Article
Chemistry, Multidisciplinary
Lichi An, Jiabao Li, Yabing Cheng, Yongkang Yu, Xingchen Gu
Summary: In this study, the difference between the meshing of the chain-sprocket and the meshing of the rack-gear in a hybrid vehicle's transmission system was analyzed. By rigidifying the external meshing Hy-Vo chain as a rack, the fluctuation range of the pitch line of the external meshing Hy-Vo chain was analyzed. A design method for the internal-external composite meshing Hy-Vo chain was deduced, and its effectiveness and feasibility were proven through experiments. The study also showed that the description of the internal-external composite meshing in the classical meshing theory is not completely correct.
APPLIED SCIENCES-BASEL
(2023)
Article
Computer Science, Interdisciplinary Applications
Christos Georgiadis, Maxence Reberol, Jean-Francois Remacle
Summary: The pipeline presented in the article focuses on generating quadrilateral meshes on complex geometries, with advantages including reduced element count and alignment with a given direction field. The approach efficiently handles non-manifold feature edges and small features, ultimately producing globally aligned quadrilateral meshes.
ENGINEERING WITH COMPUTERS
(2022)
Article
Computer Science, Software Engineering
Benjamin Jones, Yuxuan Mei, Haisen Zhao, Taylor Gotfrid, Jennifer Mankoff, Adriana Schulz
Summary: We propose an interactive design system for knitting that enables users to create patterns using an industrial knitting machine. Our system allows direct control of key design parameters and ensures consistency and knittability. We demonstrate the effectiveness of our approach through a series of examples.
ACM TRANSACTIONS ON GRAPHICS
(2022)
Article
Computer Science, Software Engineering
Lin-Ping Yuan, Wei Zeng, Siwei Fu, Zhiliang Zeng, Haotian Li, Chi-Wing Fu, Huamin Qu
Summary: This article presents a new approach based on deep learning to automatically extract colormaps from visualizations. The method summarizes colors in an input visualization image and uses a pre-trained deep neural network to predict the colormap. The approach performs well on both synthetic and real-world visualizations.
IEEE TRANSACTIONS ON VISUALIZATION AND COMPUTER GRAPHICS
(2022)
Article
Computer Science, Software Engineering
Marco Livesu, Luca Pitzalis, Gianmarco Cherchi
Summary: This article studies the dual approach in hexahedral mesh generation and proposes four main contributions: enumerating all possible transitions, demonstrating the internal asymmetry of schemes, exploring the combinatorial space of dual schemes, and expanding the class of adaptive grids. Extensive experiments show the superiority of their transition schemes compared to prior art.
ACM TRANSACTIONS ON GRAPHICS
(2022)
Article
Computer Science, Software Engineering
Eytan Adar, Elsie Lee
Summary: The research discusses the evaluation languages used in communicative visualizations and how using a learning lens can improve the design and assessment of visualizations.
IEEE TRANSACTIONS ON VISUALIZATION AND COMPUTER GRAPHICS
(2021)
Article
Computer Science, Software Engineering
Lingxiao Li, Paul Zhang, Dmitriy Smirnov, S. Mazdak Abulnaga, Justin Solomon
Summary: This work presents an interactive hex meshing pipeline that sidesteps the challenge of maintaining the bijectivity of PolyCube deformation by using a new representation of PolyCubes as unions of cuboids. Users have extensive control over each stage of the process, including automatic alternatives. A user study showed that participants prefer hex meshes generated using this tool.
ACM TRANSACTIONS ON GRAPHICS
(2021)
Article
Mathematics, Interdisciplinary Applications
Demetris Avraam, Rebecca Wilson, Oliver Butters, Thomas Burton, Christos Nicolaides, Elinor Jones, Andy Boyd, Paul Burton
Summary: Data visualizations are valuable tools that graphically reveal information about data structures, properties, and relationships between variables. However, in sensitive fields like medicine and social sciences, restrictions are placed on sharing individual-level records to protect privacy. Anonymization techniques such as k-anonymization and probabilistic perturbation can be used to generate privacy-preserving visualizations while adhering to data protection laws. These methods allow for exploration and inferential analysis while maintaining data confidentiality.
Article
Engineering, Mechanical
Xin Zhao, Yaping Zhao, Gongfa Li
Summary: According to the definition, the straight sided normal profile helicoid is established and it is proven that its normal section is a straight line and the cross-section is an extended involute. The calculation formula for the guide cylinder radius under different installation modes of ZN-type worm is derived. The meshing limit line equation of uniform speed vertical staggered shaft drive is derived and simplified. The meshing equation and the meshing limit line equation of ZN-type worm drive are derived. Through theoretical calculation, it is verified that the meshing limit line is an inherent characteristic of ZN-type worm pair and cannot be eliminated by modifying parameters. The meshing limit line is solved and some conclusions are drawn. The numerical results show that the meshing limit line exists on the worm tooth surface, dividing the contact area into effective and ineffective parts, and the conjugate line of the meshing limit line is located in the middle of the worm gear tooth surface.
PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART C-JOURNAL OF MECHANICAL ENGINEERING SCIENCE
(2023)
Article
Engineering, Mechanical
Yang Zhang, Lingyun Zhu, Xiangfeng Gou
Summary: The tooth strength of spiral bevel gear is compromised due to reduced tooth thickness along the cone distance. This paper presents a mathematical model that accurately describes the meshing characteristics and basic parameters of the gear. It analyzes the multi-state meshing and stress condition by dividing the tooth surface into different regions. It also proposes methods for calculating the load distribution ratio and identifies excitations from the varying length of the contact line.
INTERNATIONAL JOURNAL OF MECHANICAL SCIENCES
(2023)
Article
Computer Science, Software Engineering
Alex Kale, Yifan Wu, Jessica Hultman
Summary: Analysts often make visual causal inferences about possible data-generating models. However, visual analytics (VA) software tends to leave these models implicit in the mind of the analyst, which casts doubt on the statistical validity of informal visual insights. We formally evaluate the quality of causal inferences from visualizations by adopting causal support-a Bayesian cognition model that learns the probability of alternative causal explanations given some data-as a normative benchmark for causal inferences. We contribute two experiments assessing how well crowdworkers can detect (1) a treatment effect and (2) a confounding relationship. We find that chart users' causal inferences tend to be insensitive to sample size such that they deviate from our normative benchmark. While interactively cross-filtering data in visualizations can improve sensitivity, on average users do not perform reliably better with common visualizations than they do with textual contingency tables. These experiments demonstrate the utility of causal support as an evaluation framework for inferences in VA and point to opportunities to make analysts' mental models more explicit in VA software.
IEEE TRANSACTIONS ON VISUALIZATION AND COMPUTER GRAPHICS
(2022)
Article
Computer Science, Software Engineering
Jude T. Anderson, David M. Williams, Andrew Corrigan
Summary: A novel method is introduced for constructing 2D surface meshes in 3D space time and 3D hypersurface meshes in 4D space time. The time-space domain is divided into time slabs, each equipped with an initial plane or hyperplane and an unstructured simplicial surface or hypersurface mesh. The vertices of the terminating plane or hyperplane are obtained from the vertices of the initial plane using a space-time trajectory tracking approach. The validity and flexibility of this method are demonstrated through multiple numerical experiments.
COMPUTER-AIDED DESIGN
(2023)
Article
Computer Science, Software Engineering
Zoltan Csati, Jean-Francois Witz, Vincent Magnier, Ahmed El Bartali, Nathalie Limodin, Denis Najjar
Summary: This paper presents an automated approach for creating high-quality finite element meshes for polycrystalline microstructures, using image segmentation techniques to obtain grains and convert them to CAD geometry. Existing meshing software can then be used to create a high-quality mesh automatically.
Article
Computer Science, Software Engineering
Jonathan Zong, Dhiraj Barnwal, Rupayan Neogy, Arvind Satyanarayan
Summary: Lyra 2 extends a visualization design environment with methods for authoring interaction techniques by demonstration, allowing users to directly interact with visualizations and receive suggestions for interaction design, ultimately enabling rapid creation of diverse interactive visualizations.
IEEE TRANSACTIONS ON VISUALIZATION AND COMPUTER GRAPHICS
(2021)
Article
Engineering, Mechanical
Kun Yue, Zhong Kang, Mengjie Zhang, Liming Wang, Yimin Shao, Zaigang Chen
Summary: An improved gear meshing power loss calculation method is proposed in this paper to consider the coupling effects between gear friction and dynamic characteristics. A six degrees-of-freedom gear dynamic model and power loss iteration calculation process are established, and the effects of gear surface quality and loads on power loss are analyzed. Experimental results show that this method is in better agreement with the experimental results compared to the traditional method.
TRIBOLOGY INTERNATIONAL
(2023)
Article
Computer Science, Interdisciplinary Applications
Brian Matejek, Tim Franzmeyer, Donglai Wei, Xueying Wang, Jinglin Zhao, Kalman Palagyi, Jeff W. Lichtman, Hanspeter Pfister
Summary: A novel topological thinning strategy utilizing biological constraints is proposed for accurate skeleton generation from segmented neuronal volumes; a Convolutional Neural Network (CNN) is used to detect cell bodies and improve anchoring accuracy of the skeletons; an synapse-aware topological thinning approach is employed to produce expressive neuron skeletons.
IEEE TRANSACTIONS ON MEDICAL IMAGING
(2022)
Article
Computer Science, Software Engineering
Weikai Yang, Xi Ye, Xingxing Zhang, Lanxi Xiao, Jiazhi Xia, Zhongyuan Wang, Jun Zhu, Hanspeter Pfister, Shixia Liu
Summary: In this paper, we propose a visual analysis method called FSLDiagnotor to address the issue of unsatisfactory performance in ensemble few-shot classifiers. We formulate the problem as sparse subset selection and develop two algorithms to recommend appropriate base learners and shots. The recommended results are explained and adjusted using matrix visualization and scatterplot. Two case studies demonstrate the effectiveness of FSLDiagnotor in building few-shot classifiers with improved accuracy.
IEEE TRANSACTIONS ON VISUALIZATION AND COMPUTER GRAPHICS
(2022)
Article
Multidisciplinary Sciences
Jiajun Deng, Jiancheng Yang, Likun Hou, Junqi Wu, Yi He, Mengmeng Zhao, Bingbing Ni, Donglai Wei, Hanspeter Pfister, Caicun Zhou, Tao Jiang, Yunlang She, Chunyan Wu, Chang Chen
Summary: We proposed a biomarker system called PITER that utilizes histopathological and genetic characteristics to identify candidates for immunotherapy and has shown potential in identifying lung adenocarcinoma patients with a good response to treatment.
Article
Computer Science, Software Engineering
Tica Lin, Zhutian Chen, Johanna Beyer, Yingcai Wu, Hanspeter Pfister, Yalong F. Yang
Summary: Most sports visualizations face challenges due to the combination of spatial, highly temporal, and user-centric data. The emergence of augmented and mixed reality technologies has brought exciting opportunities and new challenges for sports visualization. This article discusses the lessons learned from working with sports domain experts and designing sports visualizations with AR/XR technologies. The unique design constraints and requirements of different user groups in sports are highlighted, along with the potential benefits of sports visualization research for the larger visualization community.
IEEE COMPUTER GRAPHICS AND APPLICATIONS
(2023)
Article
Multidisciplinary Sciences
Jiancheng Yang, Rui Shi, Donglai Wei, Zequan Liu, Lin Zhao, Bilian Ke, Hanspeter Pfister, Bingbing Ni
Summary: We introduce MedMNIST v2, a large-scale dataset collection of standardized biomedical images with 12 datasets for 2D and 6 datasets for 3D. The dataset covers primary data modalities in biomedical images and is designed for lightweight classification tasks. It consists of 708,069 2D images and 9,998 3D images and can support various research purposes in biomedical image analysis, computer vision, and machine learning. We benchmarked baseline methods on MedMNIST v2, including neural networks and AutoML tools.
Article
Biology
Clarence Yapp, Edward Novikov, Won-Dong Jang, Tuulia Vallius, Yu-An Chen, Marcelo Cicconet, Zoltan Maliga, Connor A. Jacobson, Donglai Wei, Sandro Santagata, Hanspeter Pfister, Peter K. Sorger
Summary: This paper reports two findings that substantially improve image segmentation of tissues using a range of machine learning architectures. The inclusion of intentionally defocused and saturated images in training data and imaging the nuclear envelope using an antibody cocktail both significantly improve segmentation. These approaches have a positive impact on a wide range of tissue types and may have applications in image processing outside of microscopy.
COMMUNICATIONS BIOLOGY
(2022)
Article
Computer Science, Software Engineering
Tica Lin, Yalong Yang, Johanna Beyer, Hanspeter Pfister
Summary: Augmented Reality (AR) embeds digital information into physical objects, enabling real-time comparisons and search. This study categorizes different design aspects in AR label design and evaluates five different label conditions for visual search tasks. The study finds that angle-encoded labels with directional cues have the best performance and highest user satisfaction, especially for searching objects outside the field of view and comparing sparse objects.
IEEE TRANSACTIONS ON VISUALIZATION AND COMPUTER GRAPHICS
(2023)
Article
Computer Science, Information Systems
Leander Lauenburg, Zudi Lin, Ruihan Zhang, Marcia dos Santos, Siyu Huang, Ignacio Arganda-Carreras, Edward S. Boyden, Hanspeter Pfister, Donglai Wei
Summary: In this study, a novel Cyclic Segmentation Generative Adversarial Network (CySGAN) is proposed to conduct image translation and instance segmentation simultaneously using a unified network with weight sharing. The proposed CySGAN outperforms pre-trained generalist models, feature-level domain adaptation models, and the baselines that conduct image translation and segmentation sequentially. The study shows the effectiveness of the CySGAN in 3D neuronal nuclei segmentation for unlabeled imaging modalities.
IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS
(2023)
Proceedings Paper
Computer Science, Information Systems
Zhutian Chen, Qisen Yang, Jerry Shan, Tica Lin, Johanna Beyer, Haijun Xia, Hanspeter Pfster
Summary: We present iBall, a basketball video-watching system that uses gaze-moderated embedded visualizations to help casual fans understand and engage with basketball games. Through a comparative study of casual and die-hard fans' game-watching behaviors, we developed iBall and confirmed its usefulness and user engagement in an experiment.
PROCEEDINGS OF THE 2023 CHI CONFERENCE ON HUMAN FACTORS IN COMPUTING SYSTEMS (CHI 2023)
(2023)
Proceedings Paper
Yalong Yang, Wenyu Xia, Fritz Lekschas, Carolina Nobre, Robert Krueger, Hanspeter Pfister
Summary: Matrix visualizations are commonly used for displaying large-scale network, tabular, set, or sequential data. This article compares the performance of focus+context, pan&zoom, and overview+detail interaction methods in exploring multivariate matrix visualizations. The study finds that the fish-eye lens outperforms other techniques in overall performance, while pan&zoom is faster for locating and searching details, and as good as overview+detail in contextualizing details.
PROCEEDINGS OF THE 2022 CHI CONFERENCE ON HUMAN FACTORS IN COMPUTING SYSTEMS (CHI' 22)
(2022)
Proceedings Paper
Computer Science, Artificial Intelligence
Donglai Wei, Siddhant Kharbanda, Sarthak Arora, Roshan Roy, Nishant Jain, Akash Palrecha, Tanav Shah, Shray Mathur, Ritik Mathur, Abhijay Kemkar, Anirudh Chakravarthy, Zudi Lin, Won-Dong Jang, Yansong Tang, Song Bai, James Tompkin, Philip H. S. Torr, Hanspeter Pfister
Summary: Existing datasets for video object segmentation cannot meet the requirements of analyzing multi-shot videos. Therefore, we collected a new dataset called YouMVOS, which includes 200 popular YouTube videos. Our dataset surpasses previous datasets in terms of video duration, object variation, and narrative structure complexity, and provides competitive baseline methods.
2022 IEEE/CVF CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION (CVPR 2022)
(2022)
Proceedings Paper
Computer Science, Artificial Intelligence
Zixiang Zhao, Jiangshe Zhang, Shuang Xu, Zudi Lin, Hanspeter Pfister
Summary: Guided depth super-resolution (GDSR) is a key topic in multi-modal image processing, which reconstructs high-resolution depth maps from low-resolution ones with the help of high-resolution RGB images. In this study, the researchers propose a Discrete Cosine Transform Network (DCTNet) to address the challenges in GDSR. The DCTNet outperforms previous methods with a relatively small number of parameters.
2022 IEEE/CVF CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION (CVPR 2022)
(2022)
Proceedings Paper
Computer Science, Artificial Intelligence
Salma Abdel Magid, Zudi Lin, Donglai Wei, Yulun Zhang, Jinjin Gu, Hanspeter Pfister
Summary: Evaluation practices for image super-resolution typically rely on single-value metrics like PSNR or SSIM, which offer limited insight into error sources and model behavior. This study proposes a new approach focusing on interpretability, utilizing a texture classifier for in-depth error analysis to identify the sources of SR errors. By examining datasets from various perspectives, the research uncovers unexpected insights that may help in debugging blackbox SR networks.
2022 IEEE/CVF CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION (CVPR 2022)
(2022)
Proceedings Paper
Computer Science, Theory & Methods
Boaz Arad, Radu Timofte, Rony Yahel, Nimrod Morag, Amir Bernat, Yuanhao Cai, Jing Lin, Zudi Lin, Haoqian Wang, Yulun Zhang, Hanspeter Pfister, Luc Van Gool, Shuai Liu, Yongqiang Li, Chaoyu Feng, Lei Lei, Jiaojiao Li, Songcheng Du, Chaoxiong Wu, Yihong Leng, Rui Song, Mingwei Zhang, Chongxing Song, Shuyi Zhao, Zhiqiang Lang, Wei Wei, Lei Zhang, Renwei Dian, Tianci Shan, Anjing Guo, Chengguo Feng, Jinyang Liu, Mirko Agarla, Simone Bianco, Marco Buzzelli, Luigi Celona, Raimondo Schettini, Jiang He, Yi Xiao, Jiajun Xiao, Qiangqiang Yuan, Jie Li, Liangpei Zhang, Taesung Kwon, Dohoon Ryu, Hyokyoung Bae, Hao-Hsiang Yang, Hua-En Chang, Zhi-Kai Huang, Wei-Ting Chen, Sy-Yen Kuo, Junyu Chen, Haiwei Li, Song Liu, Sabarinathan K. Uma, B. Sathya Bama, S. Mohamed Mansoor Roomi
Summary: This paper reviews the third biennial challenge on spectral reconstruction from RGB images, which aims to recover hyperspectral information from compressed RGB images. 241 teams participated in the challenge, with 60 teams entering the final testing phase. The performance of these submissions is evaluated as a benchmark for the current state-of-the-art in spectral reconstruction from natural RGB images.
2022 IEEE/CVF CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION WORKSHOPS, CVPRW 2022
(2022)
Proceedings Paper
Computer Science, Theory & Methods
Yuanhao Cai, Jing Lin, Zudi Lin, Haoqian Wang, Yulun Zhang, Hanspeter Pfister, Radu Timofte, Luc Van Gool
Summary: This paper proposes a Transformer-based method, Multi-stage Spectral-wise Transformer (MST++), for efficient spectral reconstruction. By utilizing Spectral-wise Multi-head Self-attention (S-MSA) and Spectral-wise Attention Block (SAB), the proposed method extracts multi-resolution contextual information to improve the reconstruction quality progressively. Experimental results demonstrate the superior performance of MST++ compared to other state-of-the-art methods.
2022 IEEE/CVF CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION WORKSHOPS, CVPRW 2022
(2022)