Compare More Nuanced:Pairwise Alignment Bilinear Network For Few-shot Fine-grained Learning

The recognition ability of human beings is developed in a progressive way. Usually, children learn to discriminate various objects from coarse to fine-grained with limited supervision. Inspired by this learning process, we propose a simple yet effective model for the Few-Shot Fine-Grained (FSFG) recognition, which tries to tackle the challenging fine-grained recognition task using meta-learning. The proposed method, named Pairwise Alignment Bilinear Network (PABN), is an end-to-end deep neural network. Unlike traditional deep bilinear networks for fine-grained classification, which adopt the self-bilinear pooling to capture the subtle features of images, the proposed model uses a novel pairwise bilinear pooling to compare the nuanced differences between base images and query images for learning a deep distance metric. In order to match base image features with query image features, we design feature alignment losses before the proposed pairwise bilinear pooling. Experiment results on four fine-grained classification datasets and one generic few-shot dataset demonstrate that the proposed model outperforms both the state-ofthe-art few-shot fine-grained and general few-shot methods.Comment: ICME 2019 Ora

Bis(2-cyclo­hexyl­imino­methyl-4,6-disulfanylphenolato)nickel(II) acetonitrile solvate

In the title compound, [Ni(C13H16NOS2)2]·CH3CN, the NiII atom is four-coordinated by two N,O-bidentate Schiff base ligands, resulting in a distorted tetra­hedral coordination for the metal ion

catena-Poly[[[aqua­(1,10-phenanthro­line)manganese(II)]-μ-adamantane-1,3-dicarboxyl­ato] monohydrate]

In the title coordination polymer, {[Mn(C12H14O4)(C12H8N2)(H2O)]·H2O}n, the MnII atom has a highly distorted cis-MnN2O4 octa­hedral geometry arising from its coordination by a bidentate phenanthroline ligand, a water mol­ecule and monodentate and bidentate adamantane-1,3-dicarboxyl­ate dianions. The bridging dianion leads to [001] chains in the crystal. The chains are linked by O—H⋯O hydrogen bonds, involving both the coordinated and uncoordinated water mol­ecules, thereby forming a two-dimensional network

Prevention of in-stent restenosis with endothelial progenitor cell (EPC) capture stent placement combined with regional EPC transplantation: An atherosclerotic rabbit model

Background: Even with drug-eluting stents, the risk of in-stent restenosis (ISR) remains high. The goal of this study was to investigate the use of an endothelial progenitor cell (EPC) capture stent plus regional EPC transplantation to reduce the ISR rate. Methods: Endothelial progenitor cell capture stents were fabricated using fibrin gel and anti-CD34 plus anti-VEGFR-2 dual antibodies. Twenty male New Zealand white rabbits established as an atherosclerotic model were randomly divided into two groups: group 1 (n = 10), in which EPC capture stents were deployed into the right iliac artery; and group 2 (n = 10), in which sirolimus-eluting stents were placed. In both groups, EPCs were transplanted into target vessels beyond the stents, with outflow blocked. Radiologic-pathologic correlation outcomes were reviewed after 2 months.  Results: The technical success rate of EPC capture stent placement plus EPC transplantation was 100%. The ISR rate in group 1 was lower than in group 2 (1/10 vs. 4/10; p > 0.05). Minimal luminal diameters were larger in group 1 than in group 2 (computed tomographic angiography, 1.85 ± 0.15 mm vs. 1.50 ± 0.20 mm; duplex ultrasound, 1.90 ± 0.10 mm vs. 1.70 ± 0.30 mm; p > 0.05). Transplanted EPCs were tracked positively only in group 1. Pathologic analysis demonstrated neointimal hyperplasia thickness of 0.21 ± 0.09 mm in group 1 vs. 0.11 ± 0.07 mm in group 2 (p < 0.05).  Conclusion: Endothelial progenitor cell capture stent placement plus local EPC transplant decreases the ISR rate through thrombosis reduction rather than through neointimal hyperplasia inhibition

Plasma Generation and Application in a Laser Ablation Pulsed Plasma Thruster

The laser ablation plasma thruster is a novel electric propulsion thruster, which combined the laser ablation and electromagnetic acceleration. In order to investigate the plasma expansion and ionization in the laser ablation plasma thruster, which was difficult to obtain from experiments, the heat conduction model and fluid dynamics model were established. The heat conduction model was established to calculate the target ablation, taking into account temperature-dependent material properties, phase transition, dielectric transition and phase explosion. The fluid dynamics model was used to calculate the plasma properties, taking into account ionization, plasma absorption and shielding. The ablation plasma velocity, temperature and electron number density were predicted by using the numerical method. The calculated results showed that the peak values of ablation plasma velocity, temperature and electron number density fraction were distributed at the front of the plasma plume. Moreover, the discharge characteristics and thrust performance were tested with different charged energy, structural parameters and propellants. The thrust performance was proven to be improved by electromagnetic acceleration

Applicability of Perturbative QCD to Pion Virtual Compton Scattering

We study explicitly the applicability of perturbative QCD (pQCD) to the pion virtual Compton scattering. It is found that there are central-region singularities introduced by the QCD running coupling constant, in addition to the end-point singularities generally existed in other exclusive processes such as the pion form factor. We introduce a simple technique to evaluate the contributions from these singularities, so that we can arrive at a judgement that these contributions will be unharmful to the applicability of pQCD at certain energy scale, i.e., the ``work point'' which is defined to determine when pQCD is applicable to exclusive processes. The applicability of pQCD for different pion distribution amplitudes are explored in detail. We show that pQCD begins to work at 10 ${GeV}^2$. If we relax our constraint to a weak sense, the work point may be as low as 4 ${GeV}^2$.Comment: 13 Latex pages, 10 figures, to appear in PL

Masked Cross-image Encoding for Few-shot Segmentation

Few-shot segmentation (FSS) is a dense prediction task that aims to infer the pixel-wise labels of unseen classes using only a limited number of annotated images. The key challenge in FSS is to classify the labels of query pixels using class prototypes learned from the few labeled support exemplars. Prior approaches to FSS have typically focused on learning class-wise descriptors independently from support images, thereby ignoring the rich contextual information and mutual dependencies among support-query features. To address this limitation, we propose a joint learning method termed Masked Cross-Image Encoding (MCE), which is designed to capture common visual properties that describe object details and to learn bidirectional inter-image dependencies that enhance feature interaction. MCE is more than a visual representation enrichment module; it also considers cross-image mutual dependencies and implicit guidance. Experiments on FSS benchmarks PASCAL-$5^i$ and COCO-$20^i$ demonstrate the advanced meta-learning ability of the proposed method.Comment: conferenc