Search Results for author: Ruixuan Wang

Found 23 papers, 8 papers with code

Generalizable Two-Branch Framework for Image Class-Incremental Learning

no code implementations28 Feb 2024 Chao Wu, Xiaobin Chang, Ruixuan Wang

Specifically, the main branch can be any existing CL model and the newly introduced side branch is a lightweight convolutional network.

Class Incremental Learning Incremental Learning

Intensive Vision-guided Network for Radiology Report Generation

no code implementations6 Feb 2024 Fudan Zheng, Mengfei Li, Ying Wang, Weijiang Yu, Ruixuan Wang, Zhiguang Chen, Nong Xiao, Yutong Lu

Given the above limitation in feature extraction, we propose a Globally-intensive Attention (GIA) module in the medical image encoder to simulate and integrate multi-view vision perception.

A Target Detection Algorithm in Traffic Scenes Based on Deep Reinforcement Learning

no code implementations25 Dec 2023 Xinyu Ren, Ruixuan Wang

This research presents a novel active detection model utilizing deep reinforcement learning to accurately detect traffic objects in real-world scenarios.


Classifier-head Informed Feature Masking and Prototype-based Logit Smoothing for Out-of-Distribution Detection

no code implementations27 Oct 2023 Zhuohao Sun, Yiqiao Qiu, Zhijun Tan, Weishi Zheng, Ruixuan Wang

Logit smoothing computes the cosine similarity between the feature vector of the test sample and the prototype of the predicted ID class at the penultimate layer and uses the similarity as an adaptive temperature factor on the logit to alleviate the network's overconfidence prediction for OOD data.

Out-of-Distribution Detection Out of Distribution (OOD) Detection

Adapter Learning in Pretrained Feature Extractor for Continual Learning of Diseases

1 code implementation18 Apr 2023 Wentao Zhang, Yujun Huang, Tong Zhang, Qingsong Zou, Wei-Shi Zheng, Ruixuan Wang

In particular, updating an intelligent diagnosis system with training data of new diseases would cause catastrophic forgetting of old disease knowledge.

Continual Learning

PAMI: partition input and aggregate outputs for model interpretation

no code implementations7 Feb 2023 Wei Shi, Wentao Zhang, Weishi Zheng, Ruixuan Wang

There is an increasing demand for interpretation of model predictions especially in high-risk applications.

Adaptively Integrated Knowledge Distillation and Prediction Uncertainty for Continual Learning

no code implementations18 Jan 2023 Kanghao Chen, Sijia Liu, Ruixuan Wang, Wei-Shi Zheng

The first one is to adaptively integrate multiple levels of old knowledge and transfer it to each block level in the new model.

Continual Learning Knowledge Distillation

PyGFI: Analyzing and Enhancing Robustness of Graph Neural Networks Against Hardware Errors

no code implementations7 Dec 2022 Ruixuan Wang, Fred Lin, Daniel Moore, Sriram Sankar, Xun Jiao

Inspired by the inherent algorithmic resilience of DL methods, this paper conducts, for the first time, a large-scale and empirical study of GNN resilience, aiming to understand the relationship between hardware faults and GNN accuracy.

Recommendation Systems

Learning Discriminative Representation via Metric Learning for Imbalanced Medical Image Classification

no code implementations14 Jul 2022 Chenghua Zeng, Huijuan Lu, Kanghao Chen, Ruixuan Wang, Wei-Shi Zheng

Data imbalance between common and rare diseases during model training often causes intelligent diagnosis systems to have biased predictions towards common diseases.

Image Classification Medical Image Classification +1

PCCT: Progressive Class-Center Triplet Loss for Imbalanced Medical Image Classification

no code implementations11 Jul 2022 Kanghao Chen, Weixian Lei, Rong Zhang, Shen Zhao, Wei-Shi Zheng, Ruixuan Wang

For the class-center involved triplet loss, the positive and negative samples in each triplet are replaced by their corresponding class centers, which enforces data representations of the same class closer to the class center.

Image Classification Medical Image Classification

Task-oriented Self-supervised Learning for Anomaly Detection in Electroencephalography

1 code implementation4 Jul 2022 Yaojia Zheng, Zhouwu Liu, Rong Mo, Ziyi Chen, Wei-Shi Zheng, Ruixuan Wang

Compared to supervised learning with labelled disease EEG data which can train a model to analyze specific diseases but would fail to monitor previously unseen statuses, anomaly detection based on only normal EEGs can detect any potential anomaly in new EEGs.

Anomaly Detection EEG +1

Continual Learning with Bayesian Model based on a Fixed Pre-trained Feature Extractor

no code implementations28 Apr 2022 Yang Yang, Zhiying Cui, Junjie Xu, Changhong Zhong, Wei-Shi Zheng, Ruixuan Wang

In this case, updating the intelligent system with data of new diseases would inevitably downgrade its performance on previously learned diseases.

Class Incremental Learning Image Classification +1

EnHDC: Ensemble Learning for Brain-Inspired Hyperdimensional Computing

no code implementations25 Mar 2022 Ruixuan Wang, Dongning Ma, Xun Jiao

Ensemble learning is a classical learning method utilizing a group of weak learners to form a strong learner, which aims to increase the accuracy of the model.

Ensemble Learning Human Activity Recognition

SATS: Self-Attention Transfer for Continual Semantic Segmentation

1 code implementation15 Mar 2022 Yiqiao Qiu, Yixing Shen, Zhuohao Sun, Yanchong Zheng, Xiaobin Chang, Weishi Zheng, Ruixuan Wang

Considering that pixels belonging to the same class in each image often share similar visual properties, a class-specific region pooling is applied to provide more efficient relationship information for knowledge transfer.

Knowledge Distillation Overlapped 100-10 +8

Automated Architecture Search for Brain-inspired Hyperdimensional Computing

no code implementations11 Feb 2022 Junhuan Yang, Yi Sheng, Sizhe Zhang, Ruixuan Wang, Kenneth Foreman, Mikell Paige, Xun Jiao, Weiwen Jiang, Lei Yang

On the Clintox dataset, which tries to learn features from developed drugs that passed/failed clinical trials for toxicity reasons, the searched HDC architecture obtains the state-of-the-art ROC-AUC scores, which are 0. 80% higher than the manually designed HDC and 9. 75% higher than conventional neural networks.

Drug Discovery

Understanding of Kernels in CNN Models by Suppressing Irrelevant Visual Features in Images

1 code implementation25 Aug 2021 Jia-Xin Zhuang, Wanying Tao, Jianfei Xing, Wei Shi, Ruixuan Wang, Wei-Shi Zheng

In this paper, a simple yet effective optimization method is proposed to interpret the activation of any kernel of interest in CNN models.

Discriminative Distillation to Reduce Class Confusion in Continual Learning

no code implementations11 Aug 2021 Changhong Zhong, Zhiying Cui, Ruixuan Wang, Wei-Shi Zheng

Successful continual learning of new knowledge would enable intelligent systems to recognize more and more classes of objects.

Continual Learning Image Classification

Preserving Earlier Knowledge in Continual Learning with the Help of All Previous Feature Extractors

no code implementations28 Apr 2021 Zhuoyun Li, Changhong Zhong, Sijia Liu, Ruixuan Wang, Wei-Shi Zheng

In order to reduce the forgetting of particularly earlier learned old knowledge and improve the overall continual learning performance, we propose a simple yet effective fusion mechanism by including all the previously learned feature extractors into the intelligent model.

Continual Learning

Towards Unbiased COVID-19 Lesion Localisation and Segmentation via Weakly Supervised Learning

1 code implementation1 Mar 2021 Yang Yang, Jiancong Chen, Ruixuan Wang, Ting Ma, Lingwei Wang, Jie Chen, Wei-Shi Zheng, Tong Zhang

Despite tremendous efforts, it is very challenging to generate a robust model to assist in the accurate quantification assessment of COVID-19 on chest CT images.

Decoder Generative Adversarial Network +1

Identifying the Best Machine Learning Algorithms for Brain Tumor Segmentation, Progression Assessment, and Overall Survival Prediction in the BRATS Challenge

1 code implementation5 Nov 2018 Spyridon Bakas, Mauricio Reyes, Andras Jakab, Stefan Bauer, Markus Rempfler, Alessandro Crimi, Russell Takeshi Shinohara, Christoph Berger, Sung Min Ha, Martin Rozycki, Marcel Prastawa, Esther Alberts, Jana Lipkova, John Freymann, Justin Kirby, Michel Bilello, Hassan Fathallah-Shaykh, Roland Wiest, Jan Kirschke, Benedikt Wiestler, Rivka Colen, Aikaterini Kotrotsou, Pamela Lamontagne, Daniel Marcus, Mikhail Milchenko, Arash Nazeri, Marc-Andre Weber, Abhishek Mahajan, Ujjwal Baid, Elizabeth Gerstner, Dongjin Kwon, Gagan Acharya, Manu Agarwal, Mahbubul Alam, Alberto Albiol, Antonio Albiol, Francisco J. Albiol, Varghese Alex, Nigel Allinson, Pedro H. A. Amorim, Abhijit Amrutkar, Ganesh Anand, Simon Andermatt, Tal Arbel, Pablo Arbelaez, Aaron Avery, Muneeza Azmat, Pranjal B., W Bai, Subhashis Banerjee, Bill Barth, Thomas Batchelder, Kayhan Batmanghelich, Enzo Battistella, Andrew Beers, Mikhail Belyaev, Martin Bendszus, Eze Benson, Jose Bernal, Halandur Nagaraja Bharath, George Biros, Sotirios Bisdas, James Brown, Mariano Cabezas, Shilei Cao, Jorge M. Cardoso, Eric N Carver, Adrià Casamitjana, Laura Silvana Castillo, Marcel Catà, Philippe Cattin, Albert Cerigues, Vinicius S. Chagas, Siddhartha Chandra, Yi-Ju Chang, Shiyu Chang, Ken Chang, Joseph Chazalon, Shengcong Chen, Wei Chen, Jefferson W. Chen, Zhaolin Chen, Kun Cheng, Ahana Roy Choudhury, Roger Chylla, Albert Clérigues, Steven Colleman, Ramiro German Rodriguez Colmeiro, Marc Combalia, Anthony Costa, Xiaomeng Cui, Zhenzhen Dai, Lutao Dai, Laura Alexandra Daza, Eric Deutsch, Changxing Ding, Chao Dong, Shidu Dong, Wojciech Dudzik, Zach Eaton-Rosen, Gary Egan, Guilherme Escudero, Théo Estienne, Richard Everson, Jonathan Fabrizio, Yong Fan, Longwei Fang, Xue Feng, Enzo Ferrante, Lucas Fidon, Martin Fischer, Andrew P. French, Naomi Fridman, Huan Fu, David Fuentes, Yaozong Gao, Evan Gates, David Gering, Amir Gholami, Willi Gierke, Ben Glocker, Mingming Gong, Sandra González-Villá, T. Grosges, Yuanfang Guan, Sheng Guo, Sudeep Gupta, Woo-Sup Han, Il Song Han, Konstantin Harmuth, Huiguang He, Aura Hernández-Sabaté, Evelyn Herrmann, Naveen Himthani, Winston Hsu, Cheyu Hsu, Xiaojun Hu, Xiaobin Hu, Yan Hu, Yifan Hu, Rui Hua, Teng-Yi Huang, Weilin Huang, Sabine Van Huffel, Quan Huo, Vivek HV, Khan M. Iftekharuddin, Fabian Isensee, Mobarakol Islam, Aaron S. Jackson, Sachin R. Jambawalikar, Andrew Jesson, Weijian Jian, Peter Jin, V Jeya Maria Jose, Alain Jungo, B Kainz, Konstantinos Kamnitsas, Po-Yu Kao, Ayush Karnawat, Thomas Kellermeier, Adel Kermi, Kurt Keutzer, Mohamed Tarek Khadir, Mahendra Khened, Philipp Kickingereder, Geena Kim, Nik King, Haley Knapp, Urspeter Knecht, Lisa Kohli, Deren Kong, Xiangmao Kong, Simon Koppers, Avinash Kori, Ganapathy Krishnamurthi, Egor Krivov, Piyush Kumar, Kaisar Kushibar, Dmitrii Lachinov, Tryphon Lambrou, Joon Lee, Chengen Lee, Yuehchou Lee, M Lee, Szidonia Lefkovits, Laszlo Lefkovits, James Levitt, Tengfei Li, Hongwei Li, Hongyang Li, Xiaochuan Li, Yuexiang Li, Heng Li, Zhenye Li, Xiaoyu Li, Zeju Li, Xiaogang Li, Wenqi Li, Zheng-Shen Lin, Fengming Lin, Pietro Lio, Chang Liu, Boqiang Liu, Xiang Liu, Mingyuan Liu, Ju Liu, Luyan Liu, Xavier Llado, Marc Moreno Lopez, Pablo Ribalta Lorenzo, Zhentai Lu, Lin Luo, Zhigang Luo, Jun Ma, Kai Ma, Thomas Mackie, Anant Madabushi, Issam Mahmoudi, Klaus H. Maier-Hein, Pradipta Maji, CP Mammen, Andreas Mang, B. S. Manjunath, Michal Marcinkiewicz, S McDonagh, Stephen McKenna, Richard McKinley, Miriam Mehl, Sachin Mehta, Raghav Mehta, Raphael Meier, Christoph Meinel, Dorit Merhof, Craig Meyer, Robert Miller, Sushmita Mitra, Aliasgar Moiyadi, David Molina-Garcia, Miguel A. B. Monteiro, Grzegorz Mrukwa, Andriy Myronenko, Jakub Nalepa, Thuyen Ngo, Dong Nie, Holly Ning, Chen Niu, Nicholas K Nuechterlein, Eric Oermann, Arlindo Oliveira, Diego D. C. Oliveira, Arnau Oliver, Alexander F. I. Osman, Yu-Nian Ou, Sebastien Ourselin, Nikos Paragios, Moo Sung Park, Brad Paschke, J. Gregory Pauloski, Kamlesh Pawar, Nick Pawlowski, Linmin Pei, Suting Peng, Silvio M. Pereira, Julian Perez-Beteta, Victor M. Perez-Garcia, Simon Pezold, Bao Pham, Ashish Phophalia, Gemma Piella, G. N. Pillai, Marie Piraud, Maxim Pisov, Anmol Popli, Michael P. Pound, Reza Pourreza, Prateek Prasanna, Vesna Prkovska, Tony P. Pridmore, Santi Puch, Élodie Puybareau, Buyue Qian, Xu Qiao, Martin Rajchl, Swapnil Rane, Michael Rebsamen, Hongliang Ren, Xuhua Ren, Karthik Revanuru, Mina Rezaei, Oliver Rippel, Luis Carlos Rivera, Charlotte Robert, Bruce Rosen, Daniel Rueckert, Mohammed Safwan, Mostafa Salem, Joaquim Salvi, Irina Sanchez, Irina Sánchez, Heitor M. Santos, Emmett Sartor, Dawid Schellingerhout, Klaudius Scheufele, Matthew R. Scott, Artur A. Scussel, Sara Sedlar, Juan Pablo Serrano-Rubio, N. Jon Shah, Nameetha Shah, Mazhar Shaikh, B. Uma Shankar, Zeina Shboul, Haipeng Shen, Dinggang Shen, Linlin Shen, Haocheng Shen, Varun Shenoy, Feng Shi, Hyung Eun Shin, Hai Shu, Diana Sima, M Sinclair, Orjan Smedby, James M. Snyder, Mohammadreza Soltaninejad, Guidong Song, Mehul Soni, Jean Stawiaski, Shashank Subramanian, Li Sun, Roger Sun, Jiawei Sun, Kay Sun, Yu Sun, Guoxia Sun, Shuang Sun, Yannick R Suter, Laszlo Szilagyi, Sanjay Talbar, DaCheng Tao, Zhongzhao Teng, Siddhesh Thakur, Meenakshi H Thakur, Sameer Tharakan, Pallavi Tiwari, Guillaume Tochon, Tuan Tran, Yuhsiang M. Tsai, Kuan-Lun Tseng, Tran Anh Tuan, Vadim Turlapov, Nicholas Tustison, Maria Vakalopoulou, Sergi Valverde, Rami Vanguri, Evgeny Vasiliev, Jonathan Ventura, Luis Vera, Tom Vercauteren, C. A. Verrastro, Lasitha Vidyaratne, Veronica Vilaplana, Ajeet Vivekanandan, Qian Wang, Chiatse J. Wang, Wei-Chung Wang, Duo Wang, Ruixuan Wang, Yuanyuan Wang, Chunliang Wang, Guotai Wang, Ning Wen, Xin Wen, Leon Weninger, Wolfgang Wick, Shaocheng Wu, Qiang Wu, Yihong Wu, Yong Xia, Yanwu Xu, Xiaowen Xu, Peiyuan Xu, Tsai-Ling Yang, Xiaoping Yang, Hao-Yu Yang, Junlin Yang, Haojin Yang, Guang Yang, Hongdou Yao, Xujiong Ye, Changchang Yin, Brett Young-Moxon, Jinhua Yu, Xiangyu Yue, Songtao Zhang, Angela Zhang, Kun Zhang, Xue-jie Zhang, Lichi Zhang, Xiaoyue Zhang, Yazhuo Zhang, Lei Zhang, Jian-Guo Zhang, Xiang Zhang, Tianhao Zhang, Sicheng Zhao, Yu Zhao, Xiaomei Zhao, Liang Zhao, Yefeng Zheng, Liming Zhong, Chenhong Zhou, Xiaobing Zhou, Fan Zhou, Hongtu Zhu, Jin Zhu, Ying Zhuge, Weiwei Zong, Jayashree Kalpathy-Cramer, Keyvan Farahani, Christos Davatzikos, Koen van Leemput, Bjoern Menze

This study assesses the state-of-the-art machine learning (ML) methods used for brain tumor image analysis in mpMRI scans, during the last seven instances of the International Brain Tumor Segmentation (BraTS) challenge, i. e., 2012-2018.

Brain Tumor Segmentation Survival Prediction +1

Fully Convolutional Network Ensembles for White Matter Hyperintensities Segmentation in MR Images

2 code implementations14 Feb 2018 Hongwei Li, Gongfa Jiang, Jian-Guo Zhang, Ruixuan Wang, Zhaolei Wang, Wei-Shi Zheng, Bjoern Menze

In this paper, we present a study using deep fully convolutional network and ensemble models to automatically detect such WMH using fluid attenuation inversion recovery (FLAIR) and T1 magnetic resonance (MR) scans.

Data Augmentation

Cannot find the paper you are looking for? You can Submit a new open access paper.