HDMNet: A Hierarchical Matching Network with Double Attention for Large-scale Outdoor LiDAR Point Cloud Registration

Outdoor LiDAR point clouds are typically large-scale and complexly distributed. To achieve efficient and accurate registration, emphasizing the similarity among local regions and prioritizing global local-to-local matching is of utmost importance, subsequent to which accuracy can be enhanced through cost-effective fine registration. In this paper, a novel hierarchical neural network with double attention named HDMNet is proposed for large-scale outdoor LiDAR point cloud registration. Specifically, A novel feature consistency enhanced double-soft matching network is introduced to achieve two-stage matching with high flexibility while enlarging the receptive field with high efficiency in a patch-to patch manner, which significantly improves the registration performance. Moreover, in order to further utilize the sparse matching information from deeper layer, we develop a novel trainable embedding mask to incorporate the confidence scores of correspondences obtained from pose estimation of deeper layer, eliminating additional computations. The high-confidence keypoints in the sparser point cloud of the deeper layer correspond to a high-confidence spatial neighborhood region in shallower layer, which will receive more attention, while the features of non-key regions will be masked. Extensive experiments are conducted on two large-scale outdoor LiDAR point cloud datasets to demonstrate the high accuracy and efficiency of the proposed HDMNet.Comment: Accepted by WACV202

Rate effect of liquid infiltration into mesoporous materials

Rate effect of liquid infiltration in mesopores is associated with both liquid viscosity and the solid–liquid interfacial effect.</p

Long-persistence blue phosphors

This invention relates to phosphors including long-persistence blue phosphors. Phosphors of the invention are represented by the general formula: MO . mAl.sub.2 O.sub.3 :Eu.sup.2+,R.sup.3+ wherein m is a number ranging from about 1.6 to about 2.2, M is Sr or a combination of Sr with Ca and Ba or both, R.sup.3+ is a trivalent metal ion or trivalent Bi or a mixture of these trivalent ions, Eu.sup.2+ is present at a level up to about 5 mol % of M, and R.sup.3+ is present at a level up to about 5 mol % of M. Phosphors of this invention include powders, ceramics, single crystals and single crystal fibers. A method of manufacturing improved phosphors and a method of manufacturing single crystal phosphors are also provided

Association between polymorphism of TGFA Taq I and cleft Lip and/or palate: a meta-analysis

BACKGROUND: Cleft lip and palate (CL/P) is one of the most common malformations in humans. Transforming growth factor alpha (TGFA) is a well characterized mammalian growth factor which might contribute to the development of CL/P. This meta-analysis aimed to summarize the association between the TGFA Taq I polymorphisms and CL/P. METHODS: We retrieved the relevant articles from PubMed, EMBASE, ISI Web of Science and SCOPUS databases. Studies were selected using specific inclusion and exclusion criteria. The odds ratios (ORs) and their 95% confidence intervals (95% CIs) were calculated to assess the association between TGFA Taq I polymorphism and CL/P risk. Meta-analyses were performed on the total data set and separately for the major ethnic groups, disease type and source of control. All analyses were performed using the Stata software. RESULTS: Twenty articles were included in the present analysis. There is a significant association between the TGFA Taq I polymorphism and CL/P (C1C2 vs C1C1: OR = 1.67, 95% CI = 1.23-2.25, C2C2 + C1C2 vs C1C1C1: OR = 1.52, 95% CI = 1.15-2.01; C2 vs C1:OR = 1.41, 95% CI = 1.12-1.78). Stratified analyses suggested that the TGFA Taq I polymorphism was significantly associated with CL/P in Caucasians (C1C2 vs C1C1: OR = 1.95, 95% CI = 1.34-2.86; C2C2 + C1C2 vs C1C1: OR = 1.68, 95% CI = 1.18-2.38; C2 vs V1: OR = 1.52, 95% CI = 1.14 -2.02). CONCLUSION: TGFA Taq I polymorphism may be associated with the risk of CL/P

Efficient generation of isolated attosecond pulses with high beam-quality by two-color Bessel-Gauss beams

The generation of isolated attosecond pulses with high efficiency and high beam quality is essential for attosec- ond spectroscopy. We numerically investigate the supercontinuum generation in a neutral rare-gas medium driven by a two-color Bessel-Gauss beam. The results show that an efficient smooth supercontinuum in the plateau is obtained after propagation, and the spatial profile of the generated attosecond pulse is Gaussian-like with the divergence angle of 0.1 degree in the far field. This bright source with high beam quality is beneficial for detecting and controlling the microscopic processes on attosecond time scale.Comment: 3 pages, 3 figure

Letting a Neural Network Decide Which Machine Translation System to Use for Black-Box Fuzzy-Match Repair

While systems using the Neural Network-based Machine Translation (NMT) paradigm achieve the highest scores on recent shared tasks, phrase-based (PBMT) systems, rule-based (RBMT) systems and other systems may get better results for individual examples. Therefore, combined systems should achieve the best results for MT, particularly if the system combination method can take advantage of the strengths of each paradigm. In this paper, we describe a system that predicts whether a NMT, PBMT or RBMT will get the best Spanish translation result for a particular English sentence in DGT-TM 20161. Then we use fuzzy-match repair (FMR) as a mechanism to show that the combined system outperforms individual systems in a black-box machine translation setting.John E. Ortega is supported by the Universitat d’Alacant and the Spanish government through the EFFORTUNE (TIN2015-69632-R) project. Kyunghyun Cho was partly supported by Samsung Advanced Institute of Technology (Next Generation Deep Learning: from pattern recognition to AI) and Samsung Electronics (Improving Deep Learning using Latent Structure)

Automated Olfactory Bulb Segmentation on High Resolutional T2-Weighted MRI

The neuroimage analysis community has neglected the automated segmentation of the olfactory bulb (OB) despite its crucial role in olfactory function. The lack of an automatic processing method for the OB can be explained by its challenging properties. Nonetheless, recent advances in MRI acquisition techniques and resolution have allowed raters to generate more reliable manual annotations. Furthermore, the high accuracy of deep learning methods for solving semantic segmentation problems provides us with an option to reliably assess even small structures. In this work, we introduce a novel, fast, and fully automated deep learning pipeline to accurately segment OB tissue on sub-millimeter T2-weighted (T2w) whole-brain MR images. To this end, we designed a three-stage pipeline: (1) Localization of a region containing both OBs using FastSurferCNN, (2) Segmentation of OB tissue within the localized region through four independent AttFastSurferCNN - a novel deep learning architecture with a self-attention mechanism to improve modeling of contextual information, and (3) Ensemble of the predicted label maps. The OB pipeline exhibits high performance in terms of boundary delineation, OB localization, and volume estimation across a wide range of ages in 203 participants of the Rhineland Study. Moreover, it also generalizes to scans of an independent dataset never encountered during training, the Human Connectome Project (HCP), with different acquisition parameters and demographics, evaluated in 30 cases at the native 0.7mm HCP resolution, and the default 0.8mm pipeline resolution. We extensively validated our pipeline not only with respect to segmentation accuracy but also to known OB volume effects, where it can sensitively replicate age effects

The band-gap structures and recovery rules of generalized n-component Fibonacci piezoelectric superlattices

The spectral evolution from periodic structure to random structure has always been an interesting topic in solid state physics, the generalized n-component Fibonacci sequences (n- CF) provide a convenient tool to investigate such process since its randomness can be controlled via the parameter n. In this letter, the band-gap structures of n-CF piezoelectric superlattices have been calculated using the transfer-matrix-method, the self-similarity behavior and recovery rule have been systematically analyzed. Consistent with the rigorous mathematical proof by Hu et al.[A. Hu et al. Phys. Rev. B. 48, 829 (1993)], we find that the n-CF sequences with 2 \leq n \leq 4 are identified as quasiperiodic. The imaginary wave numbers are characterized by the self-similar spectrum, their major peaks can all be properly indexed. In addition, we find that the n = 5 sequence belongs to a critical case which lies at the border between quasiperiodic to aperiodic structures. The frequency range of self-similarity pattern approaches to zero and a unique indexing of imaginary wave numbers becomes impossible. Our study offers the information on the critical 5-CF superlattice which was not available before. The classification of band-gap structures and the scaling laws around fixed points are also given