125,812 research outputs found
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Dispelling the Myths Behind First-author Citation Counts
Full text linkWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
Davallon J., Gramont G. & Schiele B. (Editeurs) (1992). L’environnement entre au musée. Lyon, Presses Universitaires de Lyon
No full textGiordan André. Davallon J., Gramont G. & Schiele B. (Editeurs) (1992). L’environnement entre au musée. Lyon, Presses Universitaires de Lyon. In: Didaskalia, n°1, 1993. p. 142
Integrating representative and discriminative models for object category detection
No full textCategory detection is a lively area of research. While categorization algorithms tend to agree in using local descriptors, they differ in the choice of the classifier, with some using generative models and others discriminative approaches. This paper presents a method for object category detection which integrates a generative model with a discriminative classifier. For each object category, we generate an appearance codebook, which becomes a common vocabulary for the generative and discriminative methods. Given a query image, the generative part of the algorithm finds a set of hypotheses and estimates their support in location and scale. Then, the discriminative part verifies each hypothesis on the same codebook activations. The new algorithm exploits the strengths of both original methods, minimizing their weaknesses. Experiments on several databases show that our new approach performs better than its building blocks taken separately. Moreover, experiments on two challenging multi-scale databases show that our new algorithm outperforms previously reported results
Synopsis iuris Imperii Romano-Germanici
No full textFecha de frontis calc., 1677Marca tip. en portFecha de front. calc., 1677Sign. : []\p1\s, A\p11\s, B-O\p12\s, P\p11\s, Q\p12\s, R\p11\sPort. a dos tintasIndice en alemán y en letra góticaSign.: []¡1, A¡11, B-O¡12, P¡11, Q¡12, R¡11Indice en alemán y en l. gó
Video Segmentation with Superpixels
Full text linkDue to its importance, video segmentation has regained interest recently. However, there is no common agreement about the necessary ingredients for best performance. This work contributes a thorough analysis of various within- and between-frame affinities suitable for video segmentation. Our results show that a frame-based superpixel segmentation combined with a few motion and appearance-based affinities are sufficient to obtain good video segmentation performance. A second contribution of the paper is the extension of [1] to include motion-cues, which makes the algorithm globally aware of motion, thus improving its performance for video sequences. Finally, we contribute an extension of an established image segmentation benchmark [1] to videos, allowing coarse-to-fine video segmentations and multiple human annotations. Our results are tested on BMDS [2], and compared to existing methods
Steven Schiele, Saving the legacy: an oral history of Utah\u27s World War II veterans, ACCN 2070, American West Center, University of Utah
No full textTranscript (39 pages) of an interview by John C. Worsencroft with Steven Schiele on February 22, 2010. From tape number IA-36 in the "Saving the Legacy" Oral History ProjectSchiele (b. 1956) was born in Davenport, Iowa, and lived in Denver, Colorado, Cheyenne, Wyoming and Granger, Utah. Steven talks about his decision to enlist in the Air Force in high school, which was influenced by his brothers\u27 service and seeing a Jimmy Stewart movie called Strategic Air Command when he was young. He discusses basic training where he became a squad leader. After basic training he went to Chanute Air Force Base where he became a general vehicle maintenance mechanic and then reported to Francis E. Warren for three and a half years. He describes his duties and his life with his family at Francis E. Warren. He talks about his decision not to reenlist with the Air Force after serving for four years. After his enlistment with the Air Force, Steven joined the Air National Guard because it allowed him to be closer to planes. He describes his work for the Air National Guard during the eighties were he was deployed to Moron, Spain several times. In the nineties Steven worked as a crew chief and was able to see the world. He describes his deployments to the United Arab Emirates, Italy, and Kosovo. He talks about the conditions and the atmosphere with the locals in Souda Bay, Crete where they were stationed during the Kosovo mission. After this Steven became student flight coordinator in charge of new recruits and then a first sergeant. Interviewed by John C. Worsencroft. 39 pages
Pragmatic Case Studies as a Source of Unity in Applied Psychology
No full textTo unify or not to unify applied psychology: that is the question. In this article we review pendulum swings in the historical efforts to answer this question—from a comprehensive, positivist, “top-down,” deductive yes between the 1930s and the early 60s, to a postmodern no since then. A rationale and proposal for a limited, “bottom-up,” inductive yes in applied psychology is then presented, employing a case-based paradigm that integrates both positivist and postmodern themes and components. This paradigm is labeled “pragmatic psychology” and, its specific use of case studies, the “Pragmatic Case Study Method” (“PCS Method”). We call for the creation of peer-reviewed journal-databases of pragmatic case studies as a foundational source of unifying applied knowledge in our discipline. As one example, the potential of the PCS Method for unifying different angles of theoretical regard is illustrated in an area of applied psychology, psychotherapy, via the case of Mrs. B. The article then turns to the broader historical and epistemological arguments for the unifying nature of the PCS Method in both applied and basic psychology.Peer reviewe
Recommended from our members
Letter to H.B. Stenzel from Donald J. Schiele on 1960-02-09
No full textJackson School of Geoscience
Classifier Based Graph Construction for Video Segmentation
Full text linkVideo segmentation has become an important and active research area with a large diversity of pro-posed approaches. Graph-based methods, enabling top-performance on recent benchmarks, consist of three essen-tial components: 1. powerful features account for object ap-pearance and motion similarities; 2. spatio-temporal neigh-borhoods of pixels or superpixels (the graph edges) are modeled using a combination of those features; 3. video segmentation is formulated as a graph partitioning prob-lem. While a wide variety of features have been explored and various graph partition algorithms have been pro-posed, there is surprisingly little research on how to con-struct a graph to obtain the best video segmentation perfor-mance. This is the focus of our paper. We propose to com-bine features by means of a classifier, use calibrated classi-fier outputs as edge weights and define the graph topology by edge selection. By learning the graph (without changes to the graph partitioning method), we improve the results of the best performing video segmentation algorithm by 6% on the challenging VSB100 benchmark, while reducing its runtime by 55%, as the learnt graph is much sparser
- …
