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BI-LAVA: Biocuration with Hierarchical Image Labeling through Active Learning and Visual Analytics
Andrew Wentzel, G. Elisabeta Marai, Juan Trelles Trabucco September 22, 2024 In the biomedical domain, taxonomies organize the acquisition modalities of scientific images in hierarchical structures. Such taxonomies leverage… Read more |
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Electronic Visualization Laboratory’s 50th Anniversary Retrospective: Look to the Future, Build on the Past
Andrew Johnson, Dana M. Plepys, Daniel J. Sandin, Daria Tsoupikova, G. Elisabeta Marai, Jason Leigh, Jonas Talandis, Lance Long, Luc Renambot, Maxine Brown, Michael E. Papka, Thomas A. DeFanti August 1, 2024 September 2023 marks the 50th anniversary of the Electronic Visualization Laboratory (EVL) at University of Illinois Chicago (UIC). EVL’s… Read more |
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Roses Have Thorns: Understanding the Downside of Oncological Care Delivery Through Visual Analytics and Sequential Rule Mining
Andrew Wentzel, Carla Floricel, G. Elisabeta Marai October 22, 2023 - October 27, 2023 Personalized head and neck cancer therapeutics have greatly improved survival rates for patients, but are often leading to understudied long-lasting… Read more |
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Multi-Organ Spatial Stratification of 3-D Dose Distributions Improves Risk Prediction of Long-Term Self-Reported Severe Symptoms in Oropharyngeal Cancer Patients Receiving Radiotherapy: Development of a Pre-Treatment Decision Support Tool.
Andrew Wentzel, G. Elisabeta Marai July 17, 2023 Recent advances in precision medicine for treating Oropharyngeal cancer (OPC) have led to significant improvements in survival for patients. However… Read more |
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DRAS: Deep Reinforcement Learning for Cluster Scheduling in High Performance Computing
Michael E. Papka December 1, 2022 Cluster schedulers are crucial in high-performance computing (HPC). They determine when and which user jobs should be allocated to available system… Read more |
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Linking scientific instruments and computation: Patterns, technologies, and experiences
Michael E. Papka October 14, 2022 Powerful detectors at modern experimental facilities routinely collect data at multiple GB/s. Online analysis methods are needed to enable the… Read more |
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Moving from Composable to Programmable
Andrew Johnson, Lance Long, Luc Renambot, Maxine Brown, Zhongyi Chen June 3, 2022 In today’s Big Data era, data scientists require modern workflows to quickly analyze large-scale datasets using complex codes to maintain the… Read more |
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Composable Infrastructures for an Academic Research Environment: Lessons Learned
Andrew Johnson, Lance Long, Luc Renambot, Maxine Brown, Zhongyi Chen June 3, 2022 Composable infrastructure holds the promise of accelerating the pace of academic research and discovery by enabling researchers to tailor the… Read more |
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Moving from Composable to Programmable
Andrew Johnson, Lance Long, Luc Renambot, Maxine Brown, Zhongyi Chen April 15, 2022 In today’s Big Data era, data scientists require modern workflows to quickly analyze large-scale datasets using complex codes to maintain the… Read more |
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Composable Infrastructures for an Academic Research Environment: Lessons Learned
Andrew Johnson, Lance Long, Luc Renambot, Maxine Brown, Timothy Bargo April 15, 2022 Composable infrastructure holds the promise of accelerating the pace of academic research and discovery by enabling researchers to tailor the… Read more |
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Exploiting appearance transfer and multi-scale context for efficient person image generation
Wei Tang April 1, 2022 Pose guided person image generation means to generate a photo-realistic person image conditioned on an input person image and a desired pose. This… Read more |
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ANIMO: Annotation of Biomed Image Modalities
G. Elisabeta Marai, Juan Trelles Trabucco December 9, 2021 - December 12, 2021 Figures within biomedical articles present essential evidence of the relevance of a publication in a curation workflow. In particular, visual cues of… Read more |
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Deep learning for mapping element distribution of high-entropy alloys in scanning transmission electron microscopy images
Lance Long September 18, 2021 The latest developments of machine learning (ML) and deep learning (DL) algorithms have paved the way to effectively analyze the atomic structure of… Read more |
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Feature Selection for Support Vector Regression Using a Genetic Algorithm
G. Elisabeta Marai September 8, 2021 Support vector regression (SVR) is particularly beneficial when the outcome and predictors are nonlinearly related. However, when many covariates are… Read more |
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Exploit Visual Dependency Relations for Semantic Segmentation
Wei Tang June 19, 2021 - June 25, 2021 Dependency relations among visual entities are ubiquitous because both objects and scenes are highly structured. They provide prior knowledge about… Read more |
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A digital twin dyad with deep Q-learning in head and neck cancer treatment
Andrew Wentzel, Elisa Tardini, G. Elisabeta Marai June 18, 2021 Each year, over 60,000 people in the United States are diagnosed with head and neck cancers. Treatment strategies are dynamic and complex and can… Read more |
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Recursive meta-Reinforcement Learning for Personalized Sequential Dynamic Treatment Policies
Elisa Tardini May 1, 2021 In recent years deep meta-reinforcement learning has extended the applicability of reinforcement learning (RL) algorithms: by integrating recurrent… Read more |
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Modality-Classification of Microscopy Images Using Shallow Variants of Deep Networks
G. Elisabeta Marai, Juan Trelles Trabucco December 16, 2020 - December 19, 2020 Microscopy images are pervasive in biomedical research publications, where images obtained through various microscopy modalities (light… Read more |
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Learning Global Pose Features in Graph Convolutional Networks for 3D Human Pose Estimation
Wei Tang November 30, 2020 - December 4, 2020 As the human body skeleton can be represented as a sparse graph, it is natural to exploit graph convolutional networks (GCNs) to model the… Read more |
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High-order Graph Convolutional Networks for 3D Human Pose Estimation
Wei Tang September 7, 2020 - September 10, 2020 Graph convolutional networks (GCNs) have been applied to 3D human pose estimation (HPE) from 2D body joint detections and have demonstrated promising… Read more |
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A Comprehensive Study of Weight Sharing in Graph Networks for 3D Human Pose Estimation
Wei Tang August 23, 2020 - August 28, 2020 Graph convolutional networks (GCNs) have been applied to 3D human pose estimation (HPE) from 2D body joint detections and have shown encouraging… Read more |
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Intelligent Assistant for Exploring Data Visualizations
Abhinav Kumar, Andrew Johnson, Jillian Aurisano May 17, 2020 - May 20, 2020 Visualization, while an effective tool for identifying patterns and insights, requires expert knowledge due to challenges faced when translating user… Read more |
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Augmenting Small Data to Classify Contextualized Dialogue Acts for Exploratory Visualization
Abhinav Kumar, Andrew Johnson, Jillian Aurisano May 11, 2020 - May 16, 2020 Our goal is to develop an intelligent assistant to support users explore data via visualizations. We have collected a new corpus of conversations… Read more |
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The Smart Amplified Group Environment
Andrew Burks, Krishna Bharadwaj, Lance Long, Luc Renambot, Maxine Brown April 26, 2020 SAGE2 is a widely known open-source environment for collaborative immersive analytics on large display walls. This paper briefly outlines our… Read more |
