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Articles 1 - 10 of 10
Full-Text Articles in Physical Sciences and Mathematics
Identifying Regional Trends In Avatar Customization, Peter Mawhorter, Sercan Sengun, Haewoon Kwak, D. Fox Harrell
Identifying Regional Trends In Avatar Customization, Peter Mawhorter, Sercan Sengun, Haewoon Kwak, D. Fox Harrell
Research Collection School Of Computing and Information Systems
Since virtual identities such as social media profiles and avatars have become a common venue for self-expression, it has become important to consider the ways in which existing systems embed the values of their designers. In order to design virtual identity systems that reflect the needs and preferences of diverse users, understanding how the virtual identity construction differs between groups is important. This paper presents a new methodology that leverages deep learning and differential clustering for comparative analysis of profile images, with a case study of almost 100 000 avatars from a large online community using a popular avatar creation …
Erratum: "Imaging The Three‐Dimensional Orientation And Rotational Mobility Of Fluorescent Emitters Using The Tri‐Spot Point Spread Function", Oumeng Zhang, Jin Lu, Tianben Ding, Matthew D. Lew
Erratum: "Imaging The Three‐Dimensional Orientation And Rotational Mobility Of Fluorescent Emitters Using The Tri‐Spot Point Spread Function", Oumeng Zhang, Jin Lu, Tianben Ding, Matthew D. Lew
Electrical & Systems Engineering Publications and Presentations
In the original paper, a calibration error exists in the image-formation model used to analyze experimental images taken by our microscope, causing a bias in the orientation measurements in Figs. 2 and 3. The updated measurements are shown in Fig. E1. We have also updated the supplementary material for the original article to discuss the revised PSF model and estimation algorithms (supplementary material 2) and show the revised model and measurements (Figs. S1, S3, S7, S8, and S10–S13).
Multiwavelength Digital Holographic Imaging And Phase Unwrapping Of Protozoa Using Custom Fiji Plug-Ins, David Cohoe, Iulia Hanczarek, J. Kent Wallace, Jay Nadeau
Multiwavelength Digital Holographic Imaging And Phase Unwrapping Of Protozoa Using Custom Fiji Plug-Ins, David Cohoe, Iulia Hanczarek, J. Kent Wallace, Jay Nadeau
Physics Faculty Publications and Presentations
Multiwavelength digital holographic microscopy (DHM) has been used to improve phase reconstructions of digital holograms by reducing 2p phase ambiguities. However, most samples used as test images have been solid or adhered to a surface, making it easy to determine focal planes and correct for chromatic aberration. In this study we apply 3-wavelength off-axis DHM to swimming protozoa containing distinct spectral features such as chlorophyll and carotenoids. We reconstruct the holograms into amplitude and phase images using the angular spectrum method. Methods for noise subtraction, chromatic aberration correction, and image registration are presented for both amplitude and phase. Approaches to …
Low-Energy Acceleration Of Binarized Convolutional Neural Networks Using A Spin Hall Effect Based Logic-In-Memory Architecture, Ashkan Samiee, Payal Borulkar, Ronald F. Demara, Peiyi Zhao, Yu Bai
Low-Energy Acceleration Of Binarized Convolutional Neural Networks Using A Spin Hall Effect Based Logic-In-Memory Architecture, Ashkan Samiee, Payal Borulkar, Ronald F. Demara, Peiyi Zhao, Yu Bai
Engineering Faculty Articles and Research
Deep Learning (DL) offers the advantages of high accuracy performance at tasks such as image recognition, learning of complex intelligent behaviors, and large-scale information retrieval problems such as intelligent web search. To attain the benefits of DL, the high computational and energy-consumption demands imposed by the underlying processing, interconnect, and memory devices on which software-based DL executes can benefit substantially from innovative hardware implementations. Logic-in-Memory (LIM) architectures offer potential approaches to attaining such throughput goals within area and energy constraints starting with the lowest layers of the hardware stack. In this paper, we develop a Spintronic Logic-in-Memory (S-LIM) XNOR neural …
Seeing Eye To Eye: A Machine Learning Approach To Automated Saccade Analysis, Maigh Attre
Seeing Eye To Eye: A Machine Learning Approach To Automated Saccade Analysis, Maigh Attre
Honors Scholar Theses
Abnormal ocular motility is a common manifestation of many underlying pathologies particularly those that are neurological. Dynamics of saccades, when the eye rapidly changes its point of fixation, have been characterized for many neurological disorders including concussions, traumatic brain injuries (TBI), and Parkinson’s disease. However, widespread saccade analysis for diagnostic and research purposes requires the recognition of certain eye movement parameters. Key information such as velocity and duration must be determined from data based on a wide set of patients’ characteristics that may range in eye shapes and iris, hair and skin pigmentation [36]. Previous work on saccade analysis has …
Image Processing Algorithms For Elastin Lamellae Inside Cardiovascular Arteries, Mahmoud Habibnezhad
Image Processing Algorithms For Elastin Lamellae Inside Cardiovascular Arteries, Mahmoud Habibnezhad
Department of Computer Science and Engineering: Dissertations, Theses, and Student Research
Automated image processing methods are greatly needed to replace the tedious, manual histology analysis still performed by many physicians. This thesis focuses on pathological studies that express the essential role of elastin lamella in the resilience and elastic properties of the arterial blood vessels. Due to the stochastic nature of the shape and distribution of the elastin layers, their morphological features appear as the best candidates to develop a mathematical formulation for the resistance behavior of elastic tissues. However, even for trained physicians and their assistants, the current measurement procedures are highly error-prone and prolonged. This thesis successfully integrates such …
Integrated Database System With Spatial Information For Disaster Risk Management, Ever Enrique Castillo Osorio, Bashir Hayat, Babar Shah, Francis Chow, Ki Il Kim
Integrated Database System With Spatial Information For Disaster Risk Management, Ever Enrique Castillo Osorio, Bashir Hayat, Babar Shah, Francis Chow, Ki Il Kim
All Works
© 2019 AECE. Despite availability of various image sources for specific areas, a new disaster management system is likely to be implemented by using only one of them. Thus, its applicability and extensibility are severely limited. In addition, real-time update for the disaster area is one of the crucial functions for search and rescue activities. To meet the aforementioned requirements, in this paper, we propose a new spatial data infrastructure by defining the methodological scheme for the raster information. The proposed system has four respective layers to reduce the management cost as well as provide a flexible architecture. In each …
Work-In-Progress Reports Submitted To The Library Of Congress As Part Of Digital Libraries, Intelligent Data Analytics, And Augmented Description, Chulwoo Pack, Yi Liu, Leen-Kiat Soh, Elizabeth Lorang
Work-In-Progress Reports Submitted To The Library Of Congress As Part Of Digital Libraries, Intelligent Data Analytics, And Augmented Description, Chulwoo Pack, Yi Liu, Leen-Kiat Soh, Elizabeth Lorang
CSE Technical Reports
This document includes work-in-progress reports submitted to the Library of Congress as part of the Aida digital libraries research team's work on Digital Libraries, Intelligent Data Analytics, and Augmented Description: A Demonstration Project. These work-in-progress reports provide a snapshot glimpse, as well as underlying rationale and decision-making, at various points in the development of the project and its machine learning explorations. Reports cover explorations on historic newspapers, minimally-processed manuscript collections, materials digitized from physical originals and those digitized from microform surrogates, and investigate challenges related to image segmentation and document zoning, classification, document image quality analysis, metadata generation, and more.
Automatic Detection And Analysis Of Rip Currents At Haeundae Beach Using X-Band Marine Radar, Chanyeong Oh, Kyungmo Ahn, Se-Hyeon Cheon
Automatic Detection And Analysis Of Rip Currents At Haeundae Beach Using X-Band Marine Radar, Chanyeong Oh, Kyungmo Ahn, Se-Hyeon Cheon
OES Faculty Publications
The observation system has been developed to investigate the rip currents at Haeundae beach using Xband marine radar. X-band radar system can observe shape, size, and velocity of rip currents, which is difficult to obtain through field observation by conventional device. Algorithms which automatically detect locations, shapes, and magnitudes of rip currents were developed using time averaged X-band radar sea clutter images. X-band sea clutter images are transformed through 3D FFT into 2D wave number spectrum and frequency spectrum. Rip current velocities were estimated using differences in wave-number spectra and wave frequency spectra due to Doppler shift. The algorithm was …
Design Of A Hybrid Measure For Image Similarity: A Statistical, Algebraic, And Information-Theoretic Approach, Mohammed Abdulameer Aljanabi, Zahir M. Hussain, Noor Abd Alrazak Shnain, Song Feng Lu
Design Of A Hybrid Measure For Image Similarity: A Statistical, Algebraic, And Information-Theoretic Approach, Mohammed Abdulameer Aljanabi, Zahir M. Hussain, Noor Abd Alrazak Shnain, Song Feng Lu
Research outputs 2014 to 2021
Image similarity or distortion assessment is fundamental to a wide range of applications throughout the field of image processing and computer vision. Many image similarity measures have been proposed to treat specific types of image distortions. Most of these measures are based on statistical approaches, such as the classic SSIM. In this paper, we present a different approach by interpolating the information theory with the statistic, because the information theory has a high capability to predict the relationship among image intensity values. Our unique hybrid approach incorporates information theory (Shannon entropy) with a statistic (SSIM), as well as a distinctive …