 데이터셋별 기록 예시입니다. 평가 조건과 지표 방향이 검증되지 않아 순위를 의미하지 않습니다.

Dataset기록된 모델 예시MetricPaperCode

Indian Pines

HyperspectralMAE

OA@15perclass: 92.37

논문 -

Pavia University

RPNet-RF

OA@15perclass: 95.60

논문 코드

Kennedy Space Center

RPNet-RF

OA@15perclass: 98.51

논문 코드

CASI University of Houston

SSDGL

Overall Accuracy: 95.36

논문 코드

Houston

A-SPN

Overall Accuracy: 97.27%

논문 코드

Salinas

JigsawHSI

OA@200: 100.00

논문 코드

Salinas Scene

HybridSN

Overall Accuracy: 100%

논문 코드

Botswana

FSKNet

Overall Accuracy: 1

논문 코드

데이터셋

8개

Indian Pines Pavia University Kennedy Space Center CASI University of Houston Houston Salinas Salinas Scene Botswana

Generative Adversarial Networks Based on Collaborative Learning and Attention Mechanism for Hyperspectral Image Classification

2020-04-03 이 페이지의 평가 1건

OA@15perclass: 76.81±0.91

Generative Adversarial Networks Based on Transformer Encoder and Convolution Block for Hyperspectral Image Classification

2022-07-16 이 페이지의 평가 1건

OA@15perclass: 93.20±0.59

라이브러리

Papers with Code 리더보드 row에 연결된 구현 저장소입니다.

github.com/nshaud/DeepHyperX 1 논문

github.com/swalpa/Classification-of-Hyperspectral-Image 1 논문

github.com/szubing/S-DMM 1 논문

github.com/UchaevD/RPNet-RF 1 논문

github.com/YonghaoXu/RPNet 1 논문

github.com/YuxiangZhang-BIT/IEEE_TNNLS_Gia-CFSL 1 논문

github.com/zhoufangqin/hylite 1 논문

Hyperspectral Image Classification

벤치마크

데이터셋

논문

Deep Metric Learning-Based Feature Embedding for Hyperspectral Image Classification

Deep supervised learning for hyperspectral data classification through convolutional neural networks

Feature Extraction of Hyperspectral Images With Image Fusion and Recursive Filtering

Generative Adversarial Networks Based on Collaborative Learning and Attention Mechanism for Hyperspectral Image Classification

Generative Adversarial Networks Based on Transformer Encoder and Convolution Block for Hyperspectral Image Classification

Graph Information Aggregation Cross-Domain Few-Shot Learning for Hyperspectral Image Classification

HSI-BERT: Hyperspectral Image Classification Using the Bidirectional Encoder Representation From Transformers

Hyperspectral Image Classification of Convolutional Neural Network Combined with Valuable Samples

Hyperspectral image classification via a random patches network

Locality-Aware Hyperspectral Classification

Small Sample Hyperspectral Image Classification Based on the Random Patches Network and Recursive Filtering

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

라이브러리