Results 61 to 70 of about 49,483 (287)

A Spectral Spatial Attention Fusion with Deformable Convolutional Residual Network for Hyperspectral Image Classification

Remote Sensing, 2021
Convolutional neural networks (CNNs) have exhibited excellent performance in hyperspectral image classification. However, due to the lack of labeled hyperspectral data, it is difficult to achieve high classification accuracy of hyperspectral images with ...
Tianyu Zhang, Cuiping Shi, Diling Liao, Liguo Wang   +3 more
doaj   +1 more source

Ink Classification in Hyperspectral Images

, 2020
Hyperspectral imaging provides vital information about the objects and elements present inside the image. That’s why they are very useful in satellite imagery as well as image forensics. Hyperspectral document analysis (HSDI) can be used for document authentication using ink analysis which can provide sufficient information about the ...
Bilal, Muhammad, Ahmad, Haris, Ali, Muhammad Khizer   +2 more
openaire   +2 more sources

Single‐Cell Metabolic Imaging and Digital Scoring of Fat Tissue Remodeling by Label‐Free Metabolic Microscopy

Advanced Science, EarlyView.
Mid‐infrared optoacoustic microscopy (MiROM) acquires lipid‐ and protein‐ associated vibrational contrast in intact fat tissue without dyes, preserving native tissue architecture. Through lateral and axial segmentation, MiROM tracks intrinsic intracellular changes during postnatal remodeling. A quantitative spatial analysis tool (Q‐SAT) maps white‐ and
Myeongseop Kim, Constantin Berger, Alexander Wolf, Alina Peteranderl, Martin Klingenspor, Vasilis Ntziachristos, Yongguo Li, Miguel A. Pleitez   +7 more
wiley   +1 more source

Fast Spectral Clustering for Unsupervised Hyperspectral Image Classification

Remote Sensing, 2019
Hyperspectral image classification is a challenging and significant domain in the field of remote sensing with numerous applications in agriculture, environmental science, mineralogy, and surveillance.
Yang Zhao, Yuan Yuan, Qi Wang
doaj   +1 more source

Cohort‐Scale Spatial Autocorrelation for Tumor Prediction in Mid‐Infrared Pathology and Spatial Biomarker Discovery Using MALDI Imaging Lipidomics

Advanced Science, EarlyView.
Computational annotation of various tissue types in heterogeneous samples such as colorectal cancer liver metastasis (CRLM) using spatial autocorrelation analysis on non‐destructive mid‐infrared (MIR) imaging data enabled correlative multimodal mass spectrometry imaging (MSI) for spatial investigation of lipid tumor marker candidates. The method can be
Miriam F. Rittel, Nikolas Ebert, Denis Abu Sammour, Sebastian Graf, Björn C. Fröhlich, Emrullah Birgin, Shad A. Mohammed, Nuh N. Rahbari, Axel Wellmann, Oliver Wasenmüller, Cleo‐Aron Weis, Stefan Schmidt, Carsten Hopf   +12 more
wiley   +1 more source

Classification for hyperspectral imaging [PDF]

, 2014
Hyperspectral Imaging is a method of collecting and processing the information across pre-defined electromagnetic spectrum. These measurements make it possible to derive a continuous spectrum for each pixel of the image. After necessary adjustments these image spectra can be compared with database of reflectance spectra in order to recognise tested ...
Polak, Adam, Marshall, Stephen, Ren, Jinchang, Stothard, David J.M.   +3 more
openaire  

Hyperspectral Image Classification via Kernel Sparse Representation [PDF]

IEEE Transactions on Geoscience and Remote Sensing, 2011
In this paper, a new technique for hyperspectral image classification is proposed. Our approach relies on the sparse representation of a test sample with respect to all training samples in a feature space induced by a kernel function. Projecting the samples into the feature space and kernelizing the sparse representation improves the separability of ...
Yi Chen, Nasser M. Nasrabadi, Trac D. Tran   +2 more
openaire   +1 more source

Bayesian Gravitation-Based Classification for Hyperspectral Images

IEEE Transactions on Geoscience and Remote Sensing, 2022
Integration of spectral and spatial information is extremely important for the classification of high-resolution hyperspectral images (HSIs). Gravitation describes interaction among celestial bodies which can be applied to measure similarity between data for image classification.
Aizhu Zhang, Genyun Sun, Zhaojie Pan, Jinchang Ren, Xiuping Jia, Chenglong Zhang, Hang Fu, Yanjuan Yao   +7 more
openaire   +2 more sources

AI‐Enhanced Vibrational Capsule for Minimally Invasive Detection of Abnormal Bowel Tissue

Advanced Science, EarlyView.
A fully integrated vibration‐assisted capsule is presented for the minimally invasive detection of bowel lesions. The capsule incorporates a wireless sensor and an eccentric motor to probe tissue mechanics in situ. By coupling triaxial vibration signals with AI‐based classification and analytical modeling, the system enables early, non‐visual ...
Xizheng Fang, Yao Yan, Kenneth Omokhagbo Afebu, Andrew Bickerdike, Bo Tian, Yang Liu, Shyam Prasad   +6 more
wiley   +1 more source

High‐Content SRS Imaging Unveils Altered Cholesterol Metabolism in Ovarian Cancers Under CAR‐T Treatment

Advanced Science, EarlyView.
High‐content Stimulated Raman Scattering (SRS) Imaging reveals that ovarian cancer cells surviving Chimeric Antigen Receptor (CAR) ‐T cell challenge exhibit increased cholesterol esterification. Pharmacological inhibition of this pathway with Avasimibe significantly enhances CAR‐T induced killing of ovarian cancer cells by reducing cancer cell ...
Chinmayee V. Prabhu Dessai, Zhuoying Huang, Haonan Lin, Guangrui Ding, Hongjian He, Menna Siddiqui, Meng Zhang, Wilson Wong, Ji‐Xin Cheng   +8 more
wiley   +1 more source