Results 21 to 30 of about 4,082 (191)

SquconvNet: Deep Sequencer Convolutional Network for Hyperspectral Image Classification

Remote Sensing, 2023
The application of Transformer in computer vision has had the most significant influence of all the deep learning developments over the past five years.
Bing Li, Qi-Wen Wang, Jia-Hong Liang, En-Ze Zhu, Rong-Qian Zhou   +4 more
doaj   +2 more sources

Vision Transformer-Based Ensemble Learning for Hyperspectral Image Classification

Remote Sensing, 2023
Hyperspectral image (HSI) classification, due to its characteristic combination of images and spectra, has important applications in various fields through pixel-level image classification.
Jun Liu, Haoran Guo, Yile He, Huali Li
doaj   +2 more sources

Hyperspectral Image Classification with Multi-Scale Feature Extraction

Remote Sensing, 2019
Spectral features cannot effectively reflect the differences among the ground objects and distinguish their boundaries in hyperspectral image (HSI) classification.
Bing Tu, Nanying Li, Leyuan Fang, Danbing He, Pedram Ghamisi   +4 more
doaj   +2 more sources

Hyperspectral imaging (HSI) for intraoperative tumor cell classification [PDF]

Laryngo-Rhino-Otologie, 2019
R Beck, H Köhler, F Goltz, A Dietz, C Chalopin, I Gockel   +5 more
openaire   +2 more sources

Disease Detection and Classification Using Deep Learning-Enhanced Hyperspectral Imaging (HSI)

The Hyperspectral Imaging (HSI) has emerged as an effective disease detection and classifier that has a high-resolution spectral and spatial data, which accurately detects small biological changes. Combining with deep learning, HSI systems are automatically able to extract complex spectralxpsatial features of an image, enhancing diagnostic performance ...
Ayesha Farooqi, Nikhil Kumar Goyal
openaire   +2 more sources

Refinement of Hyperspectral Image Classification with Segment-Tree Filtering

Remote Sensing, 2017
This paper proposes a novel method of segment-tree filtering to improve the classification accuracy of hyperspectral image (HSI). Segment-tree filtering is a versatile method that incorporates spatial information and has been widely applied in image ...
Lu Li, Chengyi Wang, Jingbo Chen, Jianglin Ma   +3 more
doaj   +2 more sources

A Novel Transformer Network with a CNN-Enhanced Cross-Attention Mechanism for Hyperspectral Image Classification

Remote Sensing
Recently, with the remarkable advancements of deep learning in the field of image processing, convolutional neural networks (CNNs) have garnered widespread attention from researchers in the domain of hyperspectral image (HSI) classification.
Xinyu Wang, Le Sun, Chuhan Lu, Baozhu Li
doaj   +2 more sources

ACTL: Asymmetric Convolutional Transfer Learning for Tree Species Identification Based on Deep Neural Network

IEEE Access, 2021
The identification of tree species is of great significance to the sustainable management and utilization of forest ecosystems. Hyperspectral data provide sufficient spectral and spatial information to classify tree species. Convolutional neural networks
Yun Shi, Donghui Ma, Jie Lv, Jie Li
doaj   +1 more source

WHU-OHS: A benchmark dataset for large-scale Hersepctral Image classification

International Journal of Applied Earth Observations and Geoinformation, 2022
Hyperspectral image (HSI) classification is one of the most important remote sensing techniques. Currently, the performances of most of the HSI classification networks on the public HSI datasets are overoptimistic (i.e., the overall accuracy exceeds 98 %)
Jiayi Li, Xin Huang, Lilin Tu
doaj   +1 more source

A semi-supervised cycle-GAN neural network for hyperspectral image classification with minimum noise fraction

Journal of Spectral Imaging, 2022
Hyperspectral imaging (HSI) is a popular mode of remote sensing imaging that collects data beyond the visible spectrum. Many classification techniques have been developed in recent years, since classification is the most crucial task in hyperspectral ...
Tatireddy Subba Reddy, Jonnadula Harikiran   +1 more
doaj   +1 more source