Results 31 to 40 of about 253,119 (310)

A multi-level context-guided classification method with object-based convolutional neural network for land cover classification using very high resolution remote sensing images

International Journal of Applied Earth Observations and Geoinformation, 2020
Classification of very high resolution imagery (VHRI) is challenging due to the difficulty in mining complex spatial and spectral patterns from rich image details.
Chenxiao Zhang, Peng Yue, Deodato Tapete, Boyi Shangguan, Mi Wang, Zhaoyan Wu   +5 more
doaj   +1 more source

Semisupervised Complex Network With Spatial Statistics Fusion for PolSAR Image Classification

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2023
Deep learning has achieved satisfactory results in polarimetric synthetic aperture radar (PolSAR) image classification, which requires a large number of labeled samples for training. However, in practice, labeling work is time-consuming and laborious. As
Yinyin Jiang, Ming Li, Peng Zhang, Wanying Song   +3 more
doaj   +1 more source

Geometry Aware Evaluation of Handcrafted Superpixel-Based Features and Convolutional Neural Networks for Land Cover Mapping Using Satellite Imagery

Remote Sensing, 2020
In land cover mapping at a high spatial resolution, pixel values alone are not always sufficient to recognize the more complex classes. Contextual features (computed with a sliding kernel or other kind of spatial support) can be discriminating for ...
Dawa Derksen, Jordi Inglada, Julien Michel   +2 more
doaj   +1 more source

AN ITERATIVE INFERENCE PROCEDURE APPLYING CONDITIONAL RANDOM FIELDS FOR SIMULTANEOUS CLASSIFICATION OF LAND COVER AND LAND USE [PDF]

ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2015
Land cover and land use exhibit strong contextual dependencies. We propose a novel approach for the simultaneous classification of land cover and land use, where semantic and spatial context is considered.
L. Albert, F. Rottensteiner, C. Heipke
doaj   +1 more source

Multiscale cross-fusion network for hyperspectral image classification

Egyptian Journal of Remote Sensing and Space Sciences, 2023
Recently, hyperspectral image (HSI) classification methods based on deep-learning have attracted widespread attention. Convolutional neural networks, as a crucial deep-learning technique, have exhibited outstanding performance in HSI classification ...
Haizhu Pan, Yuexia Zhu, Haimiao Ge, Moqi Liu, Cuiping Shi   +4 more
doaj   +1 more source

PolSAR Classification Using Contextual Based Locality Preserving Projection and Guided Filtering

International Journal of Information and Communication Technology Research, 2021
Contextual feature extraction is studied for polarimetric synthetic aperture radar (PolSAR) image classification in this work. The contextual locality preserving projection (CLPP) method is proposed for generation of contextual feature cubes using ...
Maryam Imani
doaj  

Right for the Right Reason: Training Agnostic Networks [PDF]

, 2018
We consider the problem of a neural network being requested to classify images (or other inputs) without making implicit use of a "protected concept", that is a concept that should not play any role in the decision of the network.
A Halevy, Aylin Caliskan, J Li, MD Zeiler, N Cristianini, O Russakovsky, W Chu, Y Ganin   +7 more
core   +3 more sources

Higher Order Support Vector Random Fields for Hyperspectral Image Classification

ISPRS International Journal of Geo-Information, 2018
This paper addresses the problem of contextual hyperspectral image (HSI) classification. A novel conditional random fields (CRFs) model, known as higher order support vector random fields (HSVRFs), is proposed for HSI classification.
Junli Yang, Zhiguo Jiang, Shuang Hao, Haopeng Zhang   +3 more
doaj   +1 more source

Robust hyperspectral image classification with rejection fields

, 2015
In this paper we present a novel method for robust hyperspectral image classification using context and rejection. Hyperspectral image classification is generally an ill-posed image problem where pixels may belong to unknown classes, and obtaining ...
Bioucas-Dias, Jose, Condessa, Filipe, Kovacevic, Jelena   +2 more
core   +1 more source

GLN-LRF: global learning network based on large receptive fields for hyperspectral image classification

Frontiers in Remote Sensing
Deep learning has been widely applied to high-dimensional hyperspectral image classification and has achieved significant improvements in classification accuracy.
Mengyun Dai, Tianzhe Liu, Youzhuang Lin, Zhengyu Wang, Yaohai Lin, Changcai Yang, Riqing Chen   +6 more
doaj   +1 more source