1,721,103 research outputs found
Boosting Generalization in Bio-Signal Classification by Learning the Phase-Amplitude Coupling
No full textVarious hand-crafted features representations of bio-signals rely primarily on the amplitude or power of the signal in specific frequency bands. The phase component is often discarded as it is more sample specific, and thus more sensitive to noise, than the amplitude. However, in general, the phase component also carries information relevant to the underlying biological processes. In fact, in this paper we show the benefits of learning the coupling of both phase and amplitude components of a bio-signal. We do so by introducing a novel self-supervised learning task, which we call Phase-Swap, that detects if bio-signals have been obtained by merging the amplitude and phase from different sources. We show in our evaluation that neural networks trained on this task generalize better across subjects and recording sessions than their fully supervised counterpart
Guest Editorial: Special Issue on Traditional Computer Vision in the Age of Deep Learning
No full text
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
Deep Visual Geo-localization Benchmark
Full text linkIn this paper, we propose a new open-source benchmarking framework for Visual
Geo-localization (VG) that allows to build, train, and test a wide range of
commonly used architectures, with the flexibility to change individual
components of a geo-localization pipeline. The purpose of this framework is
twofold: i) gaining insights into how different components and design choices
in a VG pipeline impact the final results, both in terms of performance
(recall@N metric) and system requirements (such as execution time and memory
consumption); ii) establish a systematic evaluation protocol for comparing
different methods. Using the proposed framework, we perform a large suite of
experiments which provide criteria for choosing backbone, aggregation and
negative mining depending on the use-case and requirements. We also assess the
impact of engineering techniques like pre/post-processing, data augmentation
and image resizing, showing that better performance can be obtained through
somewhat simple procedures: for example, downscaling the images' resolution to
80% can lead to similar results with a 36% savings in extraction time and
dataset storage requirement. Code and trained models are available at
https://deep-vg-bench.herokuapp.com/.Comment: CVPR 2022 (Oral
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
Robust Vision-Based Navigation in Extreme Environments Inspired by the Hippocamal-Entorhinal System
Full text linkTato diplomová práce se zabývá bio-inspirovanou robotickou vizuální navigací a je rozdělena na tři hlavní části. První částí je porovnání navigace zvířat a lidí oproti navigaci v aktuálních robotických systémech a krátké shrnutí výzkumu na téma navigace lidí a zvířat. Druhá část je o novém simulátoru, který jsme navrhli tak, aby v něm výzkumníci mohli rozbíjet aktuální robotické systémy založené na počátačovém vidění. Dále také představujeme novou metodu vyhodnocování navigace jako celku, pomocí navrženého simulátoru. Poslední částí je systém pro vizuální navigaci, mapování a prozkoumávání, spolu s metodou hledání korespondencí mezi více mapami, která pro tyto účely používá geometrii velkých úseků prostředí. Funkcionalitu tohoto systému demonstrujeme na experimentech v simulovaném i reálném prostředí.This thesis deals with bio-inspired monocular visual navigation and is divided into three main parts. First, we survey the research in cognitive neuroscience on human and animal navigation, compare it with the currently best robotic vision-based navigation systems, and identify core strengths of biological navigation which could be worth replicating in robotics. Second, we present a novel simulator that we purpose-build to simulate challenging scenarios and find the limits of existing vision-based systems, which often assume small-scale, static, and unambiguous environments. We also propose a method of evaluating navigation holistically, using the simulator. Third, we present a new vision-based autonomous navigation, map-building and exploration approach. We also show that by using large-scale spatial geometry instead of visual appearance, one can achieve robust multi-session localization even in a highly perceptually aliased environment. Finally, we demonstrate the exploration and safety-aware planning of the designed system both in simulation, and in the real world on an inexpensive unmanned aerial vehicle with limited sensing capabilities
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