1,720,967 research outputs found
ConUDA: Confidence-Guided Pseudo-Label Sampling for Unsupervised Domain Adaptation in 3D LiDAR Semantic Segmentation
No full textDense annotation of real 3D LiDAR point clouds for mobile robot applications remains challenging. Unsupervised Domain Adaptation (UDA) enables the segmentation of unlabeled real-world point clouds by leveraging labeled synthetic data. However, existing self-training-based UDA methods rely on fixed thresholds for pseudo-label selection, limiting adaptation performance. In this work, we address this limitation. We propose a novel UDA framework for 3D LiDAR semantic segmentation, centered on a confidence-guided pseudo-label sampling strategy (ConSamp). Specifically, ConSamp adopts a probabilistic sampling strategy in which pseudo-labels with higher confidence are more likely to be retained. Meanwhile, the sampling function itself evolves adaptively throughout training to respond to changes in confidence distribution. Experiments show that our model achieves strong performance on synthetic-to-real 3D LiDAR semantic segmentation tasks. In particular, results better than state-of-the-art methods have been achieved on two public 3D point cloud datasets: SemanticKITTI [1] and SemanticPOSS [2]
Exploiting Local Features and Range Images for Small Data Real-Time Point Cloud Semantic Segmentation
No full textSemantic segmentation of point clouds is an essential task for understanding the environment in autonomous driving and robotics. Recent range-based works achieve real-time efficiency, while point- and voxel-based methods produce better results but are affected by high computational complexity. Moreover, highly complex deep learning models are often not suited to efficiently learn from small datasets. Their generalization capabilities can easily be driven by the abundance of data rather than the architecture design. In this paper, we harness the information from the three-dimensional representation to proficiently capture local features, while introducing the range image representation to incorporate additional information and facilitate fast computation. A GPU-based KDTree allows for rapid building, querying, and enhancing projection with straightforward operations. Extensive experiments on SemanticKITTI and nuScenes datasets demonstrate the benefits of our modification in a "small data"setup, in which only one sequence of the dataset is used to train the models, but also in the conventional setup, where all sequences except one are used for training. We show that a reduced version of our model not only demonstrates strong competitiveness against full-scale state-of-the-art models but also operates in real-time, making it a viable choice for real-world case applications. The code of our method is available at https://github.com/Bender97/WaffleAndRange
Real-time Underwater Place Recognition in Synthetic and Real Environments using Multibeam Sonar and Learning-based Descriptors
No full textOne of the biggest challenges in autonomous underwater navigation is the capability of the autonomous underwater vehicle (AUV) to localize itself, since common positioning systems (e.g., GPS or USBL), when available, can be unstable and very noisy. In this paper, we address the problem of place recognition in underwater synthetic and real environments, which is a key component in autonomous localization for robotics and navigation systems. In underwater scenarios, cameras are often subject to water turbidity and low-light conditions, making their use unreliable. Sonar data on the other hand is not affected by these limitations, but its interpretation is more challenging. In this paper we introduce a global descriptor for multibeam sonar images, to be compared with a database of sonar image descriptors acquired at known locations in sparsely structured environments. To enforce the similarity between descriptors computed from nearby poses, we introduce a novel loss that correlates the oriented-Intersection over Union (o-IoU) between pairs of sonar scans with the corresponding distances between their descriptors. A proxy image reconstruction loss has also been integrated for self-supervised adaptation to real data. Preliminary experimental results show that our method is able to localize an AUV in real-time in both synthetic and real environments by training it for localization using only synthetic sonar images
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
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