Abstract

In this work, we aim at understanding semantic interaction among graspable objects in both direct and indirect physical contact for robotic manipulation tasks. Given an object of interest, its support relationship with other graspable objects is inferred hierarchically. The support relationship is used to predict the “support order” or the order in which the surrounding objects need to be removed in order to manipulate the target object. We believe, this can extend the scope of robotic manipulation tasks to typical clutter involving physical contact, overlap and objects of generic shapes and sizes. We have created an RGBD dataset consisting of various objects present in clutter using Kinect. We conducted our experimentation and analysed the performance of our work on the images from the same dataset.

Abstract

Traditional clustering algorithms use a predefined metric and no supervision in identifying the partition. Existing semi-supervised clustering approaches either learn a metric from randomly chosen constraints or actively select informative constraints using a generic distance measure like Euclidean norm. We tackle the problem of identifying constraints that are informative to learn appropriate metric for semi-supervised clustering. We propose an approach to simultaneously find out appropriate constraints and learn a metric to boost the clustering performance. We evaluate clustering quality of our approach using the learned metric on the MNIST handwritten digits, Caltech-256 and MSRC2 object image datasets. Our results on these datasets have significant improvements over the baseline methods like MPCK-MEANS.

Abstract

Labels associated with social images are valuable source of information for tasks of image annotation, understanding and retrieval. These labels are often found to be noisy, mainly due to the collaborative tagging activities of users. Existing methods on annotation have been developed and verified on noise free labels of images. In this paper, we propose a novel and generic framework that exploits the collective knowledge embedded in noisy label co-occurrence pairs to derive robust annotations. We compare our method with a well-known image annotation algorithm and show its superiority in terms of annotation accuracy on benchmark Corel5K and ESP datasets in presence of noisy labels.

Abstract

Commercial applications like driver assistance programs in cars, smile detection softwares in cameras typically require reliable facial landmark points like the location of eyes, lips etc. and face pose at near real-time. Current methods are often unreliable, very cumbersome or computationally intensive. In this work, we focus on implementing a reliable and real-time method which parses an image and detects faces, estimates their pose and locates landmark points on the face. Our method builds on the existing literature. The method can work both for images and videos.

Abstract

The past few years have witnessed the development of non-spherical metal nanoparticles with complex morphologies, which offer tremendous potential in materials science, chemistry, physics and medicine. Covering all important aspects and techniques of preparation and characterization of metal nanoparticles with controlled morphology and architecture, this book provides a sound overview-from the basics right up to recent developments. Renowned research scientists from all over the world present the existing knowledge in the field, covering theory and modeling, synthesis and properties of these nanomaterials. By emphasizing the underlying concepts and principles in detail, this book enables researchers to fully recognize the future research scope and the application potential of the complex-shaped metal nanoparticles, inspiring further research in this field.

Abstract

The relationship between the NMR methyl group axial order parameter and the side chain conformational entropy is investigated in inhibitor-bound and apo human HIV protease using molecular dynamics simulation. Three distinct entropic classes of methyl-bearing side chains, determined by the topological distance of the methyl group from the protein backbone (i.e., the number of χ-bonds between the Cα and the carbon of the CH3 group), are revealed by atomistic trajectory analyses performed in the local frame of reference of individual methyl probes. The results demonstrate that topologically equivalent methyl groups experience similar nonbonded microenvironments regardless of the type of residues to which they are attached. Similarly, methyl groups that belong to the same side chain but that are not topologically equivalent exhibit different thermodynamic and dynamic properties. The two-parameter classification (based upon entropy and methyl axial order parameter) of side chains described here permits improved estimates of the conformational entropies of proteins from NMR motional parameters.

Abstract

Toggle navigation CCSD. HAL: HAL; HALSHS; TEL; MédiHAL; Liste des portails; AURéHAL; API; Data; Documentation. Episciences.org: Episciences.org; Revues; Documentation. Sciencesconf.org; Support. Connexion: Connexion; Connexion avec ORCID; se connecter avec Fédération; Créer un compte; Mot de passe oublié ? Login oublié ? fr; en. HAL - hal.archives-ouvertes.fr. Accueil; Déposer; Consulter: par thème arXiv; Par type de document; Les derniers dépôts; par année de publication; par laboratoire; —————; HAL; TEL; INSPIRE-HEP; ArXiv; CDS - CERN. Rechercher. in2p3-01577700, version 1. Structure, energetics, and dynamics of smectite clay hydration: Molecular dynamics investigations of hectorite” (oral). Christin P. Morrow A. Ozgur Yazaydin 1 Marimuthu Krishnan Geoffrey M. Bowers Andrey G. Kalinichev 2 R. James Kirkpatrick Détails. 1 Department of Chemistry. 2 SUBATECH - Laboratoire

Abstract

Legal judgements are complex in nature and contain cita-tions to other judgements. Research efforts are going on to develop meth-ods for efficient search of relevant legal information by extending the pop-ular approaches used in information retrieval and web searching research areas. In the literature, it was shown that it is possible to find similarjudgements by exploiting citations or links. In this paper, an approachh as been has been proposed using the notion of “paragraph-link” to im-prove the efficiency of link-based similarity method. The experiments on real-world data set and user evaluation study show the encouraging results.

Abstract

Information on web in various languages is growing fast, but large amount of content still exists in English. There are several cases of English text re-use (cross language plagiarism) observed in non-English languages. Detecting text re-use in non-English languages is a challenging task due to complexity of the language used. Complexity further increases for less resource languages like Arabic and Indian languages. In this paper, we address the problem proposed in FIRE CL!TR 2011 task of detecting plagiarized documents in Hindi language which was reused from English language source documents. We proposed three approaches using classification and key-phrase retrieval techniques. Our winning approach attained 0.792 F-measure.

Abstract

This paper presents a novel answer summarization approach for community Question Answering services (cQAs) to address the problem of “incomplete answer”, i.e., missing valuable information from the “best answer” of a complex multi-sentence question, which can be obtained from other answers to the same question. Our method automatically generate a novel and non-redundant summary from cQA answers using structured determinantal point processes (SDPP). Experimental evaluation on sample dataset from Yahoo Answers shows significant improvement over baseline approaches.