1,721,072 research outputs found
A PYRAMIDAL APPROACH FOR DESIGNING DEEP NEURAL NETWORK ARCHITECTURES
Full text linkDeveloping an intelligent system, capable of learning discriminative high-level features from high dimensional data lies at the core of solving many computer vision (CV ) and machine learning (ML) tasks. Scene or human action recognition from videos is an important topic in CV and ML. Its applications include video surveillance, robotics, human-computer interaction, video retrieval, etc. Several bio inspired hand crafted feature extraction systems have been proposed for processing temporal data. However, recent deep learning techniques have dominated CV and ML by their good performance on large scale datasets.
One of the most widely used deep learning technique is Convolutional neural network (CNN) or its variations, e.g. ConvNet, 3DCNN, C3D. CNN kernel scheme reduces the number of parameters with respect to fully connected Neural Networks. Recent deep CNNs have more layers and more kernels for each layer with respect to early CNNs, and as a consequence, they result in a large number of parameters. In addition, they violate the pyramidal plausible architecture of biological neural network due to the increasing number of filters at each higher layer resulting in difficulty for convergence at training step.
In this dissertation, we address three main questions central to pyramidal structure and deep neural networks: 1) Is it worth to utilize pyramidal architecture for proposing a generalized recognition system? 2) How to enhance pyramidal neural network (PyraNet) for recognizing action and dynamic scenes in the videos? 3) What will be the impact of imposing pyramidal structure on a deep CNN?
In the first part of the thesis, we provide a brief review of the work done for action and dynamic scene recognition using traditional computer vision and machine learning approaches. In addition, we give a historical and present overview of pyramidal neural networks and how deep learning emerged. In the second part, we introduce a strictly pyramidal deep architecture for dynamic scene and human action recognition. It is based on the 3DCNN model and the image pyramid concept. We introduce a new 3D weighting scheme that presents a simple connection scheme with lower computational and memory costs and results in less number of learnable parameters compared to other neural networks. 3DPyraNet extracts features from both spatial and temporal dimensions by keeping biological structure, thereby it is capable to capture the motion information encoded in multiple adjacent frames. 3DPyraNet model is extended with three modifications: 1) changing input image size; 2) changing receptive field and overlap size in correlation layers; and 3) adding a linear classifier at the end to classify the learned features. It results in a discriminative approach for spatiotemporal feature learning in action and dynamic scene recognition. In combination with a linear SVM classifier, our model outperforms state-of-the-art methods in one-vs-all accuracy on three video benchmark datasets (KTH, Weizmann, and Maryland). Whereas, it gives competitive accuracy on a 4th dataset (YUPENN).
In the last part of our thesis, we investigate to what extent CNN may take advantage of pyramid structure typical of biological neurons. A generalized statement over convolutional layers from input up-to fully connected layer is introduced that further helps in understanding and designing a successful deep network. It reduces ambiguity, number of parameters, and their size on disk without degrading overall accuracy. It also helps in giving a generalize guideline for modeling a deep architecture by keeping certain ratio of filters in starting layers vs. other deeper layers. Competitive results are achieved compared to similar well-engineered deeper architectures on four benchmark datasets. The same approach is further applied on person re-identification. Less ambiguity in features increase Rank-1 performance and results in better or comparable results to the state-of-the-art deep models
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
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
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
koamabayili/VECTRON-author-checklist: VECTRON author checklist
No full textWe have done our best to complete the author checklist relating to the use of animals in the hut study. Note that the objective for the hut study was to evaluate the IRS treatment applications for residual efficacy against Anopheles mosquitoes, including the local An. coluzzii mosquito population. Cows were only used to attract mosquitoes into the huts and no tests were carried out directly on the cows. The author checklist is intended for use with studies where experiments are carried out on animals, which is why we have had such difficulty in completing this for the hut study, as many of the questions do not relate to how the cows were used
Author-wise bibliometric analysis based on entropy.
No full textAuthor-wise bibliometric analysis based on entropy.</p
Author Under Sail The Imagination of Jack London, 1893-1902
No full textIn Author Under Sail, Jay Williams offers the first complete literary biography of Jack London as a professional writer engaged in the labor of writing. It examines the authorial imagination in London's work, the use of imagination in both his fiction and nonfiction, and the ways he defined imagination in the creative process in his business dealings with his publishers, editors, and agents. In this first volume of a two-volume biography, Williams traverses the years 1893 to 1902, from London's "Story of a Typhoon" to The People of the Abyss. The Jack London who emerges in the pages of Author Under Sail is a writer whose partnership with publishers, most notably his productive alliance with George Brett of Macmillan, was one of the most formative in American literary history. London pioneered many author models during the heyday of realism and naturalism, blurring the boundaries of these popular genres by focusing on absorption and theatricality and the representation of the seen and unseen. London created an impassioned, sincere, and extremely personal realism unlike that of other American writers of the time. Author Under Sail is a literary tour de force that reveals the full range of London as writer, creative citizen, and entrepreneur at the same time it sheds light on the maverick side of machine-age literature.Intro -- Title Page -- Copyright Page -- Dedication -- Contents -- Acknowledgments -- Introduction -- 1. Spirit Truth -- 2. From Absorption to Theatricality and Back Again -- 3. "I Will Build a New Present" -- 4. Sons as Authors -- 5. Fathers as Publishers -- 6. The Daughter as Author -- 7. Lovers as Authors -- 8. At Sea with the Family -- 9. Yellow News, Yellow Stories -- 10. The Return Home -- Notes -- Bibliography -- Index -- About Jay WilliamsIn Author Under Sail, Jay Williams offers the first complete literary biography of Jack London as a professional writer engaged in the labor of writing. It examines the authorial imagination in London's work, the use of imagination in both his fiction and nonfiction, and the ways he defined imagination in the creative process in his business dealings with his publishers, editors, and agents. In this first volume of a two-volume biography, Williams traverses the years 1893 to 1902, from London's "Story of a Typhoon" to The People of the Abyss. The Jack London who emerges in the pages of Author Under Sail is a writer whose partnership with publishers, most notably his productive alliance with George Brett of Macmillan, was one of the most formative in American literary history. London pioneered many author models during the heyday of realism and naturalism, blurring the boundaries of these popular genres by focusing on absorption and theatricality and the representation of the seen and unseen. London created an impassioned, sincere, and extremely personal realism unlike that of other American writers of the time. Author Under Sail is a literary tour de force that reveals the full range of London as writer, creative citizen, and entrepreneur at the same time it sheds light on the maverick side of machine-age literature.Description based on publisher supplied metadata and other sources.Electronic reproduction. Ann Arbor, Michigan : ProQuest Ebook Central, YYYY. Available via World Wide Web. Access may be limited to ProQuest Ebook Central affiliated libraries
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