Results 61 to 70 of about 16,742 (260)

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

The Future of Hyperspectral Imaging [PDF]

Journal of Imaging, 2019
The Special Issue on hyperspectral imaging (HSI), entitled “The Future of Hyperspectral Imaging”, has published 12 papers. Nine papers are related to specific current research and three more are review contributions: In both cases, the request is to propose those methods or instruments so as to show the future trends of HSI.
openaire   +6 more sources

Emerging Device Applications From Strong Light–Matter Interactions in 2D Materials

Advanced Science, EarlyView.
Two‐dimensional semiconductors enable extremely compact optoelectronic devices such as solar cells, sensors, LEDs, and lasers. Their strong light–matter interactions allow efficient light emission, detection, and energy conversion. This review article discusses the recent progress in integrating these materials with optical cavities and nanostructures ...
Janani Archana K, Kumar Shwetabh, Reyas Ali, Ramji Velayutham, Koustav Das, Abhishek Mondal, Prashant Kumar, Surendra B. Anantharaman   +7 more
wiley   +1 more source

Band Selection via Band Density Prominence Clustering for Hyperspectral Image Classification

Remote Sensing
Band clustering has been widely used for hyperspectral band selection (BS). However, selecting an appropriate band to represent a band cluster is a key issue.
Chein-I Chang, Yi-Mei Kuo, Kenneth Yeonkong Ma   +2 more
doaj   +1 more source

Engineered Strain in 2D Materials by Direct Growth on Deterministically Patterned Grayscale Topographies

Advanced Science, EarlyView.
ABSTRACT Strain is a proven technique for modifying the bandgap and enhancing carrier mobility in 2D materials. Most current strain engineering techniques rely on the post‐growth transfer of these atomically thin materials from growth substrates to target surfaces, limiting their integration into nanoelectronics.
Berke Erbas, Arindam Bala, Hernan Furci, Anushree Dutta, Naresh Kumar, Renato Zenobi, Giovanni Boero, Andras Kis, Juergen Brugger   +8 more
wiley   +1 more source

MORPHOLOGICAL SEGMENTATION OF HYPERSPECTRAL IMAGES

Image Analysis & Stereology, 2011
The present paper develops a general methodology for the morphological segmentation of hyperspectral images, i.e., with an important number of channels. This approach, based on watershed, is composed of a spectral classification to obtain the markers and a vectorial gradient which gives the spatial information. Several alternative gradients are adapted
Noyel, Guillaume, Angulo, Jesus, Jeulin, Dominique   +2 more
openaire   +7 more sources

Generative Artificial Intelligence Shaping the Future of Agri‐Food Innovation

AgriFood: Journal of Agricultural Products for Food, EarlyView.
Emerging use cases of generative artificial intelligence in agri‐food innovation. ABSTRACT The recent surge in generative artificial intelligence (AI), typified by models such as GPT, diffusion models, and large vision‐language architectures, has begun to influence the agri‐food sector.
Jun‐Li Xu, Dimitrios Argyropoulos, Tamíris da Costa   +2 more
wiley   +1 more source

Application of Enhanced Weighted Least Squares with Dark Background Image Fusion for Inhomogeneity Noise Removal in Brain Tumor Hyperspectral Images

Applied Sciences
The inhomogeneity of spectral pixel response is an unavoidable phenomenon in hyperspectral imaging, which is mainly manifested by the existence of inhomogeneity banding noise in the acquired hyperspectral data.
Jiayue Yan, Chenglong Tao, Yuan Wang, Jian Du, Meijie Qi, Zhoufeng Zhang, Bingliang Hu   +6 more
doaj   +1 more source

What to Make and How to Make It: Combining Machine Learning and Statistical Learning to Design New Materials

Advanced Intelligent Discovery, EarlyView.
Combining machine learning and probabilistic statistical learning is a powerful way to discover and design new materials. A variety of machine learning approaches can be used to identify promising candidates for target applications, and causal inference can help identify potential ways to make them a reality.
Jonathan Y. C. Ting, Amanda S. Barnard
wiley   +1 more source

HyperKon: A Self-Supervised Contrastive Network for Hyperspectral Image Analysis

Remote Sensing
The use of a pretrained image classification model (trained on cats and dogs, for example) as a perceptual loss function for hyperspectral super-resolution and pansharpening tasks is surprisingly effective.
Daniel La’ah Ayuba, Jean-Yves Guillemaut, Belen Marti-Cardona, Oscar Mendez   +3 more
doaj   +1 more source