Pandora: Description of a Painting Database for Art Movement Recognition with Baselines and Perspectives

To facilitate computer analysis of visual art, in the form of paintings, we introduce Pandora (Paintings Dataset for Recognizing the Art movement) database, a collection of digitized paintings labelled with respect to the artistic movement. Noting that the set of databases available as benchmarks for evaluation is highly reduced and most existing ones are limited in variability and number of images, we propose a novel large scale dataset of digital paintings. The database consists of more than 7700 images from 12 art movements. Each genre is illustrated by a number of images varying from 250 to nearly 1000. We investigate how local and global features and classification systems are able to recognize the art movement. Our experimental results suggest that accurate recognition is achievable by a combination of various categories.To facilitate computer analysis of visual art, in the form of paintings, we introduce Pandora (Paintings Dataset for Recognizing the Art movement) database, a collection of digitized paintings labelled with respect to the artistic movement. Noting that the set of databases available as benchmarks for evaluation is highly reduced and most existing ones are limited in variability and number of images, we propose a novel large scale dataset of digital paintings. The database consists of more than 7700 images from 12 art movements. Each genre is illustrated by a number of images varying from 250 to nearly 1000. We investigate how local and global features and classification systems are able to recognize the art movement. Our experimental results suggest that accurate recognition is achievable by a combination of various categories.Comment: 11 pages, 1 figure, 6 table

Fifth European Dirofilaria and Angiostrongylus Days (FiEDAD) 2016

Peer reviewe

Green Epoxidation of Olefins with ZnxAl/MgxAl-LDH Compounds: Influence of the Chemical Composition

This contribution concerns the effect of the chemical composition of the brucite-type layer of bi-cationic LDH materials ZnxAl and MgxAl (x = 2–5) and tri-cationic LDH MgyZnzAl (y + z = 4, y = 1, 2, 3) on their catalytic activity for olefin epoxidation with H2O2 in the presence of acetonitrile. LDH materials were prepared by the standard method of co-precipitation at constant pH 10, using an aqueous solution of the corresponding metal nitrates and a basic solution containing NaOH and Na2CO3. The fresh LDHs were calcined to yield the corresponding mixed oxides and then the recovery of the LDH structure by hydration of the mixed oxides was performed. The resulting samples were characterized by AAS, XRD, DRIFT, DR-UV–Vis, BET and determination of basic sites. The results of the catalytic tests for olefin epoxidation were well correlated with the basicity of the samples, which was in turn related to the M2+/Al3+ ratio and the electronegativity of different bivalent metals in the brucite-type layer

Making communication a first-class citizen in multicore partitioning

Computation-intensive image processing applications need to be implemented on multicore architectures. If they are to be executed efficiently on such platforms, the underlying data and/or functions should be partitioned and distributed among the processors. The optimal partitioning approach is the one which aims to minimize the inter-processor communication while maximizing the load balance. With the continuously increasing number of cores which exacerbates the demand for more complex memory hierarchies, non-uniform memory access, etc., on-chip communication has gained a significant role in taking advantage of the multicore chips. Therefore, making partitioning decisions just based on conventional performance results and without communication profiling is suboptimal. In this paper, we explore the behavior of a mesh decoder as a case study in terms of communication and computation, and propose models that allow early prediction of the application’s behavior. Using these models, profiling the application for all of the input samples is not necessary anymore. As a result, communication- and computation-aware parallelization could be performed faster and easier

Green Epoxidation of Olefins with Zn_xAl/Mg_xAl-LDH Compounds: Influence of the Chemical Composition

This contribution concerns the effect of the chemical composition of the brucite-type layer of bi-cationic LDH materials ZnxAl and MgxAl (x = 2–5) and tri-cationic LDH MgyZnzAl (y + z = 4, y = 1, 2, 3) on their catalytic activity for olefin epoxidation with H2O2 in the presence of acetonitrile. LDH materials were prepared by the standard method of co-precipitation at constant pH 10, using an aqueous solution of the corresponding metal nitrates and a basic solution containing NaOH and Na2CO3. The fresh LDHs were calcined to yield the corresponding mixed oxides and then the recovery of the LDH structure by hydration of the mixed oxides was performed. The resulting samples were characterized by AAS, XRD, DRIFT, DR-UV–Vis, BET and determination of basic sites. The results of the catalytic tests for olefin epoxidation were well correlated with the basicity of the samples, which was in turn related to the M2+/Al3+ ratio and the electronegativity of different bivalent metals in the brucite-type layer

Efficient depth-aware image deformation adaptation for curved screen displays

The curved screen has attracted considerable attentions in recent years, since it enables to enlarge the view angle and to enhance the immersive perception for users. However, existing curved surface projections are frequently prone to geometric distortion or loss of content. This paper presents a content-aware and depth-aware image adaptation solution for curved displays. An efficient optimization approach of image deformation is proposed to preserve local scene content and to minimize scene geometry distortion. To follow the original 3D perception of objects in different depth layers, the depth information is re-mapped for individual content scaling. Objective evaluation results reveal that our approach can effectively preserve foreground objects. We also perform a subjective evaluation of the proposed solution, and compare it to two alternative mapping methods, which are tested on different curvatures on both a traditional screen and an ad-hoc curvature-controllable curved display. Experimental results demonstrate that our approach outperforms other existing mapping methods for immersive display of rectangle images on curved screens