Results 11 to 20 of about 417 (152)

Multiscale Superpixel-Based Sparse Representation for Hyperspectral Image Classification [PDF]

Remote Sensing, 2017
Recently, superpixel segmentation has been proven to be a powerful tool for hyperspectral image (HSI) classification. Nonetheless, the selection of the optimal superpixel size is a nontrivial task.
Shutao Li, Shuzhen Zhang, Wei Fu
exaly   +4 more sources

Adaptive Multiscale Superpixel Embedding Convolutional Neural Network for Land Use Classification [PDF]

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2022
Currently, a large number of remote sensing images with different resolutions are available for Earth observation and land monitoring, which are inevitably demanding intelligent analysis techniques for accurately identifying and classifying land use (LU).
Huaizhong Zhang, Callum Altham, Marcello Trovati, Ce Zhang, Iain Rolland, Lanre Lawal, Dozien Wegbu, Nemitari Ajienka   +7 more
doaj   +3 more sources

Artificial Intelligence-Based Approaches for Brain Tumor Segmentation in MRI: A Review. [PDF]

NMR Biomed
Manually segmenting brain tumors in magnetic resonance imaging is a time‐consuming task that requires years of professional experience and clinical expertise. We proposed a study, which contains a comprehensive review of the brain tumor segmentation techniques. It selects the effective approaches to better understand the AI applications for brain tumor
Bibi K, Nawaz M, Khan S, Daud M, Masood A, Abdelgawad MA, Abbasi SMT, Rizwan, Khan A, Yuan W.   +9 more
europepmc   +2 more sources

Hyperspectral Imagery Classification Based on Multiscale Superpixel-Level Constraint Representation [PDF]

Remote Sensing, 2020
Sparse representation (SR)-based models have been widely applied for hyperspectral image classification. In our previously established constraint representation (CR) model, we exploited the underlying significance of the sparse coefficient and proposed ...
Haoyang Yu, Xiao Zhang, Meiping Song, Jiaochan Hu, Qiandong Guo, Lianru Gao   +5 more
doaj   +2 more sources

Enhanced Leaf Disease Segmentation Using U-Net Architecture for Precision Agriculture: A Deep Learning Approach. [PDF]

Food Sci Nutr
This study proposes a deep learning‐based approach for leaf disease identification using the U‐Net architecture for precise segmentation. By training on a dataset of 7056 annotated leaf images, the model effectively distinguishes between healthy and diseased regions, achieving 99.70% training accuracy and 98.99% validation accuracy in 40 epochs.
Singh G, Al-Huqail AA, Almogren A, Kaur S, Joshi K, Singh A, Bharany S, Hussen S, Rehman AU.   +8 more
europepmc   +2 more sources

Multiscale Superpixel-Guided Weighted Graph Convolutional Network for Polarimetric SAR Image Classification

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Polarimetric synthetic aperture radar (PolSAR) has attracted more attentions because of its excellent observation ability, and PolSAR image classification has become one of the significant tasks in remote sensing interpretation.
Ru Wang, Yinju Nie, Jie Geng
doaj   +2 more sources

Superpixel-Guided Matrix-Valued Kernel Functions for Multiscale Nonlinear Hyperspectral Unmixing

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Hyperspectral unmixing is a critical challenge in the analysis of hyperspectral remote sensing data. Due to the complex interactions between incident light and materials, which are significantly influenced by the three-dimensional geometry of the scene ...
Xiu Zhao, Meiping Song
doaj   +2 more sources

Multiscale Graph Transformer Network With Dynamic Superpixel Pyramid for Hyperspectral Image Classification

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Hyperspectral image (HSI) classification plays a crucial role in remote sensing applications, leveraging the rich spectral and spatial information inherent in HSI.
Tingting Wang, Yao Sun, Yunfeng Hu
doaj   +2 more sources

Polarimetric SAR ship detection based on superpixel and sparse reconstruction saliency

工程科学学报, 2023
Polarimetric SAR ship detection is an important application of the polarimetric SAR system. Existing polarimetric SAR ship detection methods are plagued by erroneous detection of strong clutter and missed detection of small targets in multiscale ...
Jiahao LUO, Junjun YIN, Jian YANG
doaj   +1 more source

MSP : Refine Boundary Segmentation via Multiscale Superpixel

CoRR, 2021
In this paper, we propose a simple but effective message passing method to improve the boundary quality for the semantic segmentation result. Inspired by the generated sharp edges of superpixel blocks, we employ superpixel to guide the information passing within feature map.
Jie Zhu, Huabin Huang, Banghuai Li, Yong Liu, Leye Wang   +4 more
openaire   +2 more sources