1,721,802 research outputs found
Image and video segmentation with mixture-based semi-supervised clustering
No full textnon disponibileImage segmentation is one of the fundamental problems in Computer Vision, one
that has received countless studies and generated several algorithms and techniques.
Albeit simple to state as a problem, partitioning a digital image into multiple regions is
an open problem as it cannot be objectively formalised, and there really is no general
solution. Thus, general-purpose techniques must be combined with prior knowledge in
order to be effective.
Analysis of video sequences presents even more challenges due to the intertwined
spatial and temporal dimensions, but allows for several interesting inferences about
shapes and motions of consistent regions/objects.
Recently, a lot of attention has been directed towards injecting prior knowledge into
the basic frameworks of probabilistic models in order to “bend” their strong modelling
power towards domain-specific solutions. It is in this context that we see the viability of
semi-supervised clustering, i.e. clustering under the influence of additional information.
In this thesis, we describe an original framework to perform semi-supervised clustering
with probabilistic mixture models. These models are tailored to deal with the
specific nature of images and video sequences in order to be effective and efficient. To
estimate the parameters of the proposed models, we derive a (generalized) EM algorithm
with a closed-form E-step and introduce a novel updates scheme that exploits
the strengths of our particular formulation. We show several experimental results with
known image databases and benchmark video sequences, with quantitative comparisons
to other state-of-the-art techniques where possible and relevant
Social profiling through image understanding: Personality inference using convolutional neural networks
No full textThe role of images in the last ten years has changed radically due to the advent of social networks: from media objects mainly used to communicate visual information, images have become personal, associated with the people that create or interact with them (for example, giving a “like”). Therefore, in the same way that a post reveals something of its author, so now the images associated to a person may embed some of her individual characteristics, such as her personality traits. In this paper, we explore this new level of image understanding with the ultimate goal of relating a set of image preferences to personality traits by using a deep learning framework. In particular, our problem focuses on inferring both self-assessed (how the personality traits of a person can be guessed from her preferred image) and attributed traits (what impressions in terms of personality traits these images trigger in unacquainted people), learning a sort of wisdom of the crowds. Our characterization of each image is locked within the layers of a CNN, allowing us to discover more entangled attributes (aesthetic patterns and semantic information) and to better generalize the patterns that identify a trait. The experimental results show that the proposed method outperforms state-of-the-art results and captures what visually characterizes a certain trait: using a deconvolution strategy we found a clear distinction of features, patterns and content between low and high values in a given trait
Wavelet-based Processing of EEG Data for Brain-Computer Interfaces
No full textBrain-Computer Interfaces based on non-invasive electroencephalographic (EEG) signals were recently made practical through sophisticated algorithms and clever systems, in such a way that the dream of effortlessly translating volition into action is coming true, albeit in a limited way. However, a low signal-to-noise ratio and the presence of frequent artefacts, such as eye blinks, contaminate the recordings and make the recognition of the underlying mental processes difficult. In this study, a novel wavelet-based signal processing technique, Continuous Wavelet Regression, has been applied to refine EEG data in a well-known setting. The recordings of spontaneous (i.e., asynchronous) signals of subjects performing highly different cognitive tasks have been processed by our algorithm, and then analyzed and classified, obtaining very promising results as compared with those obtained by previous studies
Super-resolved Digests of Humans in Video
No full textThis paper describes a hierarchical approach towards the extraction of highly informative summarized information of humans from video sequences. Objects of interest, such as facial features, are detected through transformation-invariant clustering of the frames, iteratively from bigger to smaller regions, and then expressed with an information-rich representation obtained by super-resolution. To guarantee the fundamental constraints under which the super-resolution process is well-behaved, we propose a Bayesian framework that integrates the uncertainties in the registration of the frames. The ultimate product of the overall process is a strip of images that describe at high resolution the dynamics of the video, switching between alternative local descriptions in response to visual changes
Adopting OPC UA for Efficient and Secure Firmware Transmission in Industry 4.0 Scenarios
Get PDFIn the realm of Industry 4.0, the Open Platform Communications Unified Architecture (OPC UA) enables secure and efficient communication among diverse industrial machines. This paper explores the potential of OPC UA, specifically its File Transfer mechanism, for secure inter-company firmware transmission: in particular, we implement a design that authorizes an Automatic Test Equipment (ATE) to download a firmware from a remote server for On-Board Programming (OBP). Our approach harnesses the inherent strengths of the protocol - robust data integrity, encryption, and authentication - to achieve a "secure by design" solution. This enhances firmware transmission and introduces a valuable use case for the OPC UA community, particularly those exploring File Transfer capabilities. We implemented our solution with the open-source OPC UA-.NETStandard library and evaluated it with the OPC UA Exploitation Framework to identify and address potential vulnerabilities. This paper showcases the real-world effectiveness and scalability of the OPC UA File Transfer mechanism, paving the way for secure and efficient collaboration in Industry 4.0
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
Ban dao ti zhong wei qiang zhong tu an xing cheng dong li xue
No full textM.Phil.Stationary Turing patterns can be observed in quantum well microcavities when they are pumped with a normally incident laser. Stable symmetric and asymmetric Turing patterns have been studied in a reduced momentum space model [M. H. Luk et al., Phys. Rev. B 87, 205307 (2013)]. However, some recent studies showed that some of these stable Turing pattens will start to collapse soon after the patterns is formed.In this thesis, we focus our analysis on the stability of different types of patterns formed in a quantum well microcavities pumped by a normally incident laser. In a reduced momentum space model, we show theoretically that oscillating patterns can be formed when the pump intensity reaches certain value. In these oscillating patterns, two interesting features, including the Hopf-bifurcation and the period doubling, could be observed. On the other hand, by using an extended momentum space model, we show how a stationary pattern starts to collapse under certain condition, present a time domain simulation to demonstrate the collapse, and compare the results with the studies on the real-space model.Last, we also study the low intensity all-optical switching, including switching time study and intensity optimization.當激光垂直照射在半導體微腔時，靜止的光學圖案能夠被觀察到。這些穩定的靜止光學圖案，不論是否對稱，都曾在不完整的動量空間被細仔研究過。但在最近的研究指出，一部份這些光學圖案在形成後會開始變得不靜止，甚至整個光學圖案會崩潰。本論文研究了在激光垂直照射半導體微腔情況下，不同光學圖案的穩定性。在不完整的動量空間，我們在理論上展示了當激光的強度達到一定數值時，振動的光學圖案能夠被觀察得到。而這些振動的光學圖案中，我們發現了一些有趣的現像，包括霍普夫分岐和週期倍增。另一方面，在完整的動量空間上，我們展示了在特定的情況下，一個光學圖案怎樣由靜止去到崩潰，當中包括穩定性研究和模擬過程；這些結果會與二維現實空間的模型進行比較。最後，我們還研究了振動的激光強度產生的光學圖案；低強度全光學開關，當中包括開關所需時間和激光強度最優化。Tsang, Chun Yin = 半導體中微腔中圖案形成動力學 / 曾俊彥.Thesis M.Phil. Chinese University of Hong Kong 2017.Includes bibliographical references (leaves 120-123).Abstracts also in Chinese.Title from PDF title page (viewed on 10, February, 2020).Tsang, Chun Yin = Ban dao ti zhong wei qiang zhong tu an xing cheng dong li xue / Zeng Junyan
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