1,720,984 research outputs found
On problems and computational imaging solutions for ptychography
No full textPtychography is a modern microscopy technique still in development within the broader family of Coherent Diffraction Imaging (CDI) based methods. They have the potential to revolutionize the study of multiple scientific fields by providing higher resolutions of larger areas at faster speeds including chemical speciation. Its principle is that a beam of coherent light is shined onto a sample in a scanning fashion and the acquired diffraction patterns are computationally merged to recreate the whole specimen's complex image.
This research is multidisciplinary; with pivotal point in electronic/computer engineering it solves problems in this modern computational imaging technique, which is used in applied physics, with applications in fields such as electrochemistry, biology, nanomaterials and other disciplines that benefit from microscopy. Based on recent advances in Artificial Intelligence, this research makes use of Machine Learning and Optimisation methods for solving certain problems.
The results of this research provided solutions to various problems of ptychography, improving the technique. Moreover, the thesis delivers an implementation of the proposed solutions as a complete software framework based on modern engineering paradigms such as GPU computing.
The development of this work is based on an actual laboratory that implements ptychography. This laboratory is the X-ray spectromicroscopy beamline TwinMic at the synchrotron radiation facility Elettra Sincrotrone Trieste, in collaboration with its Scientific Computing group. The thesis also contains the result of two beamtime experiments and discusses the proposals of an additional 2 that are already granted.
The main contributions of this research range over the topic of spatial coherence, positions refinement, and parameters tuning.
Partial coherence of the source deteriorates the images that can be reconstructed: we proposed a refined reconstruction algorithm (M-RPIE) where the large computational field of view of the method allows for a sparser scanning.
Position errors impact negatively ptychography, thus a part of the research was devoted to providing a solution. This led to: a metric based approach; an analysis of the dynamics of the error signal; a method for the automatic control of the position feedback gain; a method to include position refinement coefficients within an optimisation process
Ptychography requires a multitude of parameters which currently are manually tuned. Using advanced Deep Learning techniques, we proposed a reconstruction algorithm which automatically regresses the propagation distance and the position correction coefficients within an optimisation-based process.
Fourier ptychography was also explored and implemented in the software framework. We proposed a CNN model for the generation of a prior which can be effectively used to seed the reconstruction.
Since the research is multidisciplinary, certain results were utilised in other fields such as X-ray Fluorescence, Computed Tomography , super-resolution for forensics, CNNs for face recognition and depth estimation.Ptychography is a modern microscopy technique still in development within the broader family of Coherent Diffraction Imaging (CDI) based methods. They have the potential to revolutionize the study of multiple scientific fields by providing higher resolutions of larger areas at faster speeds including chemical speciation. Its principle is that a beam of coherent light is shined onto a sample in a scanning fashion and the acquired diffraction patterns are computationally merged to recreate the whole specimen's complex image.
This research is multidisciplinary; with pivotal point in electronic/computer engineering it solves problems in this modern computational imaging technique, which is used in applied physics, with applications in fields such as electrochemistry, biology, nanomaterials and other disciplines that benefit from microscopy. Based on recent advances in Artificial Intelligence, this research makes use of Machine Learning and Optimisation methods for solving certain problems.
The results of this research provided solutions to various problems of ptychography, improving the technique. Moreover, the thesis delivers an implementation of the proposed solutions as a complete software framework based on modern engineering paradigms such as GPU computing.
The development of this work is based on an actual laboratory that implements ptychography. This laboratory is the X-ray spectromicroscopy beamline TwinMic at the synchrotron radiation facility Elettra Sincrotrone Trieste, in collaboration with its Scientific Computing group. The thesis also contains the result of two beamtime experiments and discusses the proposals of an additional 2 that are already granted.
The main contributions of this research range over the topic of spatial coherence, positions refinement, and parameters tuning.
Partial coherence of the source deteriorates the images that can be reconstructed: we proposed a refined reconstruction algorithm (M-RPIE) where the large computational field of view of the method allows for a sparser scanning.
Position errors impact negatively ptychography, thus a part of the research was devoted to providing a solution. This led to: a metric based approach; an analysis of the dynamics of the error signal; a method for the automatic control of the position feedback gain; a method to include position refinement coefficients within an optimisation process
Ptychography requires a multitude of parameters which currently are manually tuned. Using advanced Deep Learning techniques, we proposed a reconstruction algorithm which automatically regresses the propagation distance and the position correction coefficients within an optimisation-based process.
Fourier ptychography was also explored and implemented in the software framework. We proposed a CNN model for the generation of a prior which can be effectively used to seed the reconstruction.
Since the research is multidisciplinary, certain results where utilised in other fields such as X-ray Fluorescence, Computed Tomography , super-resolution for forensics, CNNs for face recognition and depth estimation
Perspective registration and multi-frame super-resolution of license plates in surveillance videos
No full textOne task often encountered in surveillance videos is the recognition of a target—e.g. the license plate of a vehicle. Often, the quality of a single video frame does not permit a reliable recognition. If multiple frames are available, it is possible to combine them in order to generate a single image with lower noise (frame averaging) and/or higher resolution (super-resolution). In order for these techniques to work, it is necessary to accurately estimate the motion of the object of interest in the recorded footage. In this paper, we introduce a method capable of accurately computing the perspective transformation that describes the motion of a planar object. The method minimizes the squared distance between the transformed image and a reference, computed over a user-defined region of interest, and uses the partial derivatives in order to significantly speed up the computation. This approach is inspired by the well known Kanade–Lucas–Tomasi feature tracker
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
A Parameter Refinement Method for Ptychography Based on Deep Learning Concepts
Full text linkX-ray ptychography is an advanced computational microscopy technique, which is delivering exceptionally detailed quantitative imaging of biological and nanotechnology specimens, which can be used for high-precision X-ray measurements. However, coarse parametrisation in propagation distance, position errors and partial coherence frequently threaten the experimental viability. In this work, we formally introduce these actors, solving the whole reconstruction as an optimisation problem. A modern deep learning framework was used to autonomously correct the setup incoherences, thus improving the quality of a ptychography reconstruction. Automatic procedures are indeed crucial to reduce the time for a reliable analysis, which has a significant impact on all the fields that use this kind of microscopy. We implemented our algorithm in our software framework, SciComPty, releasing it as open-source. We tested our system on both synthetic datasets, as well as on real data acquired at the TwinMic beamline of the Elettra synchrotron facility
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
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