Found: 8
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Utilizing Geospatial Data for Assessing Energy Security: Mapping Small Solar Home Systems Using Unmanned Aerial Vehicles and Deep Learning.
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- ISPRS International Journal of Geo-Information, 2022, v. 11, n. 4, p. 222, doi. 10.3390/ijgi11040222
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- Article
Machine Learning for Engineering Meta‐Atoms with Tailored Multipolar Resonances.
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- Laser & Photonics Reviews, 2024, v. 18, n. 7, p. 1, doi. 10.1002/lpor.202300855
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- Article
Deep Learning the Electromagnetic Properties of Metamaterials—A Comprehensive Review.
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- Advanced Functional Materials, 2021, v. 31, n. 31, p. 1, doi. 10.1002/adfm.202101748
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- Article
Closing the domain gap: blended synthetic imagery for climate object detection.
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- Environmental Data Science, 2023, v. 2, p. 1, doi. 10.1017/eds.2023.33
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- Article
Heterogeneity and Memory Effect in the Sluggish Dynamics of Vacancy Defects in Colloidal Disordered Crystals and Their Implications to High‐Entropy Alloys.
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- Advanced Science, 2022, v. 9, n. 36, p. 1, doi. 10.1002/advs.202205522
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- Article
Self-Supervised Encoders Are Better Transfer Learners in Remote Sensing Applications.
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- Remote Sensing, 2022, v. 14, n. 21, p. 5500, doi. 10.3390/rs14215500
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- Article
Learning the Physics of All‐Dielectric Metamaterials with Deep Lorentz Neural Networks.
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- Advanced Optical Materials, 2022, v. 10, n. 13, p. 1, doi. 10.1002/adom.202200097
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- Article
Transfer learning for metamaterial design and simulation.
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- Nanophotonics (21928606), 2024, v. 13, n. 13, p. 2323, doi. 10.1515/nanoph-2023-0691
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- Article