Results 71 to 80 of about 2,924,189 (218)

Background Learning Based on Target Suppression Constraint for Hyperspectral Target Detection

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2020
Hyperspectral target detection is critical in both military and civilian applications. However, it is a challenging task due to the complexity of background and the limited samples of target in hyperspectral images (HSIs).
Weiying Xie, Xin Zhang, Yunsong Li, Keyan Wang, Qian Du   +4 more
doaj   +1 more source

Anomaly Detection of Remote Sensing Images Based on the Channel Attention Mechanism and LRX

Applied Sciences, 2023
Anomaly detection of remote sensing images has gained significant attention in remote sensing image processing due to their rich spectral information. The Local RX (LRX) algorithm, derived from the Reed–Xiaoli (RX) algorithm, is a hyperspectral anomaly ...
Huinan Guo, Hua Wang, Xiaodong Song, Zhongling Ruan   +3 more
doaj   +1 more source

Challenges in Hyperspectral Imaging for Autonomous Driving: The HSI-Drive Case

2025 15th Workshop on Hyperspectral Imaging and Signal Processing: Evolution in Remote Sensing (WHISPERS)
The use of hyperspectral imaging (HSI) in autonomous driving (AD), while promising, faces many challenges related to the specifics and requirements of this application domain. On the one hand, non-controlled and variable lighting conditions, the wide depth-of-field ranges, and dynamic scenes with fast-moving objects. On the other hand, the requirements
Koldo Basterretxea, Jon Gutiérrez-Zaballa, Javier Echanobe   +2 more
openaire   +3 more sources

ManUSPECTRAL – the Mannheim Urology HyperSPECTRAL Imaging Atlas of 17 Physiological Human Organs

BJU International, EarlyView.
Objectives To establish a standardised intraoperative hyperspectral imaging (HSI) human organ reference dataset and to characterise spectral signatures across organ classes as a foundation for future computational and clinical applications. Subjects and Methods Intraoperative assessment of anatomical structures and tissue quality such as perfusion or ...
Alexander Rathenborg, Vera Klütz, Paula Grützner, Luisa Hartung, Greta Demmel, Christoph Julien Bender, Jan Sellner, Silvia Seidlitz, Caelan Max Haney‐Aubert, Wahid Fattal, Tilmann Clanget, Berkin Özdemir, Samuel Knoedler, Gabriel Alexander Salg, Luisa Renner, Nicolas Carl, Cuyler Yu, Charlene Leung, Dominic Edelmann, Nicholas Schreck, Maurice Stephan Michel, Lena Maier‐Hein, Karl‐Friedrich Kowalewski   +22 more
wiley   +1 more source

Locality Regularized Robust-PCRC: A Novel Simultaneous Feature Extraction and Classification Framework for Hyperspectral Images [PDF]

, 2020
Despite the successful applications of probabilistic collaborative representation classification (PCRC) in pattern classification, it still suffers from two challenges when being applied on hyperspectral images (HSIs) classification: 1) ineffective ...
Ling, Wing-Kuen, Cao, Faxian, Yang, Zhijing, Hu, Ruo, Cheng, Yongqiang   +4 more
core   +1 more source

O129 CLASSIFICATION OF BARRETT’S CARCINOMA SPECIMENS BY HYPERSPECTRAL IMAGING (HSI)

Diseases of the Esophagus, 2019
Abstract Aim Hyperspectral imaging (HSI) technology combines imaging with spectroscopy and can be used for the classification of malignant and non-malignant cells. Thereby HSI combined with artificial intelligent algorithms can be used to predict tumor cells in in Barrett’s carcinoma specimens.
Thieme René, Maktabi Marianne, Köhler Hannes, Chalopin Claire, Jansen-Winkeln Boris, Gockel Ines   +5 more
openaire   +1 more source

Brain tissue classification in hyperspectral images using multistage diffusion features and transformer

Journal of Microscopy, EarlyView.
Abstract Brain surgery is a widely practised and effective treatment for brain tumours, but accurately identifying and classifying tumour boundaries is crucial to maximise resection and avoid neurological complications. This precision in classification is essential for guiding surgical decisions and subsequent treatment planning.
Neetu Sigger, Tuan T. Nguyen, Gianluca Tozzi   +2 more
wiley   +1 more source

Hyperspectral clustering using atrous spatial-spectral convolutional network

, 2022
: Hyperspectral imaging is an important technology in the field of geosciences and remote sensing. However, the high-dimensional nature of hyperspectral images (HSIs) together with the limited availability of training/labeled samples challenge an ...
Ghamisi, Pedram, Scheunders, Paul, Rasti, Behnood, Gloaguen, Richard, Shahi, Kasra Rafiezadeh   +4 more
core   +1 more source

Guiding the AI revolution in periodontology and implant dentistry: Concepts, ethics, accountability, and a roadmap for sustainable adoption

Periodontology 2000, EarlyView.
Abstract Background Artificial intelligence (AI) is increasingly gaining attention in the field of periodontology and implant dentistry. Currently developed models can support diagnosis, treatment planning, and maintenance monitoring. However, most of the available literature is based on retrospective and often single‐modality data sets.
Aminollah Khormali, Negin Soghli, Patricia A. Miguez   +2 more
wiley   +1 more source

Hyperspectral Image Resolution Enhancement Based on Spectral Unmixing and Information Fusion [PDF]

, 2011
Hyperspectral imaging sensors exibit high spectral resolution, but normally low spatial resolution. This leads to spectral signatures of pixels originating from different object types. Such pixels are called mixed pixels.
Avbelj, Janja, Reinartz, Peter, Müller, Rupert, Cerra, Daniele, Bieniarz, Jakub   +4 more
core