Characterising the Thematic Content of Image Pixels with Topologically Structured Clustering

Characterising the Thematic Content of Image Pixels with Topologically Structured Clustering

The location of a pixel in feature space is a function of its thematic composition. The latter is central to an image classification analysis, notably as an input (e.g., training data for a supervised classifier) and/or an output (e.g., predicted class label). Whether as an input to or output from a...

Descrizione completa

Dettagli Bibliografici
Autore principale:	Giles M. Foody
Natura:	Articolo
Lingua:	English
Pubblicazione:	MDPI AG 2025-01-01
Serie:	Remote Sensing
Soggetti:	ground data reference data training sites unsupervised classification supervised classification Kohonen neural network
Accesso online:	https://www.mdpi.com/2072-4292/17/1/130

Documenti analoghi

Global and Local Assessment of Image Classification Quality on an Overall and Per-Class Basis without Ground Reference Data
di: Giles M. Foody
Pubblicazione: (2022-10-01)

ROAD DETECTION USING MORPHOLOGICAL OPERATIONS IN A COMPLEX SCENARIO
di: Neetha Joseph, et al.
Pubblicazione: (2013-11-01)

Improvement of land cover classification accuracy by training sample clustering
di: Artem Andreiev, et al.
Pubblicazione: (2024-04-01)

A Sample-Encoding Generalization of the Kohonen Associative Memory and Application to Knee Kinematic Data Representation and Pathology Classification
di: Badreddine Ben Nouma, et al.
Pubblicazione: (2019-04-01)

Ground Truth in Classification Accuracy Assessment: Myth and Reality
di: Giles M. Foody
Pubblicazione: (2024-02-01)

Comparison of Automatic Classification Methods for Identification of Ice Surfaces from Unmanned-Aerial-Vehicle-Borne RGB Imagery
di: Jakub Jech, et al.
Pubblicazione: (2023-10-01)

Application a Committee of Kohonen Neural Networks to Training of Image Classifier Based on Description of Descriptors Set
di: Volodymyr Gorokhovatskyi, et al.
Pubblicazione: (2024-01-01)

SS-DBSCAN: Semi-Supervised Density-Based Spatial Clustering of Applications With Noise for Meaningful Clustering in Diverse Density Data
di: Tiba Zaki Abdulhameed, et al.
Pubblicazione: (2024-01-01)

Classification of companies with theassistance of self-learning neural networks
di: Vladimír KONEČNÝ, et al.
Pubblicazione: (2010-02-01)

Comparing the potentials of the different canola flower indices for canola mapping based on Landsat 9 images
di: Haifeng Tian, et al.
Pubblicazione: (2024-12-01)

Comparing methodologies for mapping the afforestation of public streets in Chapada Neighbourhood, using pléiades images
di: Jessika Zambrano, et al.
Pubblicazione: (2025-02-01)

Classifying Facies in 3D Digital Rock Images Using Supervised and Unsupervised Approaches
di: Cenk Temizel, et al.
Pubblicazione: (2022-10-01)

Some pattern recognitions for a recommendation framework for higher education students’ generic competence development using machine learning
di: Chi-ho So, et al.
Pubblicazione: (2023-01-01)

Classifying the risk of forest loss in the Peruvian amazon rainforest: An alternative approach for sustainable forest management using artificial intelligence
di: Gianmarco Goycochea Casas, et al.
Pubblicazione: (2023-12-01)

Determining the Best Classification Algorithm in order to Estimate the Area under Date Palm Cultivation using LANDSAT 8 Satellite Imagery
di: S Rahnama, et al.
Pubblicazione: (2019-09-01)

Clustering Algorithm with a Greedy Agglomerative Heuristic and Special Distance Measures
di: Guzel Shkaberina, et al.
Pubblicazione: (2022-06-01)

Comparison of hyperspectral and multi-spectral imagery to building a spectral library and land cover classification performance
di: Mukesh Singh Boori, et al.
Pubblicazione: (2018-12-01)

A New Competitive Neural Architecture for Object Classification
di: Mohammed Madiafi, et al.
Pubblicazione: (2022-05-01)

Gearbox Condition Monitoring Using Advanced Classifiers
di: P. Večeř, et al.
Pubblicazione: (2010-01-01)

Remote sensing methods for estimating tree species of forests in the Volyn region, Ukraine
di: Oleksandr Melnyk, et al.
Pubblicazione: (2023-01-01)

Corrigendum: Remote sensing methods for estimating tree species of forests in the Volyn region, Ukraine
di: Oleksandr Melnyk, et al.
Pubblicazione: (2023-11-01)

Mapping Typical Urban LULC from Landsat Imagery without Training Samples or Self-Defined Parameters
di: Hui Li, et al.
Pubblicazione: (2017-07-01)

Unsupervised Hierarchical Classification Approach for Imprecise Data in the Breast Cancer Detection
di: Mario Fordellone, et al.
Pubblicazione: (2022-07-01)

Sketch distance-based clustering of chromosomes for large genome database compression
di: Tao Tang, et al.
Pubblicazione: (2019-12-01)

Application of a Multispectral SPOT Image for Land Use Classification in Sampean Watershed
di: Januar Fery Irawan, et al.
Pubblicazione: (2011-05-01)

An Analysis of the Effect of Data Augmentation Methods: Experiments for a Musical Genre Classification Task
di: Rémi Mignot, et al.
Pubblicazione: (2019-12-01)

A Maximum-Entropy Fuzzy Clustering Approach for Cancer Detection When Data Are Uncertain
di: Mario Fordellone, et al.
Pubblicazione: (2023-02-01)

Unsupervised PolSAR Image Classification Based on Superpixel Pseudo-Labels and a Similarity-Matching Network
di: Lei Wang, et al.
Pubblicazione: (2024-11-01)

Quantitative Detection of Chromium Pollution in Biochar Based on Matrix Effect Classification Regression Model
di: Mei Guo, et al.
Pubblicazione: (2021-04-01)

AUTOREGRESSIVE MODEL BASED ON BAYESIAN APPROACH FOR TEXTURE REPRESENTATION
di: T. Karthikeyan, et al.
Pubblicazione: (2012-08-01)

Unsupervised Pre-Training of Imbalanced Data for Identification of Wafer Map Defect Patterns
di: Ho Sun Shon, et al.
Pubblicazione: (2021-01-01)

Usage of self-organizing neural networks in evaluation of consumer behaviour
di: Jana Weinlichová, et al.
Pubblicazione: (2010-01-01)

FOREST COVER DIGITAL MAPPING OF THE KARELIAN PART OF THE WHITE SEA COASTAL ZONE BASED ON IMPROVED INTERPRETATION METHOD OF REMOTE SENSING DATA
di: Viktor Tarasenko, et al.
Pubblicazione: (2019-10-01)

Beyond Supervised Learning in Remote Sensing: A Systematic Review of Deep Learning Approaches
di: Benyamin Hosseiny, et al.
Pubblicazione: (2024-01-01)

A novel heuristic method for detecting overfit in unsupervised classification of climate model data
di: Emma J. D. Boland, et al.
Pubblicazione: (2023-01-01)

Unsupervised Classifications of Depression Levels Based on Machine Learning Algorithms Perform Well as Compared to Traditional Norm-Based Classifications
di: Zhenkai Yang, et al.
Pubblicazione: (2020-02-01)

An Electronic Registration for Undergraduate Students with Department Selection Based on Artificial Neural Network
di: Banaz Anwer Qader
Pubblicazione: (2018-03-01)

A Survey on Semi-, Self- and Unsupervised Learning for Image Classification
di: Lars Schmarje, et al.
Pubblicazione: (2021-01-01)

Data-Driven Signal–Noise Classification for Microseismic Data Using Machine Learning
di: Sungil Kim, et al.
Pubblicazione: (2021-03-01)

An Improved Pheromone-Based Kohonen Self- Organising Map in Clustering and Visualising Balanced and Imbalanced Datasets
di: Rubiyah Yusof, et al.
Pubblicazione: (2021-09-01)