Results 41 to 50 of about 495 (155)

Semi-Supervised Classification for PolSAR Data With Multi-Scale Evolving Weighted Graph Convolutional Network

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2021
Although deep learning-based methods have been successfully applied to polarimetric synthetic aperture radar (PolSAR) image classification tasks, most of the available techniques are not suitable to deal with PolSAR data on irregular domains, e.g ...
Shijie Ren, Feng Zhou
doaj   +1 more source

Multiscale superpixelwise prophet model for noise-robust feature extraction in hyperspectral images. [PDF]

, 2023
Despite of various approaches proposed to smooth the hyperspectral images (HSIs) before feature extraction, the efficacy is still affected by the noise, even using the corrected dataset with the noisy and water absorption bands discarded.
Zhao, Huimin, Yan, Yijun, Sun, Genyun, Zabalza, Jaime, Jia, Xiuping, Ren, Jinchang, Yan, Yijun; id_orcid, Ma, Ping   +7 more
core   +1 more source

SGML: A Symmetric Graph Metric Learning Framework for Efficient Hyperspectral Image Classification

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2022
Recently, the semi-supervised graph convolutional network (SSGCN) has been verified effective for hyperspectral image (HSI) classification. However, constrained by the limited training data and spectral uncertainty, the classification performance is ...
Yunsong Li, Bobo Xi, Jiaojiao Li, Rui Song, Yuchao Xiao, Jocelyn Chanussot   +5 more
doaj   +1 more source

Efficient Multiscale Object-based Superpixel Framework

Journal of the Brazilian Computer Society
Superpixel segmentation can be used as an intermediary step in many applications, often to improve object delineation and reduce computer workload. However, classical methods do not incorporate information about the desired object. Deep-learning-based approaches consider object information, but their delineation performance depends on data annotation ...
Felipe C. Belém, Benjamin Perret, Jean Cousty, Silvio J. F. Guimarães, Alexandre X. Falcão   +4 more
openaire   +2 more sources

Adjacent Superpixel-Based Multiscale Spatial-Spectral Kernel for Hyperspectral Classification

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2019
The kernel-based spatial-spectral approach has been widely used for hyperspectral image (HSI) classification in recent years, where composite kernel (CK) and spatial-spectral kernel (SSK) are the most representative methods. Unlike CK, SSK measures the similarity of two clusters in kernel space to capture the hidden manifold in HSI, which has proven to
Le Sun 0002, Chenyang Ma, Yunjie Chen, Hiuk Jae Shim, Zebin Wu 0001, Byeungwoo Jeon   +5 more
openaire   +1 more source

Fast and Effective Superpixel Segmentation using Accurate Saliency Estimation

, 2022
International audienceSuperpixels through Iterative CLEarcutting (SICLE) is a recently proposed framework for superpixel segmentation. SICLE consists of three steps: (i) seed oversampling; (ii) superpixel generation; and (iii) seed removal; such that ...
João, Leonardo, Belém, Felipe, Cousty, Jean, Guimarães, Silvio, Perret, Benjamin, Borlido, Isabela, Falcão, Alexandre   +6 more
core   +1 more source

MSG-SR-Net: A Weakly Supervised Network Integrating Multiscale Generation and Superpixel Refinement for Building Extraction From High-Resolution Remotely Sensed Imageries

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2022
Weakly supervised semantic segmentation (WSSS) methods based on image-level labels can relieve the tedious pixel-level annotation burden, and these methods are mainly based on class activation maps (CAMs).
Xin Yan, Li Shen, Jicheng Wang, Xu Deng, Zhilin Li   +4 more
doaj   +1 more source

Superpixel Based Segmentation of Historical Document Images Using a Multiscale Texture Analysis

, 2019
International audienceIn this paper, a superpixel based segmentation of Historical Document Images (HDIs) using multiscale texture analysis is proposed. A Simple Linear Iterative Clustering (SLIC) superpixel technique and Kmeans classifier are applied in
Chaieb, Ramzi, Ramzi Chaieb, Karim Kalti, Kalti, Karim, Emna Soyed, Soyed, Emna   +5 more
core   +1 more source

Multiscale Adaptive Convolution for Hyperspectral Image Classification

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2022
Convolutional neural network (CNN) is widely used in hyperspectral image (HSI) classification owing to their advantages of spatial-spectral features capture capability and learning depth features as well as their structural flexibility. Nevertheless, the
Qi Ren, Bing Tu, Qianming Li, Wangquan He, Yishu Peng   +4 more
doaj   +1 more source

Superpixel-based Fast Fuzzy C-Means Clustering for Color Image Segmentation [PDF]

, 2018
A great number of improved fuzzy c-means (FCM) clustering algorithms have been widely used for grayscale and color image segmentation. However, most of them are time-consuming and unable to provide desired segmentation results for color images due to two
Nandi, A, Meng, H, Jia, X, Liu, S, Zhang, Y, Lei, T   +5 more
core   +1 more source