Efficient On-the-fly Category Retrieval using ConvNets and GPUs

We investigate the gains in precision and speed, that can be obtained by using Convolutional Networks (ConvNets) for on-the-fly retrieval - where classifiers are learnt at run time for a textual query from downloaded images, and used to rank large image or video datasets. We make three contributions: (i) we present an evaluation of state-of-the-art image representations for object category retrieval over standard benchmark datasets containing 1M+ images; (ii) we show that ConvNets can be used to obtain features which are incredibly performant, and yet much lower dimensional than previous state-of-the-art image representations, and that their dimensionality can be reduced further without loss in performance by compression using product quantization or binarization. Consequently, features with the state-of-the-art performance on large-scale datasets of millions of images can fit in the memory of even a commodity GPU card; (iii) we show that an SVM classifier can be learnt within a ConvNet framework on a GPU in parallel with downloading the new training images, allowing for a continuous refinement of the model as more images become available, and simultaneous training and ranking. The outcome is an on-the-fly system that significantly outperforms its predecessors in terms of: precision of retrieval, memory requirements, and speed, facilitating accurate on-the-fly learning and ranking in under a second on a single GPU.Comment: Published in proceedings of ACCV 201

Surface composition of BaTiO3/SrTiO3(001) films grown by atomic oxygen plasma assisted molecular beam epitaxy

We have investigated the growth of BaTiO3 thin films deposited on pure and 1% Nb-doped SrTiO3(001) single crystals using atomic oxygen assisted molecular beam epitaxy (AO-MBE) and dedicated Ba and Ti Knudsen cells. Thicknesses up to 30 nm were investigated for various layer compositions. We demonstrate 2D growth and epitaxial single crystalline BaTiO3 layers up to 10 nm before additional 3D features appear; lattice parameter relaxation occurs during the first few nanometers and is completed at {\guillemotright}10 nm. The presence of a Ba oxide rich top layer that probably favors 2D growth is evidenced for well crystallized layers. We show that the Ba oxide rich top layer can be removed by chemical etching. The present work stresses the importance of stoichiometry and surface composition of BaTiO3 layers, especially in view of their integration in devices.Comment: In press in J. Appl. Phy

Psoriasis and reverse Koebner response after tattooing

Peer reviewe

Exploring Spatial Correlation for Visual Object Retrieval

2013-2014 > Academic research: refereed > Publication in refereed journa

On the termination of deep-sea fan channels: Examples from the Rhone Fan (Gulf of Lion, Western Mediterranean Sea)

The termination of a deep-sea turbiditic channel represents the ultimate sink of terrigenous sediment in the oceans or lakes. Such environment is characterized by rapid slope decrease and by loss of confinement of turbidity currents. It results in the deposition of Channel-Mouth-Lobes that can be separated from the channel mouth by an erosional (scoured) or by-pass dominated Channel-Lobe Transition Zone. Several factors can control the occurrence, extent and morphologic expression of the area such as the slope break angle, the upslope and downslope angle and the mud/sand ratio in flows. Disentangling these factors remains challenging due to the scarcity of outcrops and to the usual faint morphologies and low thickness of deposits. With bathymetric and seismic data we calculated the morphometric parameters of 8 channel-levees and their Channel-Mouth Lobes from the deepest area of the Rhone fan, a mud-sand rich system, and among which the youngest one (called neofan) was deposited at the end of the Last Glacial Maximum between 21.5 and 18.3 ka cal. BP. Emplacement and shape (finger-shaped or pear-shaped bulges) of Channel-Mouth Lobes is controlled by the seabed morphology (adjacent channel-levees and salt diapirs). A less prominent morphology of the neofan is attributed to premature quiescence related to the post sea-level rise sediment starvation. We show that the occurrence and expression of a Channel-Lobe Transition Zone is controlled by the gradient upstream of the channel mouth slope break. The extended Channel-Lobe Transition Zone and detached lobe of the neofan are attributed to the high upslope gradient (0.26°) while the less detached or attached lobes of other channel-levees is attributed to lower upslope gradient (0.13°). We show that scouring and scours concatenation into flutes at the Channel-Lobe Transition Zone is a major driver for the inception of channels and further confinement of turbidity current. For the first time we show that concatenation of scours in shingled disposition developed an incipient channel sinuosity at this very early stage of channel development. The channel-levee can extend downslope nearly instantaneously by tens of kilometers when isolated nascent channels connect to the channel mouth

The breakdown of the municipality as caring platform: lessons for co-design and co-learning in the age of platform capitalism

If municipalities were the caring platforms of the 19-20th century sharing economy, how does care manifest in civic structures of the current period? We consider how platforms - from the local initiatives of communities transforming neighbourhoods, to the city, in the form of the local authority - are involved, trusted and/or relied on in the design of shared services and amenities for the public good. We use contrasting cases of interaction between local government and civil society organisations in Sweden and the UK to explore trends in public service provision. We look at how care can manifest between state and citizens and at the roles that co-design and co-learning play in developing contextually sensitive opportunities for caring platforms. In this way, we seek to learn from platforms in transition about the importance of co-learning in political and structural contexts and make recommendations for the co-design of (digital) platforms to care with and for civil society

A Graph Based Backtracking Algorithm for Solving General CSPs

Many AI tasks can be formalized as constraint satisfaction problems (CSPs), which involve finding values for variables subject to constraints. While solving a CSP is an NP-complete task in general, tractable classes of CSPs have been identified based on the structure of the underlying constraint graphs. Much effort has been spent on exploiting structural properties of the constraint graph to improve the efficiency of finding a solution. These efforts contributed to development of a class of CSP solving algorithms called decomposition algorithms. The strength of CSP decomposition is that its worst-case complexity depends on the structural properties of the constraint graph and is usually better than the worst-case complexity of search methods. Its practical application is limited, however, since it cannot be applied if the CSP is not decomposable. In this paper, we propose a graph based backtracking algorithm called omega-CDBT, which shares merits and overcomes the weaknesses of both decomposition and search approaches

Chemical Distribution of the Dynamical Ejecta in the Neutron Star Merger GW170817

GW170817 and its associated electromagnetic counterpart AT2017gfo continue to be a treasure trove as observations and modeling continue. Recent precision astrometry of AT2017gfo with the Hubble Space Telescope combined with previous constraints from Very Long Baseline Interferometry (VLBI) constraints narrowed down the inclination angle to 19-25 deg (90\% confidence). This paper explores how the inclusion of precise inclination information can reveal new insights about the ejecta properties, in particular, about the composition of the dynamical ejecta of AT2017gfo. Our analysis relies on updated kilonova modeling, which includes state-of-the-art heating rates, thermalization efficiencies, and opacities and is parameterized by $\bar{Y}_{\rm e,dyn}$, the average electron fraction of the dynamical ejecta component. Using this model, we incorporate the latest inclination angle constraint of AT2017gfo into a light curve fitting framework to derive updated parameter estimates. Our results suggest that the viewing angle of the observer is pointed towards the lanthanide-poor ($Y_{\rm e,dyn}\gtrsim0.25$), squeezed polar dynamical ejecta component, which can explain the early blue emission observed in the light curve of AT2017gfo. In contrast to a recent claim of spherical ejecta powering AT2017gfo, our study indicates that the composition of the dynamical ejecta has a strong angular dependence, with a lanthanide-rich ($Y_{\rm e,dyn}\lesssim0.25$), tidal component distributed around the merger plane with a half-opening angle of $35^\circ$. The inclination angle constraint reduces $\bar{Y}_{\rm e,dyn}$ from $0.24$ to $0.22$, with values $0.17\lesssim Y_{\rm e, dyn} \lesssim0.41$ enabling the robust production of $r$-process elements up to the $3^{\rm rd}$ peak in the tidal dynamical ejecta.Comment: 8 pages, 6 figure