Results 11 to 20 of about 20,723,044 (331)
Influence of deep levels on the electrical transport properties of CdZnTeSe detectors [PDF]
Journal of Applied Physics, 2018 We investigated the influence of deep levels on the electrical transport properties of CdZnTeSe radiation detectors by comparing experimental data with numerical simulations based on simultaneous solution of drift-diffusion and Posisson equations ...
Dědič, V +6 more
core +2 more sources
Deep levels in a-plane, high Mg-content MgxZn1-xO epitaxial layers grown by molecular beam epitaxy [PDF]
, 2012 Deep level defects in n-type unintentionally doped a-plane MgxZn1−xO, grown by molecular beam epitaxy on r-plane sapphire were fully characterized using deep level optical spectroscopy (DLOS) and related methods.
A. Arehart +7 more
core +4 more sources
Materials Science-Poland, 2013 In this study we present the results of investigations on Schottky Au-GaN diodes by means of conventional DLTS and Laplace DLTS methods within the temperature range of 77–350 K. Si-doped GaN layers were grown by Molecular Beam Epitaxy technique (MBE) on sapphire substrates.
Paulina Kamyczek +3 more
openaire +2 more sources
Deep Industrial Image Anomaly Detection: A Survey [PDF]
Machine Intelligence Research, 2023 The recent rapid development of deep learning has laid a milestone in industrial image anomaly detection (IAD). In this paper, we provide a comprehensive review of deep learning-based image anomaly detection techniques, from the perspectives of neural ...
Jiaqi Liu +6 more
semanticscholar +1 more source
Scaling deep learning for materials discovery
Nature, 2023 Novel functional materials enable fundamental breakthroughs across technological applications from clean energy to information processing^ 1 – 11 . From microchips to batteries and photovoltaics, discovery of inorganic crystals has been bottlenecked by ...
Amil Merchant +5 more
semanticscholar +1 more source
Speech recognition with deep recurrent neural networks [PDF]
IEEE International Conference on Acoustics, Speech, and Signal Processing, 2013 Recurrent neural networks (RNNs) are a powerful model for sequential data. End-to-end training methods such as Connectionist Temporal Classification make it possible to train RNNs for sequence labelling problems where the input-output alignment is ...
Alex Graves +2 more
semanticscholar +1 more source
Multimodal deep learning for biomedical data fusion: a review
Briefings Bioinform., 2022 Biomedical data are becoming increasingly multimodal and thereby capture the underlying complex relationships among biological processes. Deep learning (DL)-based data fusion strategies are a popular approach for modeling these nonlinear relationships ...
S. Stahlschmidt +2 more
semanticscholar +1 more source
Letter to the Editor: Chest radiograph: 'Let the reader beware'
South African Journal of Radiology, 2003 No abstact ...
Don Emby
doaj +1 more source
Electronic properties of deep levels in p‐type CdTe [PDF]
, 1983 DLTS and associated electrical measurements were made on unintentionally doped CdTe crystals obtained from several vendors, on Cu‐doped CdTe, and on Te‐annealed CdTe. All of the crystals were p‐type. Four majority carrier deep levels were observed in the
Collins, R. T., McGill, T. C.
core +1 more source
Journal of Physics and Chemistry of Solids, 1995 Abstract The photoluminescence spectra of AgGaSe 2 obtained at 77 K are reported. Two emission peaks have been observed and their pressure dependence studied. One of these peaks has been identified with emission involving one of the two deep-level peaks, D 1 and D 2 observed previously in absorption measurement [ Appl. Phys. Lett. 64, 1717 (
Choi, I.-H., Yu, P.Y.
openaire +2 more sources