Results 81 to 90 of about 12,889,375 (285)
Cross-Domain CNN for Hyperspectral Image Classification [PDF]
IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium, 2018 IGARSS ...
Hyungtae Lee, Sungmin Eum, Heesung Kwon
openaire +3 more sources
Tackling cancer stemness with nanotechnology in the era of precision medicine
BMEMat, EarlyView.Precise customization of nanoparticles (NPs) enables active targeting of cancer stem cells (CSCs), thereby improving drug delivery and therapeutic efficacy. NP‐based probing enhances CSC detection through imaging and liquid biopsy, whereas diverse therapeutic payloads improve therapeutic outcomes.
Shaolei Guo +9 more
wiley +1 more source
Deep Underground Science and Engineering, EarlyView.A lithology identification while drilling method was developed, integrating an automated cuttings sampling system, a smart drilling rig, and an ensemble learning model. Underground trials achieved 97.42% accuracy in real‐time identification of cuttings lithology and composition, enhancing hazard management and supporting unmanned drilling technology in
Kun Li +7 more
wiley +1 more source
A Spectral-Texture Kernel-Based Classification Method for Hyperspectral Images
Remote Sensing, 2016 Classification of hyperspectral images always suffers from high dimensionality and very limited labeled samples. Recently, the spectral-spatial classification has attracted considerable attention and can achieve higher classification accuracy and ...
Yi Wang, Yan Zhang, Haiwei Song
doaj +1 more source
Development of a new spectral library classifier for airborne hyperspectral images on heterogeneous environments [PDF]
, 2011 The classification of hyperspectral images on heterogeneous environments without prior knowledge about the study area is a challenging task. Finding potential pure spectral signatures or endmembers (EM) of the various surface materials within an image is
Mende, Andre +4 more
core
Eye &ENT Research, EarlyView.ABSTRACT Artificial intelligence (AI) is reshaping ophthalmology from task‐specific image analysis toward multimodal, longitudinal, and clinically integrated decision support. This narrative review summarizes the methodological evolution of ophthalmic AI, including traditional machine learning, task‐specific deep learning, self‐supervised learning ...
Yuxin Liu, Hanruo Liu
wiley +1 more source
International Journal of Advanced Robotic Systems, 2017 Hyperspectral remote sensing technology becomes more and more popular in recent years which can be applied to satellite, plane, and flying robots. An important application of hyperspectral remote sensing is the classification of ground objects.
Binge Cui +3 more
doaj +1 more source
Hyperspectral images segmentation: a proposal [PDF]
, 2009 Hyper-Spectral Imaging (HIS) also known as chemical or spectroscopic imaging is an emerging technique that combines imaging and spectroscopy to capture both spectral and spatial information from an object. Hyperspectral images are made up of contiguous
GORETTA, Nathalie +8 more
core
FlexMat, EarlyView.This review organizes flexible wearable electronics for cardiovascular monitoring into four interconnected information layers: surface electrophysiology, hemodynamic sensing, vascular imaging, and biofluid biomarker analysis. This framework clarifies how electrical rhythm, vascular loading, structural and flow‐related features, and biochemical states ...
Qiao Chen +5 more
wiley +1 more source
IEEE Access, 2020 Due to the characteristics of the spectrum integration, information redundancy, spectrum mixing phenomenon and nonlinearity of the hyperspectral remote sensing images, it is a major challenging task to classify the hyperspectral remote sensing images ...
Huayue Chen, Fang Miao, Xu Shen
doaj +1 more source