no code implementations • 15 Nov 2024 • Qi Liu, Yanchen Liu, Ruifeng Li, Chenhong Cao, Yufeng Li, Xingyu Li, Peng Wang, Runhan Feng
We then propose an injection attack detector, MDHP-Net, which integrates optimal MDHP parameters with MDHP-LSTM blocks to enhance temporal feature extraction.
1 code implementation • 14 Oct 2024 • Hong Li, Zhiquan Tan, Xingyu Li, Weiran Huang
In addition, there is still a lack of research investigating the consequences of integrating a multi-modal model into the updating procedure for both uni-modal and multi-modal tasks and the subsequent impacts it has on downstream tasks.
no code implementations • 13 Oct 2024 • Muhammad Gohar Javed, Chuan Guo, Li Cheng, Xingyu Li
In this work, we introduce InterMask, a novel framework for generating human interactions using collaborative masked modeling in discrete space.
Ranked #1 on
Motion Synthesis
on Inter-X
no code implementations • 23 Sep 2024 • YuAn Liu, Shu Wang, Zhe Qu, Xingyu Li, Shichao Kan, Jianxin Wang
Federated Domain Generalization (FedDG) aims to train the global model for generalization ability to unseen domains with multi-domain training samples.
no code implementations • 29 Jul 2024 • Tianhang Nan, Hao Quan, Yong Ding, Xingyu Li, Kai Yang, Xiaoyu Cui
However, a drawback of such methods is the incorporation of more redundant patches, leading to interference.
no code implementations • 23 Jul 2024 • Bach Viet Do, Xingyu Li, Chaoye Pan, Oleg Gusikhin
In this study, we demonstrate how we construct a dataset consisting of many multivariate time series to forecast first-tier supply chain disruptions, utilizing features related to capacity, inventory, utilization, and processing, as outlined in the classical Factory Physics framework.
1 code implementation • 14 Jul 2024 • Yinsheng He, Xingyu Li, Roger J. Zemp
To explore the potential of leveraging MIL-based segmentation for pseudo supervision, we propose a novel distillation framework for histopathology image segmentation.
no code implementations • 7 Jul 2024 • Xiaokang Pan, Xingyu Li, Jin Liu, Tao Sun, Kai Sun, Lixing Chen, Zhe Qu
This paper provides a comprehensive generalization analysis of three representative STORM-based algorithms: STORM, COVER, and SVMR, for one, two, and $K$-level stochastic optimizations under both convex and strongly convex settings based on algorithmic stability.
no code implementations • 15 May 2024 • Xingyu Li, Bo Tang
Deep neural networks suffer from the catastrophic forgetting problem in the field of continual learning (CL).
no code implementations • 10 May 2024 • Xingyu Li, Lu Peng, Yuping Wang, Weihua Zhang
This survey explores the transformative impact of foundation models (FMs) in artificial intelligence, focusing on their integration with federated learning (FL) for advancing biomedical research.
no code implementations • 8 May 2024 • Zhaoxiang Zhang, Hanqiu Deng, Jinan Bao, Xingyu Li
Image Anomaly Detection has been a challenging task in Computer Vision field.
no code implementations • 2 May 2024 • Xingyu Li, Fei Tao, Wei Ye, Aydin Nassehi, John W. Sutherland
In this study, we introduce Generative Manufacturing Systems (GMS) as a novel approach to effectively manage and coordinate autonomous manufacturing assets, thereby enhancing their responsiveness and flexibility to address a wide array of production objectives and human preferences.
1 code implementation • 25 Apr 2024 • Nico Schiavone, Xingyu Li
In this work, we propose a framework utilizing reinforcement learning as a control for foundation models, allowing for the granular generation of small, focused synthetic support sets to augment the performance of neural network models on real data classification tasks.
1 code implementation • 12 Apr 2024 • Yifei Lin, Hanqiu Deng, Xingyu Li
Nowadays large computers extensively output logs to record the runtime status and it has become crucial to identify any suspicious or malicious activities from the information provided by the realtime logs.
no code implementations • 27 Feb 2024 • Hanqiu Deng, Xingyu Li
Visual anomaly detection is a challenging open-set task aimed at identifying unknown anomalous patterns while modeling normal data.
1 code implementation • 21 Feb 2024 • Qi Liu, Xingyu Li, Ke Sun, Yufeng Li, Yanchen Liu
Scalable service-Oriented Middleware over IP (SOME/IP) is an Ethernet communication standard protocol in the Automotive Open System Architecture (AUTOSAR), promoting ECU-to-ECU communication over the IP stack.
1 code implementation • 12 Dec 2023 • Jian Zhu, Yu Cui, Zhangmin Huang, Xingyu Li, Lei Liu, Lingfang Zeng, Li-Rong Dai
Furthermore, an adaptive confidence multi-view network is employed to measure the confidence of each view and then fuse multi-view features through a weighted summation.
1 code implementation • 17 Nov 2023 • Shuangzhi Li, Lei Ma, Xingyu Li
Specifically, from the perspective of data augmentation, we design a universal physical-aware density-based data augmentation (PDDA) method to mitigate the performance loss stemming from diverse point densities.
1 code implementation • 24 Oct 2023 • Nico Schiavone, Jingyi Wang, Shuangzhi Li, Roger Zemp, Xingyu Li
To this end, we introduce an active few shot learning framework, Myriad Active Learning (MAL), including a contrastive-learning encoder, pseudo-label generation, and novel query sample selection in the loop.
1 code implementation • 10 Oct 2023 • Pengyue Hou, Xingyu Li
The recent success of SimCSE has greatly advanced state-of-the-art sentence representations.
no code implementations • 9 Oct 2023 • Chen Qiu, Xingyu Li, Chaithanya Kumar Mummadi, Madan Ravi Ganesh, Zhenzhen Li, Lu Peng, Wan-Yi Lin
Prompt learning for vision-language models, e. g., CoOp, has shown great success in adapting CLIP to different downstream tasks, making it a promising solution for federated learning due to computational reasons.
1 code implementation • 30 Aug 2023 • Hanqiu Deng, Zhaoxiang Zhang, Jinan Bao, Xingyu Li
On top of the proposed AnoCLIP, we further introduce a test-time adaptation (TTA) mechanism to refine visual anomaly localization results, where we optimize a lightweight adapter in the visual encoder using AnoCLIP's pseudo-labels and noise-corrupted tokens.
no code implementations • 29 Aug 2023 • Hao Xuan, Peican Zhu, Xingyu Li
Based on ALU, we introduce a new classification paradigm that utilizes pre- and post-purification logit differences for model's adversarial robustness boost.
1 code implementation • 18 Aug 2023 • Xiaohan Zhang, Xingyu Li, Waqas Sultani, Chen Chen, Safwan Wshah
We attribute this deficiency to the lack of ability to extract the geometric layout of visual features and models' overfitting to low-level details.
no code implementations • 18 Aug 2023 • Pengbo Hu, Ji Qi, Xingyu Li, Hong Li, Xinqi Wang, Bing Quan, Ruiyu Wang, Yi Zhou
Our approach succeeds in performance while significantly saving inference steps.
1 code implementation • ICCV 2023 • Hong Li, Xingyu Li, Pengbo Hu, Yinuo Lei, Chunxiao Li, Yi Zhou
In addition, we find that the jointly trained model typically has a preferred modality on which the competition is weaker than other modalities.
no code implementations • 7 Aug 2023 • Xingyu Li, Bo Tang
Deep neural networks (DNNs) have demonstrated promising results in various complex tasks.
no code implementations • 7 Aug 2023 • Xingyu Li, Bo Tang, Haifeng Li
Continual lifelong learning is an machine learning framework inspired by human learning, where learners are trained to continuously acquire new knowledge in a sequential manner.
1 code implementation • 20 Jun 2023 • Jinan Bao, Hanshi Sun, Hanqiu Deng, Yinsheng He, Zhaoxiang Zhang, Xingyu Li
However, there is a lack of a universal and fair benchmark for evaluating AD methods on medical images, which hinders the development of more generalized and robust AD methods in this specific domain.
no code implementations • 16 Jun 2023 • Yuqian Sun, Xingyu Li, Ze Gao
This research delves into the intersection of illustration art and artificial intelligence (AI), focusing on how illustrators engage with AI agents that embody their original characters (OCs).
no code implementations • 3 May 2023 • Min Cen, Xingyu Li, Bangwei Guo, Jitendra Jonnagaddala, Hong Zhang, Xu Steven Xu
Additionally, under the same experimental conditions using the same set of training and testing datasets, DPSeq surpassed 4 CNN (ResNet18, ResNet50, MobileNetV2, and EfficientNet) and 2 transformer (ViT and Swin-T) models, achieving the highest AUROC and AUPRC values in predicting MSI status, BRAF mutation, and CIMP status.
no code implementations • 24 Apr 2023 • Zhihang Song, Zimin He, Xingyu Li, Qiming Ma, Ruibo Ming, Zhiqi Mao, Huaxin Pei, Lihui Peng, Jianming Hu, Danya Yao, Yi Zhang
In this paper, we summarize the evolution of synthetic dataset generation methods and review the work to date in synthetic datasets related to single and multi-task categories for to autonomous driving study.
1 code implementation • 18 Mar 2023 • Yinsheng He, Xingyu Li
Recently, various deep learning methods have shown significant successes in medical image analysis, especially in the detection of cancer metastases in hematoxylin and eosin (H&E) stained whole-slide images (WSIs).
no code implementations • 21 Feb 2023 • Min Cen, Xingyu Li, Bangwei Guo, Jitendra Jonnagaddala, Hong Zhang, Xu Steven Xu
However, most digital pathology artificial-intelligence models are based on CNN architectures, probably owing to a lack of data regarding NLP models for pathology images.
no code implementations • CVPR 2023 • Zhe Qu, Xingyu Li, Xiao Han, Rui Duan, Chengchao Shen, Lixing Chen
Intuitively, these poor clients may come from biased universal information shared with others.
no code implementations • 16 Dec 2022 • Matthias Eisenmann, Annika Reinke, Vivienn Weru, Minu Dietlinde Tizabi, Fabian Isensee, Tim J. Adler, Patrick Godau, Veronika Cheplygina, Michal Kozubek, Sharib Ali, Anubha Gupta, Jan Kybic, Alison Noble, Carlos Ortiz de Solórzano, Samiksha Pachade, Caroline Petitjean, Daniel Sage, Donglai Wei, Elizabeth Wilden, Deepak Alapatt, Vincent Andrearczyk, Ujjwal Baid, Spyridon Bakas, Niranjan Balu, Sophia Bano, Vivek Singh Bawa, Jorge Bernal, Sebastian Bodenstedt, Alessandro Casella, Jinwook Choi, Olivier Commowick, Marie Daum, Adrien Depeursinge, Reuben Dorent, Jan Egger, Hannah Eichhorn, Sandy Engelhardt, Melanie Ganz, Gabriel Girard, Lasse Hansen, Mattias Heinrich, Nicholas Heller, Alessa Hering, Arnaud Huaulmé, Hyunjeong Kim, Bennett Landman, Hongwei Bran Li, Jianning Li, Jun Ma, Anne Martel, Carlos Martín-Isla, Bjoern Menze, Chinedu Innocent Nwoye, Valentin Oreiller, Nicolas Padoy, Sarthak Pati, Kelly Payette, Carole Sudre, Kimberlin Van Wijnen, Armine Vardazaryan, Tom Vercauteren, Martin Wagner, Chuanbo Wang, Moi Hoon Yap, Zeyun Yu, Chun Yuan, Maximilian Zenk, Aneeq Zia, David Zimmerer, Rina Bao, Chanyeol Choi, Andrew Cohen, Oleh Dzyubachyk, Adrian Galdran, Tianyuan Gan, Tianqi Guo, Pradyumna Gupta, Mahmood Haithami, Edward Ho, Ikbeom Jang, Zhili Li, Zhengbo Luo, Filip Lux, Sokratis Makrogiannis, Dominik Müller, Young-tack Oh, Subeen Pang, Constantin Pape, Gorkem Polat, Charlotte Rosalie Reed, Kanghyun Ryu, Tim Scherr, Vajira Thambawita, Haoyu Wang, Xinliang Wang, Kele Xu, Hung Yeh, Doyeob Yeo, Yixuan Yuan, Yan Zeng, Xin Zhao, Julian Abbing, Jannes Adam, Nagesh Adluru, Niklas Agethen, Salman Ahmed, Yasmina Al Khalil, Mireia Alenyà, Esa Alhoniemi, Chengyang An, Talha Anwar, Tewodros Weldebirhan Arega, Netanell Avisdris, Dogu Baran Aydogan, Yingbin Bai, Maria Baldeon Calisto, Berke Doga Basaran, Marcel Beetz, Cheng Bian, Hao Bian, Kevin Blansit, Louise Bloch, Robert Bohnsack, Sara Bosticardo, Jack Breen, Mikael Brudfors, Raphael Brüngel, Mariano Cabezas, Alberto Cacciola, Zhiwei Chen, Yucong Chen, Daniel Tianming Chen, Minjeong Cho, Min-Kook Choi, Chuantao Xie Chuantao Xie, Dana Cobzas, Julien Cohen-Adad, Jorge Corral Acero, Sujit Kumar Das, Marcela de Oliveira, Hanqiu Deng, Guiming Dong, Lars Doorenbos, Cory Efird, Sergio Escalera, Di Fan, Mehdi Fatan Serj, Alexandre Fenneteau, Lucas Fidon, Patryk Filipiak, René Finzel, Nuno R. Freitas, Christoph M. Friedrich, Mitchell Fulton, Finn Gaida, Francesco Galati, Christoforos Galazis, Chang Hee Gan, Zheyao Gao, Shengbo Gao, Matej Gazda, Beerend Gerats, Neil Getty, Adam Gibicar, Ryan Gifford, Sajan Gohil, Maria Grammatikopoulou, Daniel Grzech, Orhun Güley, Timo Günnemann, Chunxu Guo, Sylvain Guy, Heonjin Ha, Luyi Han, Il Song Han, Ali Hatamizadeh, Tian He, Jimin Heo, Sebastian Hitziger, SeulGi Hong, Seungbum Hong, Rian Huang, Ziyan Huang, Markus Huellebrand, Stephan Huschauer, Mustaffa Hussain, Tomoo Inubushi, Ece Isik Polat, Mojtaba Jafaritadi, SeongHun Jeong, Bailiang Jian, Yuanhong Jiang, Zhifan Jiang, Yueming Jin, Smriti Joshi, Abdolrahim Kadkhodamohammadi, Reda Abdellah Kamraoui, Inha Kang, Junghwa Kang, Davood Karimi, April Khademi, Muhammad Irfan Khan, Suleiman A. Khan, Rishab Khantwal, Kwang-Ju Kim, Timothy Kline, Satoshi Kondo, Elina Kontio, Adrian Krenzer, Artem Kroviakov, Hugo Kuijf, Satyadwyoom Kumar, Francesco La Rosa, Abhi Lad, Doohee Lee, Minho Lee, Chiara Lena, Hao Li, Ling Li, Xingyu Li, Fuyuan Liao, Kuanlun Liao, Arlindo Limede Oliveira, Chaonan Lin, Shan Lin, Akis Linardos, Marius George Linguraru, Han Liu, Tao Liu, Di Liu, Yanling Liu, João Lourenço-Silva, Jingpei Lu, Jiangshan Lu, Imanol Luengo, Christina B. Lund, Huan Minh Luu, Yi Lv, Uzay Macar, Leon Maechler, Sina Mansour L., Kenji Marshall, Moona Mazher, Richard McKinley, Alfonso Medela, Felix Meissen, Mingyuan Meng, Dylan Miller, Seyed Hossein Mirjahanmardi, Arnab Mishra, Samir Mitha, Hassan Mohy-ud-Din, Tony Chi Wing Mok, Gowtham Krishnan Murugesan, Enamundram Naga Karthik, Sahil Nalawade, Jakub Nalepa, Mohamed Naser, Ramin Nateghi, Hammad Naveed, Quang-Minh Nguyen, Cuong Nguyen Quoc, Brennan Nichyporuk, Bruno Oliveira, David Owen, Jimut Bahan Pal, Junwen Pan, Wentao Pan, Winnie Pang, Bogyu Park, Vivek Pawar, Kamlesh Pawar, Michael Peven, Lena Philipp, Tomasz Pieciak, Szymon Plotka, Marcel Plutat, Fattaneh Pourakpour, Domen Preložnik, Kumaradevan Punithakumar, Abdul Qayyum, Sandro Queirós, Arman Rahmim, Salar Razavi, Jintao Ren, Mina Rezaei, Jonathan Adam Rico, ZunHyan Rieu, Markus Rink, Johannes Roth, Yusely Ruiz-Gonzalez, Numan Saeed, Anindo Saha, Mostafa Salem, Ricardo Sanchez-Matilla, Kurt Schilling, Wei Shao, Zhiqiang Shen, Ruize Shi, Pengcheng Shi, Daniel Sobotka, Théodore Soulier, Bella Specktor Fadida, Danail Stoyanov, Timothy Sum Hon Mun, Xiaowu Sun, Rong Tao, Franz Thaler, Antoine Théberge, Felix Thielke, Helena Torres, Kareem A. Wahid, Jiacheng Wang, Yifei Wang, Wei Wang, Xiong Wang, Jianhui Wen, Ning Wen, Marek Wodzinski, Ye Wu, Fangfang Xia, Tianqi Xiang, Chen Xiaofei, Lizhan Xu, Tingting Xue, Yuxuan Yang, Lin Yang, Kai Yao, Huifeng Yao, Amirsaeed Yazdani, Michael Yip, Hwanseung Yoo, Fereshteh Yousefirizi, Shunkai Yu, Lei Yu, Jonathan Zamora, Ramy Ashraf Zeineldin, Dewen Zeng, Jianpeng Zhang, Bokai Zhang, Jiapeng Zhang, Fan Zhang, Huahong Zhang, Zhongchen Zhao, Zixuan Zhao, Jiachen Zhao, Can Zhao, Qingshuo Zheng, Yuheng Zhi, Ziqi Zhou, Baosheng Zou, Klaus Maier-Hein, Paul F. Jäger, Annette Kopp-Schneider, Lena Maier-Hein
Of these, 84% were based on standard architectures.
1 code implementation • 8 Dec 2022 • Xiaohan Zhang, Xingyu Li, Waqas Sultani, Yi Zhou, Safwan Wshah
We attribute this deficiency to the lack of ability to extract the spatial configuration of visual feature layouts and models' overfitting on low-level details from the training set.
1 code implementation • 26 Oct 2022 • Pengyue Hou, Jie Han, Xingyu Li
Deep Neural Networks are vulnerable to adversarial attacks.
no code implementations • 12 Oct 2022 • Shuangzhi Li, Zhijie Wang, Felix Juefei-Xu, Qing Guo, Xingyu Li, Lei Ma
Then, for the first attempt, we construct a benchmark based on the physical-aware common corruptions for point cloud detectors, which contains a total of 1, 122, 150 examples covering 7, 481 scenes, 25 common corruption types, and 6 severities.
no code implementations • 23 Aug 2022 • Anran Liu, Xingyu Li, Hongyi Wu, Bangwei Guo, Jitendra Jonnagaddala, Hong Zhang, Xu Steven Xu
Methods We developed an automated, multiscale LinkNet workflow for quantifying cellular-level TILs for CRC tumors using H&E-stained images.
no code implementations • 22 Aug 2022 • Bangwei Guo, Xingyu Li, Jitendra Jonnagaddala, Hong Zhang, Xu Steven Xu
In this study, based on the latest Hierarchical Vision Transformer using Shifted Windows (Swin-T), we developed an efficient workflow for biomarkers in CRC (MSI, hypermutation, chromosomal instability, CpG island methylator phenotype, BRAF, and TP53 mutation) that only required relatively small datasets, but achieved the state-of-the-art (SOTA) predictive performance.
1 code implementation • 6 Jun 2022 • Zhe Qu, Xingyu Li, Rui Duan, Yao Liu, Bo Tang, Zhuo Lu
Therefore, in this paper, we revisit the solutions to the distribution shift problem in FL with a focus on local learning generality.
no code implementations • 31 May 2022 • Bangwei Guo, Xingyu Li, Miaomiao Yang, Hong Zhang, Xu Steven Xu
In addition, compared to the published models for genetic alterations, AMIML provided a significant improvement for predicting a wide range of genes (e. g., KMT2C, TP53, and SETD2 for KIRC; ERBB2, BRCA1, and BRCA2 for BRCA; JAK1, POLE, and MTOR for UCEC) as well as produced outstanding predictive models for other clinically relevant gene mutations, which have not been reported in the current literature.
1 code implementation • 18 May 2022 • Hao Quan, Xingyu Li, Weixing Chen, Qun Bai, Mingchen Zou, Ruijie Yang, Tingting Zheng, Ruiqun Qi, Xinghua Gao, Xiaoyu Cui
Based on digital pathology slice scanning technology, artificial intelligence algorithms represented by deep learning have achieved remarkable results in the field of computational pathology.
1 code implementation • 1 May 2022 • Xiyuan Chen, Xingyu Li, Yi Zhou, Tianming Yang
The mechanism is well described by the Drift-Diffusion Model (DDM).
1 code implementation • 30 Apr 2022 • Pengbo Hu, Xingyu Li, Yi Zhou
Our experiments suggest that for some tasks where different modalities are complementary, the multi-modal models still tend to use the dominant modality alone and ignore the cooperation across modalities.
no code implementations • 28 Apr 2022 • Pengyue Hou, Ming Zhou, Jie Han, Petr Musilek, Xingyu Li
Adversarial training is an effective method to boost model robustness to malicious, adversarial attacks.
no code implementations • 24 Apr 2022 • Xingyu Li, Jitendra Jonnagaddala, Min Cen, Hong Zhang, Xu Steven Xu
Several deep learning algorithms have been developed to predict survival of cancer patients using whole slide images (WSIs). However, identification of image phenotypes within the WSIs that are relevant to patient survival and disease progression is difficult for both clinicians, and deep learning algorithms.
no code implementations • 31 Mar 2022 • Zihan Chen, Xingyu Li, Miaomiao Yang, Hong Zhang, Xu Steven Xu
We showed that unsupervised clustering of image patches could help identify predictive patches, exclude patches lack of predictive information, and therefore improve prediction on gene mutations in all three different cancer types, compared with the WSI based method without selection of image patches and models based on only tumor regions.
no code implementations • 24 Feb 2022 • Xingyu Li, Yan Shen, Qiankun Zhou
We consider the construction of confidence intervals for treatment effects estimated using panel models with interactive fixed effects.
5 code implementations • CVPR 2022 • Hanqiu Deng, Xingyu Li
Knowledge distillation (KD) achieves promising results on the challenging problem of unsupervised anomaly detection (AD). The representation discrepancy of anomalies in the teacher-student (T-S) model provides essential evidence for AD.
Ranked #2 on
Anomaly Detection
on AeBAD-V
no code implementations • 8 Jan 2022 • Xingyu Li, Zhe Qu, Shangqing Zhao, Bo Tang, Zhuo Lu, Yao Liu
Federated learning (FL) provides a high efficient decentralized machine learning framework, where the training data remains distributed at remote clients in a network.
no code implementations • 3 Jan 2022 • Xingyu Li, Min Cen, Jinfeng Xu, Hong Zhang, Xu Steven Xu
The extracted features from the finetuned FTX2048 exhibited significantly higher accuracy for predicting tisue types of CRC compared to the off the shelf feature directly from Xception based on ImageNet database.
1 code implementation • CVPR 2022 • Chuan Guo, Shihao Zou, Xinxin Zuo, Sen Wang, Wei Ji, Xingyu Li, Li Cheng
Automated generation of 3D human motions from text is a challenging problem.
Ranked #3 on
Motion Synthesis
on Inter-X
no code implementations • 22 Dec 2021 • Xingyu Li, Zhe Qu, Bo Tang, Zhuo Lu
Federated Learning (FL) is a decentralized machine learning architecture, which leverages a large number of remote devices to learn a joint model with distributed training data.
no code implementations • 21 Nov 2021 • Kaiyuan Liu, Xingyu Li, Yurui Lai, Ge Zhang, Hang Su, Jiachen Wang, Chunxu Guo, Jisong Guan, Yi Zhou
Despite its great success, deep learning severely suffers from robustness; that is, deep neural networks are very vulnerable to adversarial attacks, even the simplest ones.
no code implementations • 5 Nov 2021 • Xingyu Li, Jitendra Jonnagaddala, Shuhua Yang, Hong Zhang, Xu Steven Xu
We developed a novel deep-learning algorithm (CRCNet) using whole-slide images from Molecular and Cellular Oncology (MCO) to predict survival benefit of adjuvant chemotherapy in stage II/III CRC.
no code implementations • 23 Aug 2021 • Yixin Hu, Xingyu Li
For images where faces are improperly covered, our mask overlay module incorporates statistical shape analysis (SSA) and dense landmark alignment to approximate the geometry of a face and generates corresponding face-covering examples.
no code implementations • 5 Aug 2021 • Ji Yang, Xinxin Zuo, Sen Wang, Zhenbo Yu, Xingyu Li, Bingbing Ni, Minglun Gong, Li Cheng
A dataset of generic 3D objects with ground-truth annotated skeletons is collected.
no code implementations • 22 Apr 2021 • Ali Akbar Sadat Asl, Mohammad Mahdi Ershadi, Shahabeddin Sotudian, Xingyu Li, Scott Dick
The results show that the type-2 fuzzy expert system and ANFIS models perform competitively in terms of accuracy and F-measure compared to the other system modeling techniques.
no code implementations • 28 Mar 2021 • Xingyu Li, Difan Song, Miaozhe Han, Yu Zhang, Rene F. Kizilcec
We tested how well predictive models of human behavior trained in a developed country generalize to people in less developed countries by modeling global variation in 200 predictors of academic achievement on nationally representative student data for 65 countries.
no code implementations • 12 Feb 2021 • Xingyu Li
Prior model-based stain separation methods usually rely on stains' spatial distributions over an image and may fail to solve the co-localization problem.
no code implementations • 12 Feb 2021 • Xingyu Li, Zhe Qu, Bo Tang, Zhuo Lu
Federated learning (FL) is a new machine learning framework which trains a joint model across a large amount of decentralized computing devices.
no code implementations • Findings of the Association for Computational Linguistics 2020 • Tianyi Luo, Xingyu Li, Hainan Wang, Yang Liu
In this paper, we propose two weakly supervised learning approaches that use automatically extracted text information of research papers to improve the prediction accuracy of research replication using both labeled and unlabeled datasets.
1 code implementation • ICLR 2021 • Hao Cheng, Zhaowei Zhu, Xingyu Li, Yifei Gong, Xing Sun, Yang Liu
This high-quality sample sieve allows us to treat clean examples and the corrupted ones separately in training a DNN solution, and such a separation is shown to be advantageous in the instance-dependent noise setting.
Image Classification with Label Noise
Learning with noisy labels
1 code implementation • 24 Jul 2020 • Hanwen Liang, Konstantinos N. Plataniotis, Xingyu Li
To address the issue of color variations in histopathology images, this study proposes two stain style transfer models, SSIM-GAN and DSCSI-GAN, based on the generative adversarial networks.
no code implementations • 24 Apr 2020 • Xingyu Li, Konstantinos N. Plataniotis
Particularly, compared to the performance baseline obtained by random-weight model, though transferability of off-the-shelf representations from deep layers heavily depend on specific pathology image sets, the general representation generated by early layers does convey transferred knowledge in various image classification applications.
1 code implementation • 8 Oct 2019 • Jiaheng Wei, Zuyue Fu, Yang Liu, Xingyu Li, Zhuoran Yang, Zhaoran Wang
We also show a connection between this sample elicitation problem and $f$-GAN, and how this connection can help reconstruct an estimator of the distribution based on collected samples.
no code implementations • 27 Sep 2019 • Lanoir Addala, Jean Dolbeault, Xingyu Li, Mohamed Lazhar Tayeb
This paper is devoted to the linearized Vlasov-Poisson-Fokker-Planck system in presence of an external potential of confinement.
Analysis of PDEs 82C40, 35H10, 35P15, 35Q84, 35R09, 47G20, 82C21, 82D10, 82D37
no code implementations • 2 Jul 2019 • Xingyu Li, Mainak Mitra, Bogdan I. Epureanu
A novel approach is provided for evaluating the benefits and burdens from vehicle modularity in fleets/units through the analysis of a game theoretical model of the competition between autonomous vehicle fleets in an attacker-defender game.
no code implementations • 22 Feb 2019 • Xingyu Li, Marko Radulovic, Ksenija Kanjer, Konstantinos N. Plataniotis
We apply the proposed method to a public breast cancer image set.
1 code implementation • NAACL 2019 • Wei Yang, Yuqing Xie, Aileen Lin, Xingyu Li, Luchen Tan, Kun Xiong, Ming Li, Jimmy Lin
We demonstrate an end-to-end question answering system that integrates BERT with the open-source Anserini information retrieval toolkit.
Ranked #4 on
Open-Domain Question Answering
on SQuAD1.1 dev
no code implementations • 9 Nov 2018 • Xingyu Li, Bogdan I. Epureanu
Because combat environments change over time and technology upgrades are widespread for ground vehicles, a large number of vehicles and equipment become quickly obsolete.