Search Results for author: Yiming Li

Found 80 papers, 49 papers with code

AE-GPT: Using Large Language Models to Extract Adverse Events from Surveillance Reports-A Use Case with Influenza Vaccine Adverse Events

no code implementations28 Sep 2023 Yiming Li, Jianfu Li, Jianping He, Cui Tao

Though Vaccines are instrumental in global health, mitigating infectious diseases and pandemic outbreaks, they can occasionally lead to adverse events (AEs).

Semi-supervised Sound Event Detection with Local and Global Consistency Regularization

no code implementations15 Sep 2023 Yiming Li, Xiangdong Wang, Hong Liu, Rui Tao, Long Yan, Kazushige Ouchi

Then, the local consistency is adopted to encourage the model to leverage local features for frame-level predictions, and the global consistency is applied to force features to align with global prototypes through a specially designed contrastive loss.

Event Detection Sound Event Detection

Audio-free Prompt Tuning for Language-Audio Models

no code implementations15 Sep 2023 Yiming Li, Xiangdong Wang, Hong Liu

Contrastive Language-Audio Pretraining (CLAP) is pre-trained to associate audio features with human language, making it a natural zero-shot classifier to recognize unseen sound categories.

Towards Robust Model Watermark via Reducing Parametric Vulnerability

1 code implementation ICCV 2023 Guanhao Gan, Yiming Li, Dongxian Wu, Shu-Tao Xia

To protect the copyright of DNNs, backdoor-based ownership verification becomes popular recently, in which the model owner can watermark the model by embedding a specific backdoor behavior before releasing it.

BaDExpert: Extracting Backdoor Functionality for Accurate Backdoor Input Detection

no code implementations23 Aug 2023 Tinghao Xie, Xiangyu Qi, Ping He, Yiming Li, Jiachen T. Wang, Prateek Mittal

We present a novel defense, against backdoor attacks on Deep Neural Networks (DNNs), wherein adversaries covertly implant malicious behaviors (backdoors) into DNNs.

One-bit Flip is All You Need: When Bit-flip Attack Meets Model Training

1 code implementation ICCV 2023 Jianshuo Dong, Han Qiu, Yiming Li, Tianwei Zhang, Yuanjie Li, Zeqi Lai, Chao Zhang, Shu-Tao Xia

We propose a training-assisted bit flip attack, in which the adversary is involved in the training stage to build a high-risk model to release.

Towards Stealthy Backdoor Attacks against Speech Recognition via Elements of Sound

1 code implementation17 Jul 2023 Hanbo Cai, Pengcheng Zhang, Hai Dong, Yan Xiao, Stefanos Koffas, Yiming Li

Motivated by these findings, we propose to exploit elements of sound ($e. g.$, pitch and timbre) to design more stealthy yet effective poison-only backdoor attacks.

Backdoor Attack speech-recognition +1

Backdoor Attack with Sparse and Invisible Trigger

1 code implementation11 May 2023 Yinghua Gao, Yiming Li, Xueluan Gong, Shu-Tao Xia, Qian Wang

More importantly, it is not feasible to simply combine existing methods to design an effective sparse and invisible backdoor attack.

Backdoor Attack

Zero-shot Clinical Entity Recognition using ChatGPT

no code implementations29 Mar 2023 Yan Hu, Iqra Ameer, Xu Zuo, Xueqing Peng, Yujia Zhou, Zehan Li, Yiming Li, Jianfu Li, Xiaoqian Jiang, Hua Xu

In this study, we investigated the potential of ChatGPT, a large language model developed by OpenAI, for the clinical named entity recognition task defined in the 2010 i2b2 challenge, in a zero-shot setting with two different prompt strategies.

Language Modelling Large Language Model +3

Collaborative Multi-Object Tracking with Conformal Uncertainty Propagation

no code implementations25 Mar 2023 Sanbao Su, Songyang Han, Yiming Li, Zhili Zhang, Chen Feng, Caiwen Ding, Fei Miao

MOT-CUP demonstrates the importance of uncertainty quantification in both COD and MOT, and provides the first attempt to improve the accuracy and reduce the uncertainty in MOT based on COD through uncertainty propogation.

Autonomous Vehicles Conformal Prediction +5

Among Us: Adversarially Robust Collaborative Perception by Consensus

1 code implementation ICCV 2023 Yiming Li, Qi Fang, Jiamu Bai, Siheng Chen, Felix Juefei-Xu, Chen Feng

This leads to our hypothesize-and-verify framework: perception results with and without collaboration from a random subset of teammates are compared until reaching a consensus.

3D Object Detection Adversarial Defense +2

Defending Against Backdoor Attacks by Layer-wise Feature Analysis

1 code implementation24 Feb 2023 Najeeb Moharram Jebreel, Josep Domingo-Ferrer, Yiming Li

We find out that the feature difference between benign and poisoned samples tends to be maximum at a critical layer, which is not always the one typically used in existing defenses, namely the layer before fully-connected layers.

Backdoor Attack

BackdoorBox: A Python Toolbox for Backdoor Learning

1 code implementation1 Feb 2023 Yiming Li, Mengxi Ya, Yang Bai, Yong Jiang, Shu-Tao Xia

Third-party resources ($e. g.$, samples, backbones, and pre-trained models) are usually involved in the training of deep neural networks (DNNs), which brings backdoor attacks as a new training-phase threat.

Revisiting the Assumption of Latent Separability for Backdoor Defenses

1 code implementation ICLR 2023 Xiangyu Qi, Tinghao Xie, Tinghao_Xie1, Yiming Li, Saeed Mahloujifar, Prateek Mittal

This latent separation is so pervasive that a family of backdoor defenses directly take it as a default assumption (dubbed latent separability assumption), based on which to identify poison samples via cluster analysis in the latent space.

Metabolomics of Aging and Alzheimer's Disease: From Single-Omics to Multi-Omics

no code implementations19 Dec 2022 Yiming Li, Yuan Luo

Aging is a multifactorial process and a key factor of morbidity and mortality.

Untargeted Backdoor Attack against Object Detection

1 code implementation2 Nov 2022 Chengxiao Luo, Yiming Li, Yong Jiang, Shu-Tao Xia

The backdoored model has promising performance in predicting benign samples, whereas its predictions can be maliciously manipulated by adversaries based on activating its backdoors with pre-defined trigger patterns.

Backdoor Attack Image Classification +3

Backdoor Defense via Suppressing Model Shortcuts

1 code implementation2 Nov 2022 Sheng Yang, Yiming Li, Yong Jiang, Shu-Tao Xia

Recent studies have demonstrated that deep neural networks (DNNs) are vulnerable to backdoor attacks during the training process.

backdoor defense

BATT: Backdoor Attack with Transformation-based Triggers

no code implementations2 Nov 2022 Tong Xu, Yiming Li, Yong Jiang, Shu-Tao Xia

The backdoor adversaries intend to maliciously control the predictions of attacked DNNs by injecting hidden backdoors that can be activated by adversary-specified trigger patterns during the training process.

Backdoor Attack

Self-Supervised Visual Place Recognition by Mining Temporal and Feature Neighborhoods

no code implementations19 Aug 2022 Chao Chen, Xinhao Liu, Xuchu Xu, Yiming Li, Li Ding, Ruoyu Wang, Chen Feng

Inspired by noisy label learning, we propose a novel self-supervised framework named \textit{TF-VPR} that uses temporal neighborhoods and learnable feature neighborhoods to discover unknown spatial neighborhoods.

Data Augmentation Representation Learning +1

Black-box Dataset Ownership Verification via Backdoor Watermarking

1 code implementation4 Aug 2022 Yiming Li, Mingyan Zhu, Xue Yang, Yong Jiang, Tao Wei, Shu-Tao Xia

The rapid development of DNNs has benefited from the existence of some high-quality datasets ($e. g.$, ImageNet), which allow researchers and developers to easily verify the performance of their methods.

MOVE: Effective and Harmless Ownership Verification via Embedded External Features

1 code implementation4 Aug 2022 Yiming Li, Linghui Zhu, Xiaojun Jia, Yang Bai, Yong Jiang, Shu-Tao Xia, Xiaochun Cao

In general, we conduct the ownership verification by verifying whether a suspicious model contains the knowledge of defender-specified external features.

Style Transfer

Enhanced Atmospheric Turbulence Resiliency with Successive Interference Cancellation DSP in Mode Division Multiplexing Free-Space Optical Links

no code implementations19 Jul 2022 Yiming Li, Zhaozhong Chen, Zhouyi Hu, David M. Benton, Abdallah A. I. Ali, Mohammed Patel, Martin P. J. Lavery, Andrew D. Ellis

We experimentally demonstrate the enhanced atmospheric turbulence resiliency in a 137. 8 Gbit/s/mode mode-division multiplexing free-space optical communication link through the application of a successive interference cancellation digital signal processing algorithm.

Circumventing Backdoor Defenses That Are Based on Latent Separability

1 code implementation26 May 2022 Xiangyu Qi, Tinghao Xie, Yiming Li, Saeed Mahloujifar, Prateek Mittal

This latent separation is so pervasive that a family of backdoor defenses directly take it as a default assumption (dubbed latent separability assumption), based on which to identify poison samples via cluster analysis in the latent space.

Egocentric Prediction of Action Target in 3D

no code implementations CVPR 2022 Yiming Li, Ziang Cao, Andrew Liang, Benjamin Liang, Luoyao Chen, Hang Zhao, Chen Feng

We are interested in anticipating as early as possible the target location of a person's object manipulation action in a 3D workspace from egocentric vision.

Deep Convolutional Neural Networks for Molecular Subtyping of Gliomas Using Magnetic Resonance Imaging

no code implementations10 Mar 2022 Dong Wei, Yiming Li, Yinyan Wang, Tianyi Qian, Yefeng Zheng

Methods: A DCNN model was developed for the prediction of the five glioma subtypes based on a hierarchical classification paradigm.

V2X-Sim: Multi-Agent Collaborative Perception Dataset and Benchmark for Autonomous Driving

no code implementations17 Feb 2022 Yiming Li, Dekun Ma, Ziyan An, Zixun Wang, Yiqi Zhong, Siheng Chen, Chen Feng

Vehicle-to-everything (V2X) communication techniques enable the collaboration between vehicles and many other entities in the neighboring environment, which could fundamentally improve the perception system for autonomous driving.

Autonomous Driving

Backdoor Defense via Decoupling the Training Process

2 code implementations ICLR 2022 Kunzhe Huang, Yiming Li, Baoyuan Wu, Zhan Qin, Kui Ren

Recent studies have revealed that deep neural networks (DNNs) are vulnerable to backdoor attacks, where attackers embed hidden backdoors in the DNN model by poisoning a few training samples.

backdoor defense Self-Supervised Learning

Few-Shot Backdoor Attacks on Visual Object Tracking

1 code implementation ICLR 2022 Yiming Li, Haoxiang Zhong, Xingjun Ma, Yong Jiang, Shu-Tao Xia

Visual object tracking (VOT) has been widely adopted in mission-critical applications, such as autonomous driving and intelligent surveillance systems.

Autonomous Driving Backdoor Attack +1

Dynamic Scene Graph Generation via Anticipatory Pre-Training

no code implementations CVPR 2022 Yiming Li, Xiaoshan Yang, Changsheng Xu

Humans can not only see the collection of objects in visual scenes, but also identify the relationship between objects.

Graph Generation Scene Graph Generation

Defending against Model Stealing via Verifying Embedded External Features

1 code implementation ICML Workshop AML 2021 Yiming Li, Linghui Zhu, Xiaojun Jia, Yong Jiang, Shu-Tao Xia, Xiaochun Cao

In this paper, we explore the defense from another angle by verifying whether a suspicious model contains the knowledge of defender-specified \emph{external features}.

Style Transfer

CRLB Approaching Pilot-aided Phase and Channel Estimation Algorithm in MIMO Systems with Phase Noise and Quasi-Static Channel Fading

no code implementations5 Dec 2021 Yiming Li, Zhouyi Hu, Andrew Ellis

Our numerical results show that the performance of our phase estimation algorithm is close to the proposed CRLB.

Learning Distilled Collaboration Graph for Multi-Agent Perception

2 code implementations NeurIPS 2021 Yiming Li, Shunli Ren, Pengxiang Wu, Siheng Chen, Chen Feng, Wenjun Zhang

Our approach is validated on V2X-Sim 1. 0, a large-scale multi-agent perception dataset that we synthesized using CARLA and SUMO co-simulation.

3D Object Detection Knowledge Distillation +1

Symmetry-Enhanced Attention Network for Acute Ischemic Infarct Segmentation with Non-Contrast CT Images

1 code implementation11 Oct 2021 Kongming Liang, Kai Han, Xiuli Li, Xiaoqing Cheng, Yiming Li, Yizhou Wang, Yizhou Yu

In this paper, we propose a symmetry enhanced attention network (SEAN) for acute ischemic infarct segmentation.

Regional Adversarial Training for Better Robust Generalization

no code implementations2 Sep 2021 Chuanbiao Song, Yanbo Fan, Yichen Yang, Baoyuan Wu, Yiming Li, Zhifeng Li, Kun He

Adversarial training (AT) has been demonstrated as one of the most promising defense methods against various adversarial attacks.

Simultaneous Semantic and Collision Learning for 6-DoF Grasp Pose Estimation

no code implementations5 Aug 2021 Yiming Li, Tao Kong, Ruihang Chu, Yifeng Li, Peng Wang, Lei LI

In a unified framework, we jointly predict the feasible 6-DoF grasp poses, instance semantic segmentation, and collision information.

Multi-Task Learning Pose Estimation +1

HiFT: Hierarchical Feature Transformer for Aerial Tracking

1 code implementation ICCV 2021 Ziang Cao, Changhong Fu, Junjie Ye, Bowen Li, Yiming Li

Most existing Siamese-based tracking methods execute the classification and regression of the target object based on the similarity maps.

Decision Making

Asymptotic analysis of V-BLAST MIMO for coherent optical wireless communications in Gamma-Gamma turbulence

no code implementations12 Jul 2021 Yiming Li, Chao GAO, Mark S. Leeson, Xiaofeng Li

This paper investigates the asymptotic BER performance of coherent optical wireless communication systems in Gamma-Gamma turbulence when applying the V-BLAST MIMO scheme.

SiamAPN++: Siamese Attentional Aggregation Network for Real-Time UAV Tracking

1 code implementation16 Jun 2021 Ziang Cao, Changhong Fu, Junjie Ye, Bowen Li, Yiming Li

By virtue of the attention mechanism, we conduct a special attentional aggregation network (AAN) consisting of self-AAN and cross-AAN for raising the representation ability of features eventually.

Backdoor Attack in the Physical World

no code implementations6 Apr 2021 Yiming Li, Tongqing Zhai, Yong Jiang, Zhifeng Li, Shu-Tao Xia

We demonstrate that this attack paradigm is vulnerable when the trigger in testing images is not consistent with the one used for training.

Backdoor Attack

Fooling LiDAR Perception via Adversarial Trajectory Perturbation

1 code implementation ICCV 2021 Yiming Li, Congcong Wen, Felix Juefei-Xu, Chen Feng

LiDAR point clouds collected from a moving vehicle are functions of its trajectories, because the sensor motion needs to be compensated to avoid distortions.

3D Object Detection Autonomous Vehicles +2

Predictive Visual Tracking: A New Benchmark and Baseline Approach

2 code implementations8 Mar 2021 Bowen Li, Yiming Li, Junjie Ye, Changhong Fu, Hang Zhao

As a crucial robotic perception capability, visual tracking has been intensively studied recently.

Visual Tracking

Hidden Backdoor Attack against Semantic Segmentation Models

no code implementations6 Mar 2021 Yiming Li, YanJie Li, Yalei Lv, Yong Jiang, Shu-Tao Xia

Deep neural networks (DNNs) are vulnerable to the \emph{backdoor attack}, which intends to embed hidden backdoors in DNNs by poisoning training data.

Autonomous Driving Backdoor Attack +1

An Optimized H.266/VVC Software Decoder On Mobile Platform

no code implementations5 Mar 2021 Yiming Li, Shan Liu, Yu Chen, Yushan Zheng, Sijia Chen, Bin Zhu, Jian Lou

As the successor of H. 265/HEVC, the new versatile video coding standard (H. 266/VVC) can provide up to 50% bitrate saving with the same subjective quality, at the cost of increased decoding complexity.

Targeted Attack against Deep Neural Networks via Flipping Limited Weight Bits

2 code implementations ICLR 2021 Jiawang Bai, Baoyuan Wu, Yong Zhang, Yiming Li, Zhifeng Li, Shu-Tao Xia

By utilizing the latest technique in integer programming, we equivalently reformulate this BIP problem as a continuous optimization problem, which can be effectively and efficiently solved using the alternating direction method of multipliers (ADMM) method.

Backdoor Attack

Multidimensional Information Assisted Deep Learning Realizing Flexible Recognition of Vortex Beam Modes

no code implementations18 Jan 2021 Jiale Zhao, Zijing Zhang, Yiming Li, Longzhu Cen, Yuan Zhao

Recognition of OAM modes unlimited by distance and sign of TC achieved by MIADLFR method can make optical communication and detection by OAM light much more attractive.

Optics Image and Video Processing Medical Physics

Siamese Anchor Proposal Network for High-Speed Aerial Tracking

1 code implementation19 Dec 2020 Changhong Fu, Ziang Cao, Yiming Li, Junjie Ye, Chen Feng

In the domain of visual tracking, most deep learning-based trackers highlight the accuracy but casting aside efficiency.

Visual Tracking Vocal Bursts Intensity Prediction

Backdoor Attack against Speaker Verification

1 code implementation22 Oct 2020 Tongqing Zhai, Yiming Li, Ziqi Zhang, Baoyuan Wu, Yong Jiang, Shu-Tao Xia

We also demonstrate that existing backdoor attacks cannot be directly adopted in attacking speaker verification.

Backdoor Attack Clustering +1

Open-sourced Dataset Protection via Backdoor Watermarking

2 code implementations12 Oct 2020 Yiming Li, Ziqi Zhang, Jiawang Bai, Baoyuan Wu, Yong Jiang, Shu-Tao Xia

Based on the proposed backdoor-based watermarking, we use a hypothesis test guided method for dataset verification based on the posterior probability generated by the suspicious third-party model of the benign samples and their correspondingly watermarked samples ($i. e.$, images with trigger) on the target class.

Image Classification

Rectified Decision Trees: Exploring the Landscape of Interpretable and Effective Machine Learning

no code implementations21 Aug 2020 Yiming Li, Jiawang Bai, Jiawei Li, Xue Yang, Yong Jiang, Shu-Tao Xia

Interpretability and effectiveness are two essential and indispensable requirements for adopting machine learning methods in reality.

BIG-bench Machine Learning Knowledge Distillation

Automatic Failure Recovery and Re-Initialization for Online UAV Tracking with Joint Scale and Aspect Ratio Optimization

1 code implementation10 Aug 2020 Fangqiang Ding, Changhong Fu, Yiming Li, Jin Jin, Chen Feng

Current unmanned aerial vehicle (UAV) visual tracking algorithms are primarily limited with respect to: (i) the kind of size variation they can deal with, (ii) the implementation speed which hardly meets the real-time requirement.

Translation Visual Tracking

DR^2Track: Towards Real-Time Visual Tracking for UAV via Distractor Repressed Dynamic Regression

1 code implementation10 Aug 2020 Changhong Fu, Fangqiang Ding, Yiming Li, Jin Jin, Chen Feng

By repressing the response of distractors in the regressor learning, we can dynamically and adaptively alter our regression target to leverage the tracking robustness as well as adaptivity.

Real-Time Visual Tracking regression

Backdoor Learning: A Survey

1 code implementation17 Jul 2020 Yiming Li, Yong Jiang, Zhifeng Li, Shu-Tao Xia

Backdoor attack intends to embed hidden backdoor into deep neural networks (DNNs), so that the attacked models perform well on benign samples, whereas their predictions will be maliciously changed if the hidden backdoor is activated by attacker-specified triggers.

Backdoor Attack Data Poisoning

Context-Aware Refinement Network Incorporating Structural Connectivity Prior for Brain Midline Delineation

1 code implementation10 Jul 2020 Shen Wang, Kongming Liang, Yiming Li, Yizhou Yu, Yizhou Wang

Nevertheless, there are still great challenges with brain midline delineation, such as the largely deformed midline caused by the mass effect and the possible morphological failure that the predicted midline is not a connected curve.

Targeted Attack for Deep Hashing based Retrieval

2 code implementations ECCV 2020 Jiawang Bai, Bin Chen, Yiming Li, Dongxian Wu, Weiwei Guo, Shu-Tao Xia, En-hui Yang

In this paper, we propose a novel method, dubbed deep hashing targeted attack (DHTA), to study the targeted attack on such retrieval.

Image Retrieval Retrieval +1

Rethinking the Trigger of Backdoor Attack

no code implementations9 Apr 2020 Yiming Li, Tongqing Zhai, Baoyuan Wu, Yong Jiang, Zhifeng Li, Shu-Tao Xia

Backdoor attack intends to inject hidden backdoor into the deep neural networks (DNNs), such that the prediction of the infected model will be maliciously changed if the hidden backdoor is activated by the attacker-defined trigger, while it performs well on benign samples.

Backdoor Attack backdoor defense

Toward Adversarial Robustness via Semi-supervised Robust Training

1 code implementation16 Mar 2020 Yiming Li, Baoyuan Wu, Yan Feng, Yanbo Fan, Yong Jiang, Zhifeng Li, Shu-Tao Xia

In this work, we propose a novel defense method, the robust training (RT), by jointly minimizing two separated risks ($R_{stand}$ and $R_{rob}$), which is with respect to the benign example and its neighborhoods respectively.

Adversarial Defense Adversarial Robustness

Training-Set Distillation for Real-Time UAV Object Tracking

1 code implementation11 Mar 2020 Fan Li, Changhong Fu, Fuling Lin, Yiming Li, Peng Lu

After the establishment of a new slot, the weighted fusion of the previous samples generates one key-sample, in order to reduce the number of samples to be scored.

Visual Object Tracking

Keyfilter-Aware Real-Time UAV Object Tracking

1 code implementation11 Mar 2020 Yiming Li, Changhong Fu, Ziyuan Huang, Yinqiang Zhang, Jia Pan

Correlation filter-based tracking has been widely applied in unmanned aerial vehicle (UAV) with high efficiency.

Object Tracking Simultaneous Localization and Mapping +1

Globally Guided Progressive Fusion Network for 3D Pancreas Segmentation

no code implementations23 Nov 2019 Chaowei Fang, Guanbin Li, Chengwei Pan, Yiming Li, Yizhou Yu

Recently 3D volumetric organ segmentation attracts much research interest in medical image analysis due to its significance in computer aided diagnosis.

Organ Segmentation Pancreas Segmentation

Visual Privacy Protection via Mapping Distortion

1 code implementation5 Nov 2019 Yiming Li, Peidong Liu, Yong Jiang, Shu-Tao Xia

To a large extent, the privacy of visual classification data is mainly in the mapping between the image and its corresponding label, since this relation provides a great amount of information and can be used in other scenarios.

Adversarial Defense via Local Flatness Regularization

no code implementations27 Oct 2019 Jia Xu, Yiming Li, Yong Jiang, Shu-Tao Xia

In this paper, we define the local flatness of the loss surface as the maximum value of the chosen norm of the gradient regarding to the input within a neighborhood centered on the benign sample, and discuss the relationship between the local flatness and adversarial vulnerability.

Adversarial Defense

Augmented Memory for Correlation Filters in Real-Time UAV Tracking

1 code implementation24 Sep 2019 Yiming Li, Changhong Fu, Fangqiang Ding, Ziyuan Huang, Jia Pan

The outstanding computational efficiency of discriminative correlation filter (DCF) fades away with various complicated improvements.

Learning Aberrance Repressed Correlation Filters for Real-Time UAV Tracking

1 code implementation ICCV 2019 Ziyuan Huang, Changhong Fu, Yiming Li, Fuling Lin, Peng Lu

Traditional framework of discriminative correlation filters (DCF) is often subject to undesired boundary effects.

Object Tracking

$t$-$k$-means: A Robust and Stable $k$-means Variant

1 code implementation17 Jul 2019 Yiming Li, Yang Zhang, Qingtao Tang, Weipeng Huang, Yong Jiang, Shu-Tao Xia

$k$-means algorithm is one of the most classical clustering methods, which has been widely and successfully used in signal processing.


Rectified Decision Trees: Towards Interpretability, Compression and Empirical Soundness

no code implementations14 Mar 2019 Jiawang Bai, Yiming Li, Jiawei Li, Yong Jiang, Shu-Tao Xia

How to obtain a model with good interpretability and performance has always been an important research topic.

Knowledge Distillation

Multinomial Random Forest: Toward Consistency and Privacy-Preservation

no code implementations10 Mar 2019 Yiming Li, Jiawang Bai, Jiawei Li, Xue Yang, Yong Jiang, Chun Li, Shu-Tao Xia

Despite the impressive performance of random forests (RF), its theoretical properties have not been thoroughly understood.

General Classification

Semi-Supervised Brain Lesion Segmentation with an Adapted Mean Teacher Model

no code implementations4 Mar 2019 Wenhui Cui, Yanlin Liu, Yuxing Li, Menghao Guo, Yiming Li, Xiuli Li, Tianle Wang, Xiangzhu Zeng, Chuyang Ye

Since unannotated data is generally abundant, it is desirable to use unannotated data to improve the segmentation performance for CNNs when limited annotated data is available.

Image Classification Ischemic Stroke Lesion Segmentation +1

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