MINIMAL LEARNING MACHINE IN ANOMALY DETECTION FROM HYPERSPECTRAL IMAGES

MINIMAL LEARNING MACHINE IN ANOMALY DETECTION FROM HYPERSPECTRAL IMAGES

Anomaly detection from hyperspectral data needs computationally efficient methods to process the data when the data gathering platform is a drone or a cube satellite. In this study, we introduce a minimal learning machine for hyperspectral anomaly detection. Minimal learning machine is a novel dista...

书目详细资料
Main Authors:	I. Pölönen, K. Riihiaho, A.-M. Hakola, L. Annala
格式:	文件
语言:	English
出版:	Copernicus Publications 2020-08-01
丛编:	The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
在线阅读:	https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLIII-B3-2020/467/2020/isprs-archives-XLIII-B3-2020-467-2020.pdf

相似书籍

PIECEWISE ANOMALY DETECTION USING MINIMAL LEARNING MACHINE FOR HYPERSPECTRAL IMAGES
由: A.-M. Raita-Hakola, et al.
出版: (2021-06-01)

A Do-It-Yourself Hyperspectral Imager Brought to Practice with Open-Source Python
由: Kimmo Aukusti Riihiaho, et al.
出版: (2021-02-01)

PRACTICAL APPROACH FOR HYPERSPECTRAL IMAGE PROCESSING IN PYTHON
由: L. Annala, et al.
出版: (2018-04-01)

FPI Based Hyperspectral Imager for the Complex Surfaces—Calibration, Illumination and Applications
由: Anna-Maria Raita-Hakola, et al.
出版: (2022-04-01)

Hyperspectral Anomaly Detection Based on Machine Learning: An Overview
由: Yichu Xu, et al.
出版: (2022-01-01)

Firefront Forecasting in Boreal Forests: Machine Learning Approach to Predict Wildfire Propagation
由: A.-M. Raita-Hakola, et al.
出版: (2024-11-01)

HYPERBLEND: SIMULATING SPECTRAL REFLECTANCE AND TRANSMITTANCE OF LEAF TISSUE WITH BLENDER
由: K. A. Riihiaho, et al.
出版: (2022-05-01)

Comparison of Machine Learning Methods in Stochastic Skin Optical Model Inversion
由: Leevi Annala, et al.
出版: (2020-10-01)

Reflectance Measurement Method Based on Sensor Fusion of Frame-Based Hyperspectral Imager and Time-of-Flight Depth Camera
由: Samuli Rahkonen, et al.
出版: (2022-11-01)

Anomaly Detection Based on Tree Topology for Hyperspectral Images
由: Xiaotong Sun, et al.
出版: (2023-01-01)

Anomaly Detection in Hyperspectral Images via Regularization by Denoising
由: Mauro Luiz Brandao Junior, et al.
出版: (2022-01-01)

Clustering based background learning for hyperspectral anomaly detection
由: Mohamad Ebrahim Aghili, et al.
出版: (2023-12-01)

HYPERSPECTRAL ANOMALY DETECTION IN URBAN SCENARIOS
由: J. G. Rejas Ayuga, et al.
出版: (2016-06-01)

Hyperspectral Anomaly Detection Using Deep Learning: A Review
由: Xing Hu, et al.
出版: (2022-04-01)

Anomaly detection and compensation for hyperspectral imagery
由: Cho, Choongyeun, 1973-
出版: (2006)

Greedy Ensemble Hyperspectral Anomaly Detection
由: Mazharul Hossain, et al.
出版: (2024-05-01)

Hyperspectral Imaging and Machine Learning for Huanglongbing Detection on Leaf-Symptoms
由: Ruihao Dong, et al.
出版: (2025-02-01)

Anomaly Detection from Hyperspectral Remote Sensing Imagery
由: Qiandong Guo, et al.
出版: (2016-12-01)

Hyperspectral Anomaly Detection Based on Intrinsic Image Decomposition and Background Subtraction
由: Jiao Jiao, et al.
出版: (2025-01-01)

Clusters versus GPUs for Parallel Target and Anomaly Detection in Hyperspectral Images
由: Antonio Plaza, et al.
出版: (2010-01-01)

Learning-Free Hyperspectral Anomaly Detection With Unpredictive Frequency Residual Priors
由: Shichao Zhou, et al.
出版: (2022-01-01)

A Semiparametric Model for Hyperspectral Anomaly Detection
由: Dalton Rosario
出版: (2012-01-01)

Pixel-associated autoencoder for hyperspectral anomaly detection
由: Pei Xiang, et al.
出版: (2024-05-01)

RANet: Relationship Attention for Hyperspectral Anomaly Detection
由: Yingzhao Shao, et al.
出版: (2023-11-01)

An Efficient and Robust Framework for Hyperspectral Anomaly Detection
由: Linbo Tang, et al.
出版: (2021-10-01)

Hyperspectral Anomaly Detection With Morphological Random Walker
由: Zhihong Huang, et al.
出版: (2021-01-01)

Matrix Autoregressive Model for Hyperspectral Anomaly Detection
由: Jingxuan Wang, et al.
出版: (2022-01-01)

Structured Background Modeling for Hyperspectral Anomaly Detection
由: Fei Li, et al.
出版: (2018-09-01)

Exploiting Weighted Multidirectional Sparsity for Prior Enhanced Anomaly Detection in Hyperspectral Images
由: Jingjing Liu, et al.
出版: (2025-02-01)

Multi-Dimensional Low-Rank with Weighted Schatten <i>p</i>-Norm Minimization for Hyperspectral Anomaly Detection
由: Xi’ai Chen, et al.
出版: (2023-12-01)

Hyperspectral imaging benchmark based on machine learning for intraoperative brain tumour detection
由: Raquel Leon, et al.
出版: (2023-11-01)

Advancing Algorithmic Adaptability in Hyperspectral Anomaly Detection with Stacking-Based Ensemble Learning
由: Bradley J. Wheeler, et al.
出版: (2024-10-01)

Hyperspectral Anomaly Detection via Sparse Dictionary Learning Method of Capped Norm
由: Yuan Yuan, et al.
出版: (2019-01-01)

Orthogonal Subspace Projection Target Detector for Hyperspectral Anomaly Detection
由: Chein-I Chang, et al.
出版: (2021-01-01)

Detection of Apple Proliferation Disease Using Hyperspectral Imaging and Machine Learning Techniques
由: Uwe Knauer, et al.
出版: (2024-12-01)

Detection of Pear Quality Using Hyperspectral Imaging Technology and Machine Learning Analysis
由: Zishen Zhang, et al.
出版: (2024-12-01)

Detection of Pesticide Residue Level in Grape Using Hyperspectral Imaging with Machine Learning
由: Weixin Ye, et al.
出版: (2022-05-01)

Hyperspectral Anomaly Detection via Graphical Connected Point Estimation and Multiple Support Vector Machines
由: Shangzhen Song, et al.
出版: (2020-01-01)

The Spectrum Difference Enhanced Network for Hyperspectral Anomaly Detection
由: Shaohua Liu, et al.
出版: (2024-12-01)

Spectral–Spatial Feature Fusion for Hyperspectral Anomaly Detection
由: Shaocong Liu, et al.
出版: (2024-03-01)