Fully Automated Identification of Two-Dimensional Material Samples
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Carolin Gold | Riccardo Pisoni | Eliska Greplova | Benedikt Kratochwil | Tim Davatz | Annika Kurzmann | Peter Rickhaus | Mark H. Fischer | Thomas Ihn | Sebastian D. Huber | T. Ihn | S. Huber | P. Rickhaus | M. H. Fischer | C. Gold | B. Kratochwil | Tim Davatz | R. Pisoni | A. Kurzmann | E. Greplova | Riccardo Pisoni | Carolin Gold
[1] Eric A. Wan,et al. Neural network classification: a Bayesian interpretation , 1990, IEEE Trans. Neural Networks.
[2] T. Ihn,et al. Electrostatically Induced Quantum Point Contacts in Bilayer Graphene. , 2017, Nano letters.
[3] K. Shepard,et al. Boron nitride substrates for high-quality graphene electronics. , 2010, Nature nanotechnology.
[4] Recent progress in the assembly of nanodevices and van der Waals heterostructures by deterministic placement of 2D materials. , 2017, Chemical Society reviews.
[5] M. Prato,et al. Science and technology roadmap for graphene, related two-dimensional crystals, and hybrid systems. , 2015, Nanoscale.
[6] Roger G. Melko,et al. Machine learning phases of matter , 2016, Nature Physics.
[7] A. Neto,et al. Making graphene visible , 2007, Applied Physics Letters.
[8] D. Graf,et al. Tuning superconductivity in twisted bilayer graphene , 2018, Science.
[9] X. Duan,et al. Van der Waals heterostructures and devices , 2016 .
[10] Jürgen Schmidhuber,et al. Multi-column deep neural network for traffic sign classification , 2012, Neural Networks.
[11] Penghui Li,et al. Rapid identification of two-dimensional materials via machine learning assisted optic microscopy , 2019, Journal of Materiomics.
[12] Madan Dubey,et al. Two-dimensional material nanophotonics , 2014, 1410.3882.
[13] P. Avouris,et al. Photodetectors based on graphene, other two-dimensional materials and hybrid systems. , 2014, Nature nanotechnology.
[14] A. Ferrari,et al. Graphene Photonics and Optoelectroncs , 2010, CLEO 2012.
[15] SUPARNA DUTTASINHA,et al. Van der Waals heterostructures , 2013, Nature.
[16] Giuseppe Iannaccone,et al. Electronics based on two-dimensional materials. , 2014, Nature nanotechnology.
[17] Geoffrey E. Hinton,et al. Learning representations by back-propagating errors , 1986, Nature.
[18] Hua Zhang,et al. Rapid and reliable thickness identification of two-dimensional nanosheets using optical microscopy. , 2013, ACS nano.
[19] Jed I. Ziegler,et al. Bandgap engineering of strained monolayer and bilayer MoS2. , 2013, Nano letters.
[20] Satoru Masubuchi,et al. Classifying optical microscope images of exfoliated graphene flakes by data-driven machine learning , 2019, npj 2D Materials and Applications.
[21] K. Novoselov,et al. 2D materials and van der Waals heterostructures , 2016, Science.
[22] David J. Schwab,et al. A high-bias, low-variance introduction to Machine Learning for physicists , 2018, Physics reports.
[23] Makoto Yamada,et al. Deep-learning-based quality filtering of mechanically exfoliated 2D crystals , 2019, npj Computational Materials.
[24] Aurélien Géron,et al. Hands-On Machine Learning with Scikit-Learn and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems , 2017 .
[25] L. Lauhon,et al. Emerging device applications for semiconducting two-dimensional transition metal dichalcogenides. , 2014, ACS nano.
[26] Weisheng Zhao,et al. Intelligent identification of two-dimensional nanostructures by machine-learning optical microscopy , 2018, Nano Research.
[27] Takashi Taniguchi,et al. Unconventional superconductivity in magic-angle graphene superlattices , 2018, Nature.
[28] Sotiris B. Kotsiantis,et al. Supervised Machine Learning: A Review of Classification Techniques , 2007, Informatica.
[29] Takashi Taniguchi,et al. Hunting for monolayer boron nitride: optical and Raman signatures. , 2011, Small.
[30] Vijay Vasudevan,et al. Learning Transferable Architectures for Scalable Image Recognition , 2017, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.
[31] Kenji Watanabe,et al. Deep-learning-based image segmentation integrated with optical microscopy for automatically searching for two-dimensional materials , 2020, npj 2D Materials and Applications.
[32] Werner Wegscheider,et al. Automated Tuning of Double Quantum Dots into Specific Charge States Using Neural Networks , 2019 .
[33] T. Ihn,et al. Transport Through a Network of Topological Channels in Twisted Bilayer Graphene. , 2018, Nano letters.
[34] Qing Hua Wang,et al. Electronics and optoelectronics of two-dimensional transition metal dichalcogenides. , 2012, Nature nanotechnology.
[35] Lucila Ohno-Machado,et al. Logistic regression and artificial neural network classification models: a methodology review , 2002, J. Biomed. Informatics.
[36] T. Ihn,et al. Coupled Quantum Dots in Bilayer Graphene. , 2018, Nano letters.
[37] CireşAnDan,et al. 2012 Special Issue , 2012 .
[38] Alain C. Diebold,et al. Spectroscopic imaging ellipsometry for automated search of flakes of mono- and n-layers of 2D-materials , 2017 .
[39] Gang Sun,et al. Squeeze-and-Excitation Networks , 2017, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.
[40] C. K. Andersen,et al. Quantum parameter estimation with a neural network , 2017, 1711.05238.
[41] T. Ihn,et al. Spin and Valley States in Gate-Defined Bilayer Graphene Quantum Dots , 2018, Physical Review X.
[42] Takashi Taniguchi,et al. Autonomous robotic searching and assembly of two-dimensional crystals to build van der Waals superlattices , 2018, Nature Communications.