检索结果-内蒙古大学图书馆

An attention-guided network for surgical instrument segmentation from endoscopic images

COMPUTERS IN BIOLOGY AND MEDICINE 2022年第PT A期151卷 106216-106216页

作者： Yang, Lei Gu, Yuge Bian, Guibin Liu, Yanhong Zhengzhou Univ Sch Elect & Informat Engn Zhengzhou 450001 Henan Peoples R China Robot Percept & Control Engn Lab Zhengzhou 450001 Henan Peoples R China Chinese Acad Sci Inst Automation State Key Lab Management & Control Complex Syst Beijing 100190 Peoples R China

Accurate surgical instrument segmentation can provide the precise location and pose information to the surgeons, assisting the surgeon to accurately judge the follow-up operation during the robot-assisted surgery procedures. Due to strong context extraction ability, there have been significant advances in research of automatic surgical instrument segmentation, especially U-Net and its variant networks. However, there are still some problems to affect segmentation accuracy, like insufficient processing of local features, class imbalance issue, etc. To deal with these problems, with the typical encoder-decoder structure, an effective surgical instrument segmentation network is proposed for providing an end-to-end detection scheme. Specifically, aimed at the problem of insufficient processing of local features, the residual path is introduced for the full feature extraction to strengthen the backward propagation of low-level features. Further, to achieve feature enhancement of local feature maps, a non-local attention block is introduced to insert into the bottleneck layer to acquire global contexts. Besides, to highlight the pixel areas of the surgical instruments, a dual -attention module (DAM) is introduced to make full use of the high-level features extracted from decoder unit and the low-level features delivered by the encoder unit to acquire the attention features and suppress the irrelevant features. To prove the effectiveness and superiority of the proposed segmentation model, experiments are conducted on two public surgical instrument segmentation data sets, including Kvasir-instrument set and Endovis2017 set, which could acquire a 95.77% Dice score and 92.13% mIOU value on Kvasir-instrument set, and simultaneously reach 95.60% Dice score and 92.74% mIOU value on Endovis2017 set respectively. Experimental results show that the proposed segmentation model realizes a superior performance on surgical instruments in comparison to other advanced models, which could

关键词： Surgical instruments Deep learning Semantic segmentation Residual network Dual attention mechanism

来源：评论

学校读者我要写书评

暂无评论

Structure attention co-training neural network for neovascularization segmentation in intravascular optical coherence tomography

引用

MEDICAL PHYSICS 2022年第3期49卷 1723-1738页

作者： Wu, Xiangjun Zhang, Yingqian Zhang, Peng Hui, Hui Jing, Jing Tian, Feng Jiang, Jingying Yang, Xin Chen, Yundai Tian, Jie Beihang Univ Beijing Adv Innovat Ctr Big Data Based Precis Med Sch Med & Engn Beijing Peoples R China Inst Automat CAS Key Lab Mol Imaging State Key Lab Management & Control Complex Syst Beijing Peoples R China Beijing Key Lab Mol Imaging Beijing Peoples R China Peoples Liberat Army Gen Hosp Dept Cardiol Med Ctr 6 Beijing 100853 Peoples R China Beijing Jiaotong Univ Sch Comp & Informat Technol Dept Biomed Engn Beijing Peoples R China Univ Chinese Acad Sci Beijing Peoples R China Southern Med Univ Guangzhou Peoples R China Jinan Univ Zhuhai Peoples Hosp Zhuhai Precis Med Ctr Zhuhai Peoples R China

Purpose To development and validate a neovascularization (NV) segmentation model in intravascular optical coherence tomography (IVOCT) through deep learning methods. Methods and materials A total of 1950 2D slices of 70 IVOCT pullbacks were used in our study. We randomly selected 1273 2D slices from 44 patients as the training set, 379 2D slices from 11 patients as the validation set, and 298 2D slices from the last 15 patients as the testing set. Automatic NV segmentation is quite challenging, as it must address issues of speckle noise, shadow artifacts, high distribution variation, etc. To meet these challenges, a new deep learning-based segmentation method is developed based on a co-training architecture with an integrated structural attention mechanism. Co-training is developed to exploit the features of three consecutive slices. The structural attention mechanism comprises spatial and channel attention modules and is integrated into the co-training architecture at each up-sampling step. A cascaded fixed network is further incorporated to achieve segmentation at the image level in a coarse-to-fine manner. Results Extensive experiments were performed involving a comparison with several state-of-the-art deep learning-based segmentation methods. Moreover, the consistency of the results with those of manual segmentation was also investigated. Our proposed NV automatic segmentation method achieved the highest correlation with the manual delineation by interventional cardiologists (the Pearson correlation coefficient is 0.825). Conclusion In this work, we proposed a co-training architecture with an integrated structural attention mechanism to segment NV in IVOCT images. The good agreement between our segmentation results and manual segmentation indicates that the proposed method has great potential for application in the clinical investigation of NV-related plaque diagnosis and treatment.

关键词： co-training IVOCT neovascularization segmentation structural attention mechanism

来源：评论

学校读者我要写书评

暂无评论

A modified YOLOv4 detection method for a vision-based underwater garbage cleaning robot

引用

Frontiers of Information Technology & Electronic Engineering 2022年第8期23卷 1217-1228页

作者： Manjun TIAN Xiali LI Shihan KONG Licheng WU Junzhi YU First Research Institute of the Ministry of Public Security of PRC Beijing 100048China School of Information Engineering Minzu University of ChinaBeijing 100081China Department of Advanced Manufacturing and Robotics College of EngineeringPeking UniversityBeijing 100871China State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of SciencesBeijing 100190China

To tackle the problem of aquatic environment pollution,a vision-based autonomous underwater garbage cleaning robot has been developed in our *** propose a garbage detection method based on a modified YOLOv4,allowing high-speed and high-precision object ***,the YOLOv4 algorithm is chosen as a basic neural network framework to perform object *** the purpose of further improvement on the detection accuracy,YOLOv4 is transformed into a four-scale detection *** improve the detection speed,model pruning is applied to the new *** virtue of the improved detection methods,the robot can collect garbage *** detection speed is up to 66.67 frames/s with a mean average precision(mAP)of 95.099%,and experimental results demonstrate that both the detection speed and the accuracy of the improved YOLOv4 are excellent.

关键词： Object detection Aquatic environment Garbage cleaning robot Modified YOLOv4

来源：评论

学校读者我要写书评

暂无评论

Design of a Miniature Underwater Angle-of-Attack Sensor and Its Application to a Self-Propelled Robotic Fish

引用

IEEE JOURNAL OF OCEANIC ENGINEERING 2020年第4期45卷 1295-1307页

作者： Yu, Junzhi Wang, Tianzhu Wu, Zhengxing Tan, Min Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst Beijing 100190 Peoples R China Peking Univ Dept Mech & Engn Sci BIC ESAT State Key Lab Turbulence & Complex SystColl Engn Beijing 100871 Peoples R China Univ Chinese Acad Sci Beijing 100049 Peoples R China

This article proposes a miniature underwater angle-of-attack (AoA) sensor appropriate to self-propelled fin-actuated underwater robots, featuring real-time measurement of AoA relative to the incoming flow. Specifically, the developed sensor adopts a vane-rotating structure with a high-performance Hall chip that is responsible for detection of the angular deviation. Meanwhile, the Hall-effect-based acquisition scheme endows the device with several features, including low rotational damping, to satisfy underwater usage requirements. Another contribution is that an AoA model is derived to allow the real-time acquisition of AoA at the trailing edge of the caudal fin assumed in a quiescent flow. Based on this model, the AoA profile is obtained as theoretical reference with only the control laws required. Finally, the performance of the numerical model and the developed sensor are investigated through aquatic experiments assisted by a global visual measurement system. The experimental results demonstrate that the acquired AoA possesses over 0.97 Parson correlation coefficient with the theoretical data, verifying the effectiveness of the proposed mechatronic design. The developed AoA sensor and its application to robotic fish could provide potential assistance for the flow control and hydrodynamic optimization of fin-actuated underwater robots.

关键词： Robot sensing systems Real-time systems Propulsion Magnetomechanical effects Magnetic analysis Sea measurements Angle of attack (AoA) angle sensor measurement robotic fish underwater

来源：评论

学校读者我要写书评

暂无评论

A Parallel Flexible Manufacturing System: Smart Manufacturing in the Age of Smart Industry

引用

IEEE systems MAN AND CYBERNETICS MAGAZINE 2023年第4期9卷 69-76页

作者： Hu, Bin Zhang, XiaoDong Liu, XinJie Ding, TianJu Dong, XiSong Chinese Acad Sci Beijing Engn Res Ctr Intelligent Syst & Technol Inst Automat Beijing 100190 Peoples R China Chinese Acad Sci State Key Lab Management & Control Complex Syst Inst Automat Beijing 100190 Peoples R China Yantai Inst Technol Sch Informat Engn Dept Software Engn Yantai 264025 Peoples R China Yantai Univ Engn Yantai 264005 Peoples R China Yantai Inst Technol Yantai 264025 Peoples R China IEEE Piscataway NJ USA

This article proposes a parallel flexible manufacturing system (FMS), which is divided into three subparallel systems, including a parallel manufacturing system, a parallel inspection system, and a parallel loading-unloading system. By building a chess parallel manufacturing production line, the lightweight practice of a parallel FMS is completed. Based on the parallel system ACP idea, the parallel FMS can realize the agility advantage of flexible manufacturing to quickly respond to diverse needs;realize the ability to quickly correct defective products;and predict and optimize the production process through the analysis and modeling of production data, reducing the product quality defect rate. This article also proposes the concept of parallel flexible manufacturing triplets, adding a microphysical world to the artificial world and the physical world, highlighting the rapid iteration characteristics of flexible manufacturing.

关键词： Industries Frequency modulation Production Predictive models Inspection Product design Quality assessment

来源：评论

学校读者我要写书评

暂无评论

Marker or Markerless? Mode-Switchable Optical Tactile Sensing for Diverse Robot Tasks

arXiv

引用

arXiv 2024年

作者： Ou, Ni Chen, Zhuo Luo, Shan The State Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing Institute of Technology Beijing100081 China The Robot Perception Lab. Centre for Robotics Research Department of Engineering King’s College London LondonWC2R 2LS United Kingdom

Optical tactile sensors play a pivotal role in robot perception and manipulation tasks. The membrane of these sensors can be painted with markers or remain markerless, enabling them to function in either marker or markerless mode. However, this uni-modal selection means the sensor is only suitable for either manipulation or perception tasks. While markers are vital for manipulation, they can also obstruct the camera, thereby impeding perception. The dilemma of selecting between marker and markerless modes presents a significant obstacle. To address this issue, we propose a novel mode-switchable optical tactile sensing approach that facilitates transitions between the two modes. The marker-to-markerless transition is achieved through a generative model, whereas its inverse transition is realized using a sparsely supervised regressive model. Our approach allows a single-mode optical sensor to operate effectively in both marker and markerless modes without the need for additional hardware, making it well-suited for both perception and manipulation tasks. Extensive experiments validate the effectiveness of our method. For perception tasks, our approach decreases the number of categories that include misclassified samples by 2 and improves contact area segmentation IoU by 3.53%. For manipulation tasks, our method attains a high success rate of 92.59% in slip detection. Code, dataset and demo videos are available at the project website https://***/Marker-Markerless-Transition/ Copyright © 2024, The Authors. All rights reserved.

关键词： Tactile sensors

来源：评论

学校读者我要写书评

暂无评论

Exploring Token-Level Augmentation in Vision Transformer for Semi-Supervised Semantic Segmentation

arXiv

引用

arXiv 2025年

作者： Zhang, Dengke Tang, Quan Liu, Fagui Mei, Haiqing Chen, C.L. Philip The School of Computer Science and Engineering South China University of Technology Guangzhou510006 China The Department of New Network Pengcheng Laboratory Shenzhen518000 China The China Tobacco Guangdong Industrial Corporation Guangzhou510385 China State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100080 China

Semi-supervised semantic segmentation has witnessed remarkable advancements in recent years. However, existing algorithms are based on convolutional neural networks and directly applying them to Vision Transformers poses certain limitations due to conceptual disparities. To this end, we propose TokenMix, a data augmentation technique specifically designed for semi-supervised semantic segmentation with Vision Transformers. TokenMix aligns well with the global attention mechanism by mixing images at the token level, enhancing learning capability for contextual information among image patches. We further incorporate image augmentation and feature augmentation to promote the diversity of augmentation. Moreover, to enhance consistency regularization, we propose a dual-branch framework where each branch applies image and feature augmentation to the input image. We conduct extensive experiments across multiple benchmark datasets, including Pascal VOC 2012, Cityscapes, and COCO. Results suggest that the proposed method outperforms state-of-the-art algorithms with notably observed accuracy improvement, especially under limited fine annotations. Copyright © 2025, The Authors. All rights reserved.

关键词：

来源：评论

学校读者我要写书评

暂无评论

VGPN: 6-DoF Grasp Pose Detection Network Based on Hough Voting

VGPN: 6-DoF Grasp Pose Detection Network Based on Hough Voti...

引用

IEEE/RSJ International Conference on Intelligent Robots and systems (IROS)

作者： Zheng, Liming Cai, Yinghao Lu, Tao Wang, Shuo Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst Beijing 100190 Peoples R China Univ Chinese Acad Sci Sch Artificial Intelligence Beijing 101408 Peoples R China Chinese Acad Sci HKISI CAS Hong Kong Inst Sci & Innovat Ctr Artificial Intelligence & Robot CAIR Hong Kong Peoples R China

ISBN: (数字)9781665479271

ISBN: (纸本)9781665479271

In this paper, we propose a novel Voting based Grasp Pose Network (VGPN) to detect 6-DoF grasps in cluttered scenes. The motivation of this paper is that local object geometry can provide useful clues about where the object can be grasped. Generated by the sampled seed points from raw point cloud, the votes allow seed points in different object regions to contribute to locations where the object can be grasped. Geometric features from various local regions are aggregated to generate grasps in a more confident and dense space, which enables grasp prediction utilizing more global context features. The search space of grasp pose detection is also greatly reduced. Experimental results on both simulation and real-world environments show that our proposed method outperforms state-of-the-art approaches in terms of both success rate and coverage of the ground truth grasps. The objects can be grasped with fewer attempts which is critical in real-world applications.

关键词： Point cloud compression Training Geometry Pipelines Green products Grasping Collision avoidance

来源：评论

学校读者我要写书评

暂无评论

TR-GAN: Multi-Session Future MRI Prediction With Temporal Recurrent Generative Adversarial Network

引用

IEEE TRANSACTIONS ON MEDICAL IMAGING 2022年第8期41卷 1925-1937页

作者： Fan, Chen-Chen Peng, Liang Wang, Tian Yang, Hongjun Zhou, Xiao-Hu Ni, Zhen-Liang Wang, Guan'an Chen, Sheng Zhou, Yan-Jie Hou, Zeng-Guang Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst Beijing 100190 Peoples R China Univ Chinese Acad Sci Sch Artificial Intelligence Beijing 100049 Peoples R China Commun Univ China Neurosci & Intelligent Media Inst Beijing 100024 Peoples R China CAS Ctr Excellence Brain Sci & Intelligence Techn Beijing 100190 Peoples R China Macau Univ Sci & Technol CASIA MUST Joint Lab Intelligence Sci & Technol Inst Syst Engn Macau 999078 Peoples R China

Magnetic Resonance Imaging (MRI) has been proven to be an efficient way to diagnose Alzheimer's disease (AD). Recent dramatic progress on deep learning greatly promotes the MRI analysis based on data-driven CNN methods using a large-scale longitudinal MRI dataset. However, most of the existing MRI datasets are fragmented due to unexpected quits of volunteers. To tackle this problem, we propose a novel Temporal Recurrent Generative Adversarial Network (TR-GAN) to complete missing sessions of MRI datasets. Unlike existing GAN-based methods, which either fail to generate future sessions or only generate fixed-length sessions, TR-GAN takes all past sessions to recurrently and smoothly generate future ones with variant length. Specifically, TR-GAN adopts recurrent connection to deal with variant input sequence length and flexibly generate future variant sessions. Besides, we also design a multiple scale & location (MSL) module and a SWAP module to encourage the model to better focus on detailed information, which helps to generate high-quality MRI data. Compared with other popular GAN architectures, TR-GAN achieved the best performance in all evaluation metrics of two datasets. After expanding the Whole MRI dataset, the balanced accuracy of AD vs. cognitively normal (CN) vs. mild cognitive impairment (MCI) and stable MCI vs. progressive MCI classification can be increased by 3.61% and 4.00%, respectively.

关键词： Magnetic resonance imaging Generative adversarial networks Task analysis Three-dimensional displays Training Generators Data models Alzheimer's disease magnetic resonance imaging generative adversarial network

来源：评论

学校读者我要写书评

暂无评论

TASF: Terrestrial-Aerial Synergistic Framework for a New Generation of Intelligent Transportation

TASF: Terrestrial-Aerial Synergistic Framework for a New Gen...

引用

International Conference on Intelligent Transportation

作者： Cong Wang Dujun Nie Ruijun Zhang Siyu Teng Long Chen State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of Automation Chinese Academy of Sciences Beijing China School of Artificial Intelligence University of Chinese Academy of Sciences Beijing China Hong Kong Baptist University Kowloon Hong Kong China WAYTOUS Inc. Beijing China State Key Laboratory of Multimodal Artificial Intelligence Systems and the State Key Laboratory of Management and Control for Complex Systems Chinese Academy of Sciences Beijing China Guangdong Laboratory of Artificial Intelligence and Digital Economy (SZ) Shenzhen China Institute of Artificial Intelligence and Robotics Xi'an Jiaotong University Xi'an China

ISBN: (数字)9798331505929

ISBN: (纸本)9798331505936

Terrestrial-Aerial Synergistic Framework (TASF) represents a novel approach to intelligent transportation, integrating terrestrial and aerial vehicles to enhance urban transportation efficiency and capacity. In this paper, we offer an in-depth analysis of TASF, emphasizing its innovative applications in urban transportation, parcel delivery, and emergency response services. TASF incorporates a five-layer architecture comprising perception, communication, planning, control, and interaction. With the five-layer architecture, TASF can achieve effective collaboration among terrestrial and aerial vehicles, encompassing two principal features: terrestrial-aerial synergistic parallel perception and multi-agent parallel management. Parallel perception results from fusing Bird's Eye View (BEV) representations from Unmanned Aerial Vehicles (UAVs) and Unmanned Ground Vehicles (UGVs), whereas decentralized multi-agent management employs foundational models to enhance decision-making capabilities. Additionally, we consider challenges and potential solutions related to TASF, including safety, reliability, energy efficiency, management and integration. TASF marks a paradigm-shifting leap in the realm of intelligent transportation systems, providing a scalable and efficacious solution tailored to the dynamic requirements of urban mobility and emergency services.

关键词： Foundation models Urban areas Decision making Transportation Emergency services Land vehicles Energy efficiency Planning Reliability Vehicle dynamics

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：