1,720,974 research outputs found
Toward Robust Multimodal Egocentric Video Understanding
No full textEgocentric, or first-person, video offers a powerful medium for capturing and understanding natural human behavior in real-world environments. With the growing availability of wearable cameras and multimodal sensors, there is increasing interest in developing intelligent systems that can process, localize, and interpret activities from this unique perspective. However, egocentric video understanding presents fundamental challenges: videos are often long and unstructured, captured in diverse and dynamic scenes, and rich in sensory signals that may be noisy, incomplete, or constrained by real-world limitations such as privacy and power.
This thesis explores key problems in egocentric video understanding through the lens of multimodal learning, large-scale dataset curation, and robust modeling techniques for deployment under real-world constraints. It comprises four core contributions. First, we propose OWL, a method that integrates audiovisual temporal context to improve action localization in egocentric video, demonstrating significant performance gains on two large-scale datasets. Second, we document contributions to the creation of two landmark datasets, Ego4D and Ego-Exo4D, that enable scalable benchmarking of first-person perception tasks, including efforts in diverse data collection and energy-efficient activity recognition. Third, we address the practical issue of missing modalities in multimodal learning by introducing the Missing Modality Token (MMT), a transformer-compatible mechanism that allows robust inference even when inputs are partially absent. Finally, we present MiDl, a self-supervised, online test-time adaptation framework that dynamically adapts to modality incompleteness without requiring retraining or labeled data.
Together, these contributions advance the field of egocentric video understanding across both algorithmic and infrastructural dimensions. This work lays the foundation for building perception systems that are not only accurate and multimodally rich, but also scalable, resilient, and ready for deployment in the wild
SeedQuant: A Deep Learning-based Census Tool for Seed Germination of Root Parasitic Plants
No full textWitchweeds and broomrapes are root parasitic weeds that represent one of the main threats to global food security. By drastically reducing host crops’ yield, the parasites are often responsible for enormous economic losses estimated in billions of dollars annually. Parasitic plants rely on a chemical cue in the rhizosphere, indicating the presence of a host plant in proximity. Using this host dependency, research in parasitic plants focuses on understanding the necessary triggers for parasitic seeds germination, to either reduce their germination in presence of crops or provoke germination without hosts (i.e. suicidal germination). For this purpose, a number of synthetic analogs and inhibitors have been developed and their biological activities studied on parasitic plants around the world using various protocols. Current studies are using germination-based bioassays, where pre-conditioned parasitic seeds are placed in the presence of a chemical or plant root exudates, from which the germination ratio is assessed. Although these protocols are very sensitive at the chemical level, the germination rate recording is time consuming, represents a challenging task for researchers, and could easily be sped up leveraging automated seeds detection algorithms. In order to accelerate such protocols, we propose an automatic seed censing tool using computer vision latest development. We use a deep learning approach for object detection with the algorithm Faster R-CNN to count and discriminate germinated from non-germinated seeds. Our method has shown an accuracy of 95% in counting seeds on completely new images, and reduces the counting time by a significant margin, from 5 min to a fraction of second per image. We believe our proposed software 5 “SeedQuant” will be of great help for lab bioassays to perform large scale chemicals screening for parasitic seeds applications
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe 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
Get PDF“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
Get PDFWe 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
Get PDFWe 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
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