Results 91 to 100 of about 35,844 (297)

Inland excess water mapping using hyperspectral imagery [PDF]

Geographica Pannonica, 2016
Geographica Pannonica; Vol 20, No 4, 2016.
Csendes Bálint, Mucsi László
openaire   +3 more sources

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

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

Drones: Innovative Technology for Use in Precision Pest Management. [PDF]

, 2020
Arthropod pest outbreaks are unpredictable and not uniformly distributed within fields. Early outbreak detection and treatment application are inherent to effective pest management, allowing management decisions to be implemented before pests are well ...
de Lange, Elvira S, Heldens, Wieke B, Iost Filho, Fernando H, Kong, Zhaodan   +3 more
core   +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

Macrophage Phenotype Detection Methodology on Textured Surfaces via Nuclear Morphology Using Machine Learning

Advanced Intelligent Discovery, EarlyView.
A novel machine learning approach classifies macrophage phenotypes with up to 98% accuracy using only nuclear morphology from DAPI‐stained images. Bypassing traditional surface markers, the method proves robust even on complex textured biomaterial surfaces. It offers a simpler, faster alternative for studying macrophage behavior in various experimental
Oleh Mezhenskyi, Kateryna Andriienkova, Tetyana Goldanova, Ezgi Antmen, Thibaut Soubrie, Nihal Engin Vrana   +5 more
wiley   +1 more source

Deep Learning‐Assisted Coherent Raman Scattering Microscopy

Advanced Intelligent Discovery, EarlyView.
The analytical capabilities of coherent Raman scattering microscopy are augmented through deep learning integration. This synergistic paradigm improves fundamental performance via denoising, deconvolution, and hyperspectral unmixing. Concurrently, it enhances downstream image analysis including subcellular localization, virtual staining, and clinical ...
Jianlin Liu, Rujia Liu, Xinyan Zhang, Xun Chen, Shuhua Yue   +4 more
wiley   +1 more source

Overcoming the Nyquist Limit in Molecular Hyperspectral Imaging by Reinforcement Learning

Advanced Intelligent Discovery, EarlyView.
Explorative spectral acquisition guide automatically selects informative spectral bands to optimize downstream tasks, outperforming full‐spectrum acquisition. The selected hyperspectral data are used for tasks such as unmixing and segmentation. BandOptiNet encodes selection states and outputs optimal bands to guide spectral acquisition. Recent advances
Xiaobin Tang, Yongqing Zhang, Xinyu Deng, Hyeon Jeong Lee, Delong Zhang   +4 more
wiley   +1 more source

When Low Rank Representation Based Hyperspectral Imagery Classification Meets Segmented Stacked Denoising Auto-Encoder Based Spatial-Spectral Feature

Remote Sensing, 2018
When confronted with limited labelled samples, most studies adopt an unsupervised feature learning scheme and incorporate the extracted features into a traditional classifier (e.g., support vector machine, SVM) to deal with hyperspectral imagery ...
Cong Wang, Lei Zhang, Wei Wei, Yanning Zhang   +3 more
doaj   +1 more source

Metalens‐Enabled Twisted Chromatic Dispersion

Advanced Physics Research, EarlyView.
We successfully demonstrate visible broadband twisted dispersion metalenses. As a proof of concept, we realized two distinct devices: the conical helical and the spring‐like dispersion‐controlled metalenses. These results rigorously validate the universality of our approach in customizing arbitrary continuous 3D dispersion trajectories, thereby ...
Shiyu Zheng, Boyan Fu, Hong Zhang, Shuming Wang   +3 more
wiley   +1 more source