检索结果-内蒙古大学图书馆

An Interpretable CNN for the Segmentation of the Left Ventricle in Cardiac MRI by Real-Time Visualization

computer Modeling in engineering & sciences 2023年第5期135卷 1571-1587页

作者： Jun Liu Geng Yuan Changdi Yang Houbing Song Liang Luo Robotics Institute School of Computer ScienceCarnegie Mellon UniversityPittsburghPA15217USA Department of Electrical&Computer Engineering College of EngineeringNortheastern UniversityBostonMA02115USA Security and Optimization for Networked Globe Laboratory(SONG Lab) Embry-Riddle Aeronautical UniversityDaytona BeachFL32114USA School of Computer Science and Engineering University of Electronic Science and Technology of ChinaChengdu610054China

The interpretability of deep learning models has emerged as a compelling area in artificial intelligence *** safety criteria for medical imaging are highly stringent,and models are required for an ***,existing convolutional neural network solutions for left ventricular segmentation are viewed in terms of inputs and ***,the interpretability of CNNs has come into the *** medical imaging data are limited,many methods to fine-tune medical imaging models that are popular in transfer models have been built using massive public Image Net datasets by the transfer learning ***,this generates many unreliable parameters and makes it difficult to generate plausible explanations from these *** this study,we trained from scratch rather than relying on transfer learning,creating a novel interpretable approach for autonomously segmenting the left ventricle with a cardiac *** enhanced GPU training system implemented interpretable global average pooling for graphics using deep *** deep learning tasks were *** included data management,neural network architecture,and *** system monitored and analyzed the gradient changes of different layers with dynamic visualizations in real-time and selected the optimal deployment *** results demonstrated that the proposed method was feasible and efficient:the Dice coefficient reached 94.48%,and the accuracy reached 99.7%.It was found that no current transfer learning models could perform comparably to the ImageNet transfer learning *** model is lightweight and more convenient to deploy on mobile devices than transfer learning models.

关键词： Interpretable graphics training visualization image segmentation left ventricle CNNs global average pooling

来源：评论

学校读者我要写书评

暂无评论

A novel medical image data protection scheme for smart healthcare system

引用

CAAI Transactions on Intelligence Technology 2024年第4期9卷 821-836页

作者： Mujeeb Ur Rehman Arslan Shafique Muhammad Shahbaz Khan Maha Driss Wadii Boulila Yazeed Yasin Ghadi Suresh Babu Changalasetty Majed Alhaisoni Jawad Ahmad School of Computer Science and Informatics Cyber Technology InstituteDe Montfort UniversityLeicesterUK Department of Biomedical Engineering University of GlasgowGlasgowUK School of Computing Engineering and the Built EnvironmentEdinburgh Napier UniversityEdinburghUK Robotics and Internet‐of‐Things Laboratory Prince Sultan UniversityRiyadhSaudi Arabia Department of Computer Science Al Ain UniversityAl AinUnited Arab Emirates Department of Computer Engineering College of Computer Science King Khalid UniversityAbhaSaudi Arabia Computer Sciences Department College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityRiyadhSaudi Arabia

The Internet of Multimedia Things(IoMT)refers to a network of interconnected multimedia devices that communicate with each other over the ***,smart healthcare has emerged as a significant application of the IoMT,particularly in the context of knowledge‐based learning *** healthcare systems leverage knowledge‐based learning to become more context‐aware,adaptable,and auditable while maintain-ing the ability to learn from historical *** smart healthcare systems,devices capture images,such as X‐rays,Magnetic Resonance *** security and integrity of these images are crucial for the databases used in knowledge‐based learning systems to foster structured decision‐making and enhance the learning abilities of ***,in knowledge‐driven systems,the storage and transmission of HD medical images exert a burden on the limited bandwidth of the communication channel,leading to data trans-mission *** address the security and latency concerns,this paper presents a lightweight medical image encryption scheme utilising bit‐plane decomposition and chaos *** results of the experiment yield entropy,energy,and correlation values of 7.999,0.0156,and 0.0001,*** validates the effectiveness of the encryption system proposed in this paper,which offers high‐quality encryption,a large key space,key sensitivity,and resistance to statistical attacks.

关键词： data analysis medical image processing security

来源：评论

学校读者我要写书评

暂无评论

Scale Adaptive Skip-ASP Pixel Voting Network for Monocular 6D Object Pose Estimation 42

Scale Adaptive Skip-ASP Pixel Voting Network for Monocular 6...

引用

42nd Chinese Control Conference, CCC 2023

作者： Wu, Li Ma, Xin Center for Robotics School of Control Science and Engineering Shandong University Jinan250061 China

ISBN: (纸本)9789887581543

Estimating the 6D object pose from an RGB image is a challenging task in computer vision. While keypoint-based methods have recently demonstrated promising results, they are still inferior when dealing with small objects in the image. Aiming at this problem, we perform an in-depth pose error analysis on the keypoint-based methods and propose a Scale Adaptive Skip-ASP Pixel Voting Network (SASA-PVNet), which adaptively scales small objects in the input image to a suitable size and scales the output 2D keypoints back to the original input image during PnP. We also design a Skip-ASP module between the encoder and decoder in the framework to reduce the effects of distortion and blur caused by scaling the input image through multi-scale information fusion. Experiments demonstrate that our method outperforms the state-of-the-art on the LINEMOD dataset by a large margin and obtains competitive results on the Occlusion LINEMOD dataset. © 2023 Technical Committee on Control Theory, Chinese Association of Automation.

关键词： Pixels

来源：评论

学校读者我要写书评

暂无评论

A hierarchical multi-color spraying path planning with clustered traveling salesman problem 41

A hierarchical multi-color spraying path planning with clust...

引用

第41届中国控制会议

作者： Yifei Shan Xin Ma Center for Robotics School of Control Science and EngineeringShandong University

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

This paper presents a new method to solve the problem of multi-color spraying path *** method uses hierarchical optimization strategy to solve multi-color spraying path planning *** problem is broken down into two smaller subproblems:the upper-level clustered traveling salesman problem(CTSP) and the lower-level route case selection *** solve the problem of upper-level CTSP,we use genetic algorithm(GA) with multi-subpopulation initialization(MSI) *** solve the problem of lower-level route case selection,we use a greedy method(GM) and a tabu search(TS)*** blocks of the same color must be continuously *** gun returns to its starting point after completing the *** goal of multi-color spraying path planning is to find a minimum cost path for a gun to move between color blocks.

关键词： Multi-color spraying path planning Hierarchical optimization CTSP

来源：评论

学校读者我要写书评

暂无评论

Modulating surface cation vacancies of nickel-cobalt oxides as efficient catalysts for lithium-oxygen batteries

引用

Journal of Materials science & Technology 2023年第8期139卷 147-155页

作者： Yuan Yang Linna Dai Jianwei Qiu Zhibiao Hu Peng Wang Yongtao Zhao Huanhuan Guo Pengchao Si Rui Song Center for Robotics School of Control Science and EngineeringShandong UniversityJinan 250061China Research Center for Carbon Nanomaterials Key Laboratory for Liquid-Solid Structural Evolution and Processing of Materials(Ministry of Education)School of Materials Science and EngineeringShandong UniversityJinan 250061China School of Mechanical Electrical and Information EngineeringShandong UniversityWeihai 264209China College of Chemistry and Chemical Engineering Xingtai UniversityXingtai 054001China

Rechargeable lithium-oxygen batteries(LOBs)have received incremental attention owing to their high energy density and applicability to mobile devices and electric ***,the lack of robust,low-cost,and environmentally benign bifunctional catalysts is a major impediment to the commercial *** introduction of vacancies is one of the effective strategies to enhance the performance of cathode catalysts for lithium-oxygen batteries,but the preparation is *** this work,needle-like microsphere cathode catalysts of nickel-cobalt oxide containing cationic vacancies are constructed by controlling the annealing *** is demonstrated that the presence of cationic vacancies can modulate the electronic structure of the catalyst,reduce the energy barrier for the oxygen electrode re-action,meanwhile enhance the bifunctional catalytic ***,the nickel-cobalt oxide-based LOB with cationic vacancies exhibits large specific capacity(12,205 mAh g^(-1)at 200 mA g^(-1))and good *** work provides worthwhile insight into the formation and catalytic enhancement mech-anism of transition metal oxide catalysts with cationic vacancies,and to some extent,the creation of efficient and low-cost oxygen electrocatalysts for LOBs.

关键词： Li-O_(2)batteries Metal oxides Cation vacancies Catalytic kinetic

来源：评论

学校读者我要写书评

暂无评论

Driving Scene Understanding with Traffic Scene-Assisted Topology Graph Transformer 24

Driving Scene Understanding with Traffic Scene-Assisted Topo...

引用

32nd ACM International Conference on Multimedia, MM 2024

作者： Rong, Fu Peng, Wenjin Lan, Meng Zhang, Qian Zhang, Lefei National Engineering Research Center for Multimedia Software School of Computer Science Wuhan University Wuhan China School of Cyber Science and Engineering Wuhan University Wuhan China Hong Kong University of Science and Technology Hong Kong Hong Kong Horizon Robotics Beijing China National Engineering Research Center for Multimedia Software School of Computer Science Wuhan University Hubei Luojia Laboratory Wuhan China

ISBN: (纸本)9798400706868

Driving scene topology reasoning aims to understand the objects present in the current road scene and model their topology relationships to provide guidance information for downstream tasks. Previous approaches fail to adequately facilitate interactions among traffic objects and neglect to incorporate scene information into topology reasoning, thus limiting the comprehensive exploration of potential correlations among objects and diminishing the practical significance of the reasoning results. Besides, the lack of constraints on lane direction may introduce erroneous guidance information and lead to a decrease in topology prediction accuracy. In this paper, we propose a novel topology reasoning framework, dubbed TSTGT, to address these issues. Specifically, we design a divide-and-conquer topology graph Transformer to respectively infer the lane-lane and lane-traffic topology relationships, which can effectively aggregate the local and global object information in the driving scene and facilitate the topology relationship learning. Additionally, a traffic scene-assisted reasoning module is devised and combined with the topology graph Transformer to enhance the practical significance of lane-traffic topology. In terms of lane detection, we develop a point-wise matching strategy to infer lane centerlines with correct directions, thereby improving the topology reasoning accuracy. Extensive experimental results on Openlane-V2 benchmark validate the superiority of our TSTGT over state-of-the-art methods and the effectiveness of our proposed modules. The code is available at https://***/rongfu-dsb/TSTGT. © 2024 ACM.

关键词： Graph theory

来源：评论

学校读者我要写书评

暂无评论

Mechanically driven assembly of biomimetic 2D-material microtextures with bioinspired multifunctionality

引用

Nano Research 2024年第2期17卷 663-678页

作者： Yang Li Lin Jing Joshua M.Little Haochen Yang Tsai-Chun Chung Po-Yen Chen Department of Chemical and Biomolecular Engineering University of MarylandCollege ParkMD 20740USA Maryland Robotics Center University of MarylandCollege ParkMD 20742USA School of Materials Science and Engineering Nanyang Technological University50 Nanyang AvenueSingapore 639798Singapore

Nature provides a wealth of bio-inspiration for advanced material *** various nanomaterials into biomimetic microtextures with bioinspired functionalities has spurred increasing research interests and facilitated technological advances in various *** recent years,two-dimensional materials(2DMs)have emerged as important building block units in the biomimicry field due to their distinct chemical,physical,electrical,electrochemical,and catalytic *** this review article,various mechanically driven assembly approaches are summarized to fabricate various genealogies of biomimetic 2DM microtextures with bio-inspired ***,sequential deformation strategies are discussed to programmably construct higher dimensional 2DM microtextures,ranging from wrinkles/crumples(one-time deformation)to multiscale hierarchies(multiple deformations).Next,the current progress using higher dimensional 2DM microtextures to imitate different biological structures and/or induce bio-inspired multifunctionality is systematically *** showcases of bio-inspiration and biomimicry using different 2DM nanosheets are highlighted:(1)wrinkle patterns of an earthworm that spur the design of strain sensors with programmable working ranges and sensitivities,(2)wrinkle appearance of a Shar-Pei dog that motivates the fabrication of stretchable energy storage devices,(3)hierarchical scale textures of a desert lizard that inspire cation-induced gelation platforms for 2DM aerogels,and(4)wrinkle skin of an elephant that influences the development of 2DM protective skin for soft ***,challenges and future opportunities of adopting 2DM nanosheets to assemble biomimetic microstructures with synergistic functionalities are discussed.

关键词： two-dimensional(2D)materials mechanically driven assembly biomimetic microtextures functional nanocomposite bio-inspired multifunctionality

来源：评论

学校读者我要写书评

暂无评论

ViT-SENet-Tom: machine learning-based novel hybrid squeeze–excitation network and vision transformer framework for tomato fruits classification

引用

Neural Computing and Applications 2025年第9期37卷 6583-6600页

作者： Swapno, S M Masfequier Rahman Nobel, S. M. Nuruzzaman Islam, Md Babul Bhattacharya, Pronaya Mattar, Ebrahim A. Department of CSE Bangladesh University of Business and Technology Dhaka1216 Bangladesh Department of Computer Modeling Electronic and System Engineering UNICAL Rende Italy Department of Computer Science and Engineering Amity School of Engineering and Technology and Research and Innovation Cell Amity University West Bengal Kolkata India Robotics - Cybernetic College of Engineering University of Bahrain Manama Bahrain

Tomatoes are essential fruits in numerous nations for their vast demand. It is very important to maintain the freshness of tomatoes. One of the primary challenges in the recent culinary landscape is accurately identifying healthy tomatoes while effectively eliminating damaged or rejected ones. Existing approaches employ various strategies for categorizing tomato fruit, but they often suffer from inaccuracies, slow detection, and suboptimal performance. Thus, motivated by this gap, in this paper, we propose a novel machine learning (ML) framework, ViT-SENet-Tom, which is a hybrid vision transformer (ViT) model with squeeze and excitation (SENet) block network for fast, accurate, and efficient tomato fruit classification. The framework works on three tomato classes, respectively, the ripe, unripe, and reject. In developing the proposed model, we utilized advanced and newly designed layers and functions. This integration created a more complex and sophisticated neural network, significantly enhancing efficiency and contributing to the model’s novelty. Our chosen dataset was small initially, but we implemented augmentation techniques to increase its size. This approach made our system more reliable, efficient, and effective. The hybrid ViT-SENet framework employs encoders and self-attention networks with squeeze and excitation channel functions to allow precise, robust, fast, and efficient tomato classification. In simulation, the framework achieves a training accuracy of 99.87% and validation accuracy of 93.87%, indicating the precise classification of tomatoes. Besides, this work tests accuracy using fivefold cross-validation. The highest accuracy seen at fold-5 is 99.90%. These testing results demonstrate the efficacy of the proposed framework in real-deployment scenarios. The implementation has the potential to provide enhanced and more sustainable food security and safety in future. © The Author(s) 2025.

关键词： Fruits

来源：评论

学校读者我要写书评

暂无评论

Development of Detection Lung Disease Stand Alone System Based on Convolutional Neural Network (CNN) 7

Development of Detection Lung Disease Stand Alone System Bas...

引用

7th International Conference of computer and Informatics engineering, IC2IE 2024

作者： Liewarnata, Edgar Caesar Mariana, Yosica Tan, Sofyan Liawatimena, Suryadiputra Astuti, Winda Bina Nusantara University Binus Aso School of Engineering Automotive and Robotics Program Computer Engineering Department Jakarta11480 Indonesia Bina Nusantara University Binus Aso School of Engineering Product Design Program Industrial Engineering Department Jakarta11480 Indonesia Bina Nusantara University Binus Graduate Program - Master of Computer Science Automotive and Robotics Program Computer Engineering Department Binus Aso School of Engineering Computer Science Department Jakarta11480 Indonesia

ISBN: (纸本)9798331505530

Lung disease, especially Tuberculosis (TBC), placed the highest death rate in Indonesia. Tuberculosis (TB) in Indonesia is ranked second after India. Therefore, it is important to reduce or early detection of the lung disease, to prevent this disease and speed up handling. The system can recognize the disease lung identification, and the system applied as standalone system. In this work, the Convolutional Neural Network (CNN) approach for identifying diseases lung identification is proposed. The Mel Frequency Cepstral Coefficient (MFCC) applied to process the stethoscope sounds which will used as input to the CNN. The performance of the proposed system has been investigated and resulted. The accuracy of 99% and 98%, for training and testing accuracy respectively. Furthermore, the system accurately detects lung diseases identification. © 2024 IEEE.

关键词： Lung cancer

来源：评论

学校读者我要写书评

暂无评论

Local Region Frequency Guided Dynamic Inconsistency Network for Deepfake Video Detection

引用

Big Data Mining and Analytics 2024年第3期7卷 889-904页

作者： Pengfei Yue Beijing Chen Zhangjie Fu Engineering Research Center of Digital Forensics affiliated with Ministry of Education School of Computer Science and also with Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology(CICAEET) Nanjing University of Information Science and Technology Nanjing 210044China

In recent years,with the rapid development of deepfake technology,a large number of deepfake videos have emerged on the Internet,which poses a huge threat to national politics,social stability,and personal *** many existing deepfake detection methods exhibit excellent performance for known manipulations,their detection capabilities are not strong when faced with unknown ***,in order to obtain better generalization ability,this paper analyzes global and local inter-frame dynamic inconsistencies from the perspective of spatial and frequency domains,and proposes a Local region Frequency Guided Dynamic Inconsistency Network(LFGDIN).The network includes two parts:Global SpatioTemporal Network(GSTN)and Local Region Frequency Guided Module(LRFGM).The GSTN is responsible for capturing the dynamic information of the entire face,while the LRFGM focuses on extracting the frequency dynamic information of the eyes and *** LRFGM guides the GTSN to concentrate on dynamic inconsistency in some significant local regions through local region alignment,so as to improve the model's detection *** on the three public datasets(FF++,DFDC,and Celeb-DF)show that compared with many recent advanced methods,the proposed method achieves better detection results when detecting deepfake videos of unknown manipulation types.

关键词： deepfake video detection dynamic inconsistency local region local region frequency

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：