GhostVLAD for set-based face recognition

The objective of this paper is to learn a compact representation of image sets for template-based face recognition. We make the following contributions: first, we propose a network architecture which aggregates and embeds the face descriptors produced by deep convolutional neural networks into a compact fixed-length representation. This compact representation requires minimal memory storage and enables efficient similarity computation. Second, we propose a novel GhostVLAD layer that includes {\em ghost clusters}, that do not contribute to the aggregation. We show that a quality weighting on the input faces emerges automatically such that informative images contribute more than those with low quality, and that the ghost clusters enhance the network's ability to deal with poor quality images. Third, we explore how input feature dimension, number of clusters and different training techniques affect the recognition performance. Given this analysis, we train a network that far exceeds the state-of-the-art on the IJB-B face recognition dataset. This is currently one of the most challenging public benchmarks, and we surpass the state-of-the-art on both the identification and verification protocols.Comment: Accepted by ACCV 201

Sequential Adaptive Detection for In-Situ Transmission Electron Microscopy (TEM)

We develop new efficient online algorithms for detecting transient sparse signals in TEM video sequences, by adopting the recently developed framework for sequential detection jointly with online convex optimization [1]. We cast the problem as detecting an unknown sparse mean shift of Gaussian observations, and develop adaptive CUSUM and adaptive SSRS procedures, which are based on likelihood ratio statistics with post-change mean vector being online maximum likelihood estimators with $\ell_1$. We demonstrate the meritorious performance of our algorithms for TEM imaging using real data

Biomass and grazing potential of the Stipa loess steppes in Ningxia (northern China) in relation to grazing intensity

The mere amount of biomass is not a suitable measuring unit for the economic value of a plant community, because not all species are equally appreciated by cattle and sheep and some are even unpalatable. That is why we summarised palatability and appreciation to a feeding value. Together with the biomass this feeding value was used to calculate the grazing potential of the plant communities investigated.In the Stipa loess steppes of Ningxia (northern China) the two characteristic feather grasses dominating in ungrazed or slightly grazed areas are estimated as species of very high feeding value. Those species, which show increasing biomass parallel to increasing grazing intensity are of lower feeding value. Except of overgrazed areas, the Stipa grandis steppes have a higher grazing potential than the Stipa bungeana communities. A comparison of biomass and grazing potential shows that the relative differences between the grazing potential of the communities existing at different grazing levels are much higher than the relative differences in biomass

Dynamic microscopic structures and dielectric response in the cubic-to-tetragonal phase transition for BaTiO3 studied by first-principles molecular dynamics simulation

The dynamic structures of the cubic and tetragonal phase in BaTiO3 and its dielectric response above the cubic-to-tetragonal phase transition temperature (Tp) are studied by first-principles molecular dynamics (MD) simulation. It's shown that the phase transition is due to the condensation of one of the transverse correlations. Calculation of the phonon properties for both the cubic and tetragonal phase shows a saturation of the soft mode frequency near 60 cm-1 near Tp and advocates its order-disorder nature. Our first-principles calculation leads directly to a two modes feature of the dielectric function above Tp [Phys. Rev. B 28, 6097 (1983)], which well explains the long time controversies between experiments and theories

GraphSE2^2: An Encrypted Graph Database for Privacy-Preserving Social Search

In this paper, we propose GraphSE$^2$, an encrypted graph database for online social network services to address massive data breaches. GraphSE$^2$ preserves the functionality of social search, a key enabler for quality social network services, where social search queries are conducted on a large-scale social graph and meanwhile perform set and computational operations on user-generated contents. To enable efficient privacy-preserving social search, GraphSE$^2$ provides an encrypted structural data model to facilitate parallel and encrypted graph data access. It is also designed to decompose complex social search queries into atomic operations and realise them via interchangeable protocols in a fast and scalable manner. We build GraphSE$^2$ with various queries supported in the Facebook graph search engine and implement a full-fledged prototype. Extensive evaluations on Azure Cloud demonstrate that GraphSE$^2$ is practical for querying a social graph with a million of users.Comment: This is the full version of our AsiaCCS paper "GraphSE$^2$: An Encrypted Graph Database for Privacy-Preserving Social Search". It includes the security proof of the proposed scheme. If you want to cite our work, please cite the conference version of i

Strain relaxation in InGaN/GaN micro-pillars evidenced by high resolution cathodoluminescence hyperspectral imaging

A size-dependent strain relaxation and its effects on the optical properties of InGaN/GaN multiple quantum wells (QWs) in micro-pillars have been investigated through a combination of high spatial resolution cathodoluminescence (CL) hyperspectral imaging and numerical modeling. The pillars have diameters (d) ranging from 2 to 150 μm and were fabricated from a III-nitride light-emitting diode (LED) structure optimized for yellow-green emission at ∼560 nm. The CL mapping enables us to investigate strain relaxation in these pillars on a sub-micron scale and to confirm for the first time that a narrow (≤2 μm) edge blue-shift occurs even for the large InGaN/GaN pillars (d > 10 μm). The observed maximum blue-shift at the pillar edge exceeds 7 nm with respect to the pillar centre for the pillars with diameters in the 2–16 μm range. For the smallest pillar (d = 2 μm), the total blue-shift at the edge is 17.5 nm including an 8.2 nm “global” blue-shift at the pillar centre in comparison with the unetched wafer. By using a finite element method with a boundary condition taking account of a strained GaN buffer layer which was neglected in previous simulation works, the strain distribution in the QWs of these pillars was simulated as a function of pillar diameter. The blue-shift in the QWs emission wavelength was then calculated from the strain-dependent changes in piezoelectric field, and the consequent modification of transition energy in the QWs. The simulation and experimental results agree well, confirming the necessity for considering the strained buffer layer in the strain simulation. These results provide not only significant insights into the mechanism of strain relaxation in these micro-pillars but also practical guidance for design of micro/nano LEDs