Results 81 to 90 of about 7,130 (165)

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

open access: yesLaryngo-Rhino-Otologie, 2019
R Beck   +5 more
openaire   +1 more source

Self- and Cross-Attention Enhanced Transformer for Visible and Thermal Infrared Hyperspectral Image Classification

open access: yesIEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Visible hyperspectral image (V-HSI) and thermal infrared hyperspectral image (TI-HSI) have been crucial data sources for land cover classification. V-HSI can directly provide information of land surface, such as shape, color, texture, and other features.
Enyu Zhao   +5 more
doaj   +1 more source

Joint Alternate Small Convolution and Feature Reuse for Hyperspectral Image Classification

open access: yesISPRS International Journal of Geo-Information, 2018
A hyperspectral image (HSI) contains fine and rich spectral information and spatial information of ground objects, which has great potential in applications.
Hongmin Gao   +4 more
doaj   +1 more source

Structure Extraction With Total Variation for Hyperspectral Image Classification

open access: yesIEEE Access, 2019
This paper proposes a novel structure extraction approach that is able to achieve high classification accuracy and low computing burden to hyperspectral image (HSI) classification based on total variation (SETV).
Qiaoqiao Li   +4 more
doaj   +1 more source

Improving Hyperspectral Image Classification with Compact Multi-Branch Deep Learning

open access: yesRemote Sensing
The progress in hyperspectral image (HSI) classification owes much to the integration of various deep learning techniques. However, the inherent 3D cube structure of HSIs presents a unique challenge, necessitating an innovative approach for the efficient
Md. Rashedul Islam   +3 more
doaj   +1 more source

A Joint Network of 3D-2D CNN Feature Hierarchy and Pyramidal Residual Model for Hyperspectral Image Classification

open access: yesIEEE Access
Since convolutional neural networks (CNN) can extract deeper features from hyperspectral images, they show good classification performance in the hyperspectral image (HSI) classification task. However, the performance of many CNN models is constrained by
Hongwei Wei   +4 more
doaj   +1 more source

An Experimental Study for the Effects of Noise on Hyperspectral Imagery Classification

open access: yesImage Analysis and Stereology
Hyperspectral image (HSI) classification is a very important topic in remote sensing. There are many published methods for HSI classification in the literature. Nevertheless, it is not clear which method is the most robust to noise in HSI data cubes. In
Guangyi Chen, Adam Krzyzak, Shen-en Qian
doaj   +1 more source

AMHFN: Aggregation Multi-Hierarchical Feature Network for Hyperspectral Image Classification

open access: yesRemote Sensing
Deep learning methods like convolution neural networks (CNNs) and transformers are successfully applied in hyperspectral image (HSI) classification due to their ability to extract local contextual features and explore global dependencies, respectively ...
Xiaofei Yang   +5 more
doaj   +1 more source

Differentiating cytology of pancreatic ductal adenocarcinoma and pancreatic neuroendocrine tumors by EUS-FNA through hyperspectral imaging technology combined with artificial intelligence. [PDF]

open access: yesTherap Adv Gastroenterol
Qin X   +15 more
europepmc   +1 more source

Overcoming difficulties in segmentation of hyperspectral plant images with small projection areas using machine learning. [PDF]

open access: yesSci Rep
Neuwirthová E   +9 more
europepmc   +1 more source

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